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1,400 | The First Detection of Equine Coronavirus in Adult Horses and Foals in Ireland
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832964/
SHA: eee5a9068ade4c6776f189045115a90a5785e983
Authors: Nemoto, Manabu; Schofield, Warren; Cullinane, Ann
Date: 2019-10-14
DOI: 10.3390/v11100946
License: cc-by
Abstract: The objective of this study was to investigate the presence of equine coronavirus (ECoV) in clinical samples submitted to a diagnostic laboratory in Ireland. A total of 424 clinical samples were examined from equids with enteric disease in 24 Irish counties between 2011 and 2015. A real-time reverse transcription polymerase chain reaction was used to detect ECoV RNA. Nucleocapsid, spike and the region from the p4.7 to p12.7 genes of positive samples were sequenced, and sequence and phylogenetic analyses were conducted. Five samples (1.2%) collected in 2011 and 2013 tested positive for ECoV. Positive samples were collected from adult horses, Thoroughbred foals and a donkey foal. Sequence and/or phylogenetic analysis showed that nucleocapsid, spike and p12.7 genes were highly conserved and were closely related to ECoVs identified in other countries. In contrast, the region from p4.7 and the non-coding region following the p4.7 gene had deletions or insertions. The differences in the p4.7 region between the Irish ECoVs and other ECoVs indicated that the Irish viruses were distinguishable from those circulating in other countries. This is the first report of ECoV detected in both foals and adult horses in Ireland.
Text: Equine coronavirus (ECoV) is a positive-stranded RNA virus and belongs to the species Betacoronavirus 1 in the genus Betacoronavirus [1, 2] . The clinical signs associated with ECoV infection during outbreaks in the USA [3] and Japan [4] [5] [6] were fever, anorexia, lethargy and diarrhoea. The same clinical signs were also recorded in an experimental challenge study using Japanese draft horses [7] . The main transmission route is considered to be faecal-oral [7] and ECoV is usually detected in faecal samples. However, the molecular detection of ECoV in faeces from horses with diarrhoea, does not prove causation. Coronaviruses can cause both enteric and respiratory disease in many avian and mammalian species but ECoV is less likely to be found in respiratory secretions than in faeces [8, 9] .
Both molecular and seroepidemiology studies suggest that ECoV may be more prevalent in the USA than in other countries [10] . ECoV was detected in samples collected from equids in 48 states of the USA [11] . In central Kentucky, approximately 30% of both healthy and diarrheic Thoroughbred foals were infected with ECoV [12] . All of the qPCR positive foals with diarrhoea were co-infected with other pathogens such as rotavirus or Clostridium perfringens, suggesting that there was potential for ECoV to be over-diagnosed as a causative agent in complex diseases. In contrast in Japan, although an outbreak of diarrhoea occurred among ECoV-infected draft horses at one racecourse [4] [5] [6] , there have been no similar outbreaks subsequently, and all rectal swabs collected from diarrheic Thoroughbred foals were negative. Furthermore, only 2.5% of the rectal swabs collected from healthy foals in the largest Thoroughbred horse breeding region in Japan were positive for ECoV [13] . In France, 2.8% of 395 faecal samples and 0.5% of 200 respiratory samples collected in 58 counties tested positive for ECoV [9] . Similar to the reports from Japan and France, a low prevalence of ECoV was also observed in the UK [14] , Saudi Arabia and Oman [15] . The objective of this study was to investigate the presence of ECoV in clinical samples submitted to a diagnostic laboratory in Ireland. The samples were tested by real-time reverse transcription polymerase chain reaction (rRT-PCR) as it has been shown to be the most sensitive diagnostic method for ECoV [16] and is routinely employed as an alternative to virus isolation in diagnostic laboratories worldwide, both for timely diagnosis and in epidemiological studies [9, 10] . Virus isolation and biological characterisation were beyond the capacity of this study, which was similar in scope to that of the studies in horse populations in the USA, Europe and Asia [8, 9, 13, 14] . The rRT-PCR assay was performed as previously described using a primer set targeting the nucleocapsid (N) gene (ECoV-380f, ECoV-522r and ECoV-436p) [3] (Table 1) and AgPath-ID One-Step RT-PCR Kit (Thermo Fisher Scientific, MA, USA) according to the manufacturer's instructions. To prove that the extraction was successful and that there was no inhibition during rRT-PCR amplification, an internal positive control primer/probe (PrimerDesign, Southampton, UK) was added to the master mix. Thermal cycling conditions were; 48 • C for 10 min and 95 • C for 10 min, followed by 40 cycles at 94 • C for 15 s and 60 • C for 45 s. The SuperScript III One-Step RT-PCR System with Platinum Taq High Fidelity (Thermo Fisher Scientific, MA, USA) was used for sequencing analysis of two of the five ECoV samples identified. There was inadequate viral nucleic acid in the other three samples for sequencing. The primer sets used to amplify the nucleocapsid (N) gene [4] , the partial spike (S) gene [9] , and the region from the p4.7 to p12.7 genes of non-structural proteins (Oue, personal communication) are shown in Table 1 . The RT-PCR products were sequenced commercially by GATC Biotech (Cologne, Germany). Sequence analysis was performed using the BLAST and CLUSTALW programs, and Vector NTI Advance 11.5 software (Thermo Fisher Scientific, MA, USA). Phylogenetic analysis of nucleotide sequences was conducted with MEGA software Version 5.2 [17] . A phylogenetic tree was constructed based on nucleotide sequences of the K2+G (N gene) and TN93 (S gene) using the maximum likelihood method. MEGA software was used to select the optimal substitution models. Statistical analysis of the tree was performed with the bootstrap test (1000 replicates) for multiple alignments. The complete genome sequences of NC99 (EF446615) [2] , Tokachi09 (LC061272), Obihiro12-1 (LC061273) and Obihiro12-2 (LC061274) [1] , the N (AB671298) and S (AB671299) genes of Obihiro2004, the N gene of Hidaka-No.61/2012 (LC054263) and Hidaka-No.119/2012 (LC054264) [13] , the S gene of ECoV_FRA_2011/1 (KC178705), ECoV_FRA_2011/2 (KC178704), ECoV_FRA_2012/1 (KC178703), ECoV_FRA_2012/2 (KC178702) and ECoV_FRA_2012/3 (KC178701) [9] were used in sequence and/or phylogenetic analysis.
The accession numbers registered in GenBank/EMBL/DDBJ are as follows: the complete sequences of the N gene; 11V11708/IRL (LC149485) and 13V08313/IRL (LC149486), the partial sequences of the S gene; 11V11708/IRL (LC149487) and13V08313/IRL (LC149488) and the complete sequences from the p4.7 to p12.7 genes; 11V11708/IRL (LC149489) and13V08313/IRL (LC149490). One six-week-old foal was the only clinical case on a public Thoroughbred stud farm with approximately 30 mares when it presented with diarrhoea. Recovery took over three weeks during which it received fluid therapy, probiotics, antiulcer medication and antibiotics. The second foal was a 14-day-old filly, which had been hospitalised with diarrhoea two days prior to sample collection. The foal responded well to supportive treatment and at the time of sample collection, the diarrhoea had resolved. The five ECoV positive samples tested negative for equine rotavirus.
The nucleotide sequences of the complete N gene, the partial S gene and the region from the p4.7 to p12.7 genes of two positive samples (11V11708/IRL/2011 and 13V08313/IRL/2013) were determined. The nucleotide identities of the N and S genes of the two Irish ECoVs were 99.8% (1338/1341 nucleotides) and 99.5% (650/653 nucleotides), respectively. The nucleotide identities of the N gene of the two Irish ECoVs and the ECoVs from other continents are summarised in Table 2 .
Phylogenetic analysis was performed for the nucleotide sequences of the complete N and partial S genes (Figure 1 ). The analysis for the N gene showed that Irish ECoVs were independently clustered although they were closely related to Japanese viruses identified after 2009. In the phylogenetic tree of the S gene, Irish ECoVs were closely related to all other ECoVs analysed.
The length of the region from the p4.7 to p12.7 genes in the two viruses was 544 base pairs. Compared with NC99, Irish ECoVs, had a total of 37 nucleotide deletions within p4.7 and the non-coding region following the p4.7 gene. Compared with Obihiro 12-1 and 12-2, Irish ECoVs had a three-nucleotide insertion. When compared with Tokachi09, the Irish ECoVs had a 148-nucleotide insertion (see Figure S1 ). The p12.7 gene of the two Irish ECoVs did not have deletions or insertions, and the nucleotide identities were 98.8-99.7% between these viruses and the other ECoVs (NC99, Tokachi09, Obihiro12-1 and Obihiro12-2).
This study provides the first report of ECoV circulating in Ireland, the third European country with a significant horse industry where the virus has been detected in horses with enteric disease. However, detection of ECoV in faeces samples from horses with enteric disease does not prove
This study provides the first report of ECoV circulating in Ireland, the third European country with a significant horse industry where the virus has been detected in horses with enteric disease. However, detection of ECoV in faeces samples from horses with enteric disease does not prove causation. In this study, 424 samples collected between 2011 and 2015 from equids with enteric disease were tested, and only five samples (1.2%) were positive for ECoV. The inclusion of an internal positive control in the rRT-PCR eliminated the possibility of false negative results due to the presence of PCR inhibitors but the high content of nucleases associated with faeces samples may have caused some RNA degradation. However, this low prevalence of ECoV is similar to that identified in France [9] and among Thoroughbred foals in Japan [13] .
Although ECoV has been identified on three continents, little is known about the genetic and pathogenic diversity in field viruses. In this study, sequence and phylogenetic analysis (Figure 1 ) demonstrated a high level of homology between viruses detected in a donkey and a horse in two provinces in Ireland in different years. This suggests that Irish ECoVs may have low genetic diversity. Compared with the ECoVs of other countries, the N, S and p12.7 genes of the two Irish viruses were highly conserved. In contrast, the region from p4.7 and the non-coding region following the p4.7 gene had deletions or insertions ( Figure S1 ). Because of polymorphism in this region, this region could be useful for epidemiological investigation [5] . The differences in the p4.7 region between the Irish ECoVs and other ECoVs indicated that the viruses in Ireland may be distinguishable from those circulating in other countries. The positive samples were collected in November (1), March (1) and April (3) in this study. Higher case numbers are identified in the USA during the colder months (October to April) [11] , and our results were consistent with the circulation period in USA. It has been reported that outbreaks mainly occurred among adult riding, racing and show horses in USA [11] . The choice of cases to include in the current study may not have been optimal for detection of ECoV as the majority of samples were from foals. However, two positive samples were collected from adult horses in a combined riding school/show jumping yard in the West of Ireland. At the time of sample collection in April 2013, the monthly mean temperatures were below long-term average and in parts of the West, were the coldest in 24 years [18] . Cold weather may have been a predisposing factor to the ECoV infection on the farm.
Two positive samples were collected from Thoroughbred foals. A faeces sample collected from one foal with severe watery diarrhoea and inappetance was positive for ECoV but a sample collected three days later tested negative. A potential difficulty in detecting ECoV from naturally infected horses has been noted previously as serial samples from seven sick horses in the USA suggested that ECoV only persisted for three to nine days in faeces [3] . In both cases, the diarrhoea may have been caused by other unidentified coinfecting pathogens as has been suggested by investigators in the USA [12] . This is the first report of ECoV detection in faeces samples from both foals and adult horses in Ireland. The viruses identified in Ireland are genetically closely related to the Japanese viruses and the results of this study give no indication of significant genetic or phenotypic diversity. In recent years, there has been an increase in awareness and testing for ECoV in the USA and elsewhere [10] . Horse breeding and racing activities in Ireland are the most prominent and important of any country on a per capita basis. There are over 50 Thoroughbred horses per 10,000 of population in Ireland, compared to between three and five for Great Britain, France and the USA [19] . Thus, an investigation of ECoV in Ireland is pertinent not only to increase awareness nationally of the epidemiology of the virus and promote discussion on its clinical importance, but also to inform the industry globally of the health status of Irish horses. Ireland exports horses all over the world. By illustration, in 2016 the country was the second biggest seller of bloodstock at public auctions second only to the USA [19] .
Many questions remain with regard to the clinical significance of ECoV. The outbreak at a draft-horse racetrack in Japan in 2009 affected 132 of approximately 600 horses and resulted in non-starters and the implementation of movement restrictions [4] . However, draft horses appear to have a higher infection rate than other breeds and an outbreak of similar severity has not been reported in Thoroughbred racehorses [10, 20] . The much higher incidence of ECoV positive Thoroughbred foals identified in Kentucky compared to similar populations internationally suggests an increased susceptibility to ECoV infection in that population. In the past, specific environmental factors were associated with extensive reproductive loss in the Kentucky area and to a lesser extent in other states [21] , but predisposing regional factors such as differences in management, environment or husbandry have not been identified for ECoV. It has been suggested that ECoV is a coinfecting agent in foals with diarrhoea and clinical infections have predominantly been reported in adult horses with a mono-infection with EcoV [10] . There was no indication from the results of this study that coronavirus is a major cause of diarrhoea in Irish horses but the introduction of rRT-PCR as a routine diagnostic test will assist in elucidating the significance of this virus to the Irish breeding, racing and sports industries. The primary focus in future will be on testing adult horses that present with anorexia, lethargy, fever and changes in faecal character as a significant association has been demonstrated between this clinical status and molecular detection of ECoV in faeces [11] . | 1,548 | What is the difference between the Tokachi09 and Irish coronavirus genomic sequences? | {
"answer_start": [
8679
],
"text": [
"148-nucleotide insertion"
]
} | 2,126 |
1,401 | The First Detection of Equine Coronavirus in Adult Horses and Foals in Ireland
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832964/
SHA: eee5a9068ade4c6776f189045115a90a5785e983
Authors: Nemoto, Manabu; Schofield, Warren; Cullinane, Ann
Date: 2019-10-14
DOI: 10.3390/v11100946
License: cc-by
Abstract: The objective of this study was to investigate the presence of equine coronavirus (ECoV) in clinical samples submitted to a diagnostic laboratory in Ireland. A total of 424 clinical samples were examined from equids with enteric disease in 24 Irish counties between 2011 and 2015. A real-time reverse transcription polymerase chain reaction was used to detect ECoV RNA. Nucleocapsid, spike and the region from the p4.7 to p12.7 genes of positive samples were sequenced, and sequence and phylogenetic analyses were conducted. Five samples (1.2%) collected in 2011 and 2013 tested positive for ECoV. Positive samples were collected from adult horses, Thoroughbred foals and a donkey foal. Sequence and/or phylogenetic analysis showed that nucleocapsid, spike and p12.7 genes were highly conserved and were closely related to ECoVs identified in other countries. In contrast, the region from p4.7 and the non-coding region following the p4.7 gene had deletions or insertions. The differences in the p4.7 region between the Irish ECoVs and other ECoVs indicated that the Irish viruses were distinguishable from those circulating in other countries. This is the first report of ECoV detected in both foals and adult horses in Ireland.
Text: Equine coronavirus (ECoV) is a positive-stranded RNA virus and belongs to the species Betacoronavirus 1 in the genus Betacoronavirus [1, 2] . The clinical signs associated with ECoV infection during outbreaks in the USA [3] and Japan [4] [5] [6] were fever, anorexia, lethargy and diarrhoea. The same clinical signs were also recorded in an experimental challenge study using Japanese draft horses [7] . The main transmission route is considered to be faecal-oral [7] and ECoV is usually detected in faecal samples. However, the molecular detection of ECoV in faeces from horses with diarrhoea, does not prove causation. Coronaviruses can cause both enteric and respiratory disease in many avian and mammalian species but ECoV is less likely to be found in respiratory secretions than in faeces [8, 9] .
Both molecular and seroepidemiology studies suggest that ECoV may be more prevalent in the USA than in other countries [10] . ECoV was detected in samples collected from equids in 48 states of the USA [11] . In central Kentucky, approximately 30% of both healthy and diarrheic Thoroughbred foals were infected with ECoV [12] . All of the qPCR positive foals with diarrhoea were co-infected with other pathogens such as rotavirus or Clostridium perfringens, suggesting that there was potential for ECoV to be over-diagnosed as a causative agent in complex diseases. In contrast in Japan, although an outbreak of diarrhoea occurred among ECoV-infected draft horses at one racecourse [4] [5] [6] , there have been no similar outbreaks subsequently, and all rectal swabs collected from diarrheic Thoroughbred foals were negative. Furthermore, only 2.5% of the rectal swabs collected from healthy foals in the largest Thoroughbred horse breeding region in Japan were positive for ECoV [13] . In France, 2.8% of 395 faecal samples and 0.5% of 200 respiratory samples collected in 58 counties tested positive for ECoV [9] . Similar to the reports from Japan and France, a low prevalence of ECoV was also observed in the UK [14] , Saudi Arabia and Oman [15] . The objective of this study was to investigate the presence of ECoV in clinical samples submitted to a diagnostic laboratory in Ireland. The samples were tested by real-time reverse transcription polymerase chain reaction (rRT-PCR) as it has been shown to be the most sensitive diagnostic method for ECoV [16] and is routinely employed as an alternative to virus isolation in diagnostic laboratories worldwide, both for timely diagnosis and in epidemiological studies [9, 10] . Virus isolation and biological characterisation were beyond the capacity of this study, which was similar in scope to that of the studies in horse populations in the USA, Europe and Asia [8, 9, 13, 14] . The rRT-PCR assay was performed as previously described using a primer set targeting the nucleocapsid (N) gene (ECoV-380f, ECoV-522r and ECoV-436p) [3] (Table 1) and AgPath-ID One-Step RT-PCR Kit (Thermo Fisher Scientific, MA, USA) according to the manufacturer's instructions. To prove that the extraction was successful and that there was no inhibition during rRT-PCR amplification, an internal positive control primer/probe (PrimerDesign, Southampton, UK) was added to the master mix. Thermal cycling conditions were; 48 • C for 10 min and 95 • C for 10 min, followed by 40 cycles at 94 • C for 15 s and 60 • C for 45 s. The SuperScript III One-Step RT-PCR System with Platinum Taq High Fidelity (Thermo Fisher Scientific, MA, USA) was used for sequencing analysis of two of the five ECoV samples identified. There was inadequate viral nucleic acid in the other three samples for sequencing. The primer sets used to amplify the nucleocapsid (N) gene [4] , the partial spike (S) gene [9] , and the region from the p4.7 to p12.7 genes of non-structural proteins (Oue, personal communication) are shown in Table 1 . The RT-PCR products were sequenced commercially by GATC Biotech (Cologne, Germany). Sequence analysis was performed using the BLAST and CLUSTALW programs, and Vector NTI Advance 11.5 software (Thermo Fisher Scientific, MA, USA). Phylogenetic analysis of nucleotide sequences was conducted with MEGA software Version 5.2 [17] . A phylogenetic tree was constructed based on nucleotide sequences of the K2+G (N gene) and TN93 (S gene) using the maximum likelihood method. MEGA software was used to select the optimal substitution models. Statistical analysis of the tree was performed with the bootstrap test (1000 replicates) for multiple alignments. The complete genome sequences of NC99 (EF446615) [2] , Tokachi09 (LC061272), Obihiro12-1 (LC061273) and Obihiro12-2 (LC061274) [1] , the N (AB671298) and S (AB671299) genes of Obihiro2004, the N gene of Hidaka-No.61/2012 (LC054263) and Hidaka-No.119/2012 (LC054264) [13] , the S gene of ECoV_FRA_2011/1 (KC178705), ECoV_FRA_2011/2 (KC178704), ECoV_FRA_2012/1 (KC178703), ECoV_FRA_2012/2 (KC178702) and ECoV_FRA_2012/3 (KC178701) [9] were used in sequence and/or phylogenetic analysis.
The accession numbers registered in GenBank/EMBL/DDBJ are as follows: the complete sequences of the N gene; 11V11708/IRL (LC149485) and 13V08313/IRL (LC149486), the partial sequences of the S gene; 11V11708/IRL (LC149487) and13V08313/IRL (LC149488) and the complete sequences from the p4.7 to p12.7 genes; 11V11708/IRL (LC149489) and13V08313/IRL (LC149490). One six-week-old foal was the only clinical case on a public Thoroughbred stud farm with approximately 30 mares when it presented with diarrhoea. Recovery took over three weeks during which it received fluid therapy, probiotics, antiulcer medication and antibiotics. The second foal was a 14-day-old filly, which had been hospitalised with diarrhoea two days prior to sample collection. The foal responded well to supportive treatment and at the time of sample collection, the diarrhoea had resolved. The five ECoV positive samples tested negative for equine rotavirus.
The nucleotide sequences of the complete N gene, the partial S gene and the region from the p4.7 to p12.7 genes of two positive samples (11V11708/IRL/2011 and 13V08313/IRL/2013) were determined. The nucleotide identities of the N and S genes of the two Irish ECoVs were 99.8% (1338/1341 nucleotides) and 99.5% (650/653 nucleotides), respectively. The nucleotide identities of the N gene of the two Irish ECoVs and the ECoVs from other continents are summarised in Table 2 .
Phylogenetic analysis was performed for the nucleotide sequences of the complete N and partial S genes (Figure 1 ). The analysis for the N gene showed that Irish ECoVs were independently clustered although they were closely related to Japanese viruses identified after 2009. In the phylogenetic tree of the S gene, Irish ECoVs were closely related to all other ECoVs analysed.
The length of the region from the p4.7 to p12.7 genes in the two viruses was 544 base pairs. Compared with NC99, Irish ECoVs, had a total of 37 nucleotide deletions within p4.7 and the non-coding region following the p4.7 gene. Compared with Obihiro 12-1 and 12-2, Irish ECoVs had a three-nucleotide insertion. When compared with Tokachi09, the Irish ECoVs had a 148-nucleotide insertion (see Figure S1 ). The p12.7 gene of the two Irish ECoVs did not have deletions or insertions, and the nucleotide identities were 98.8-99.7% between these viruses and the other ECoVs (NC99, Tokachi09, Obihiro12-1 and Obihiro12-2).
This study provides the first report of ECoV circulating in Ireland, the third European country with a significant horse industry where the virus has been detected in horses with enteric disease. However, detection of ECoV in faeces samples from horses with enteric disease does not prove
This study provides the first report of ECoV circulating in Ireland, the third European country with a significant horse industry where the virus has been detected in horses with enteric disease. However, detection of ECoV in faeces samples from horses with enteric disease does not prove causation. In this study, 424 samples collected between 2011 and 2015 from equids with enteric disease were tested, and only five samples (1.2%) were positive for ECoV. The inclusion of an internal positive control in the rRT-PCR eliminated the possibility of false negative results due to the presence of PCR inhibitors but the high content of nucleases associated with faeces samples may have caused some RNA degradation. However, this low prevalence of ECoV is similar to that identified in France [9] and among Thoroughbred foals in Japan [13] .
Although ECoV has been identified on three continents, little is known about the genetic and pathogenic diversity in field viruses. In this study, sequence and phylogenetic analysis (Figure 1 ) demonstrated a high level of homology between viruses detected in a donkey and a horse in two provinces in Ireland in different years. This suggests that Irish ECoVs may have low genetic diversity. Compared with the ECoVs of other countries, the N, S and p12.7 genes of the two Irish viruses were highly conserved. In contrast, the region from p4.7 and the non-coding region following the p4.7 gene had deletions or insertions ( Figure S1 ). Because of polymorphism in this region, this region could be useful for epidemiological investigation [5] . The differences in the p4.7 region between the Irish ECoVs and other ECoVs indicated that the viruses in Ireland may be distinguishable from those circulating in other countries. The positive samples were collected in November (1), March (1) and April (3) in this study. Higher case numbers are identified in the USA during the colder months (October to April) [11] , and our results were consistent with the circulation period in USA. It has been reported that outbreaks mainly occurred among adult riding, racing and show horses in USA [11] . The choice of cases to include in the current study may not have been optimal for detection of ECoV as the majority of samples were from foals. However, two positive samples were collected from adult horses in a combined riding school/show jumping yard in the West of Ireland. At the time of sample collection in April 2013, the monthly mean temperatures were below long-term average and in parts of the West, were the coldest in 24 years [18] . Cold weather may have been a predisposing factor to the ECoV infection on the farm.
Two positive samples were collected from Thoroughbred foals. A faeces sample collected from one foal with severe watery diarrhoea and inappetance was positive for ECoV but a sample collected three days later tested negative. A potential difficulty in detecting ECoV from naturally infected horses has been noted previously as serial samples from seven sick horses in the USA suggested that ECoV only persisted for three to nine days in faeces [3] . In both cases, the diarrhoea may have been caused by other unidentified coinfecting pathogens as has been suggested by investigators in the USA [12] . This is the first report of ECoV detection in faeces samples from both foals and adult horses in Ireland. The viruses identified in Ireland are genetically closely related to the Japanese viruses and the results of this study give no indication of significant genetic or phenotypic diversity. In recent years, there has been an increase in awareness and testing for ECoV in the USA and elsewhere [10] . Horse breeding and racing activities in Ireland are the most prominent and important of any country on a per capita basis. There are over 50 Thoroughbred horses per 10,000 of population in Ireland, compared to between three and five for Great Britain, France and the USA [19] . Thus, an investigation of ECoV in Ireland is pertinent not only to increase awareness nationally of the epidemiology of the virus and promote discussion on its clinical importance, but also to inform the industry globally of the health status of Irish horses. Ireland exports horses all over the world. By illustration, in 2016 the country was the second biggest seller of bloodstock at public auctions second only to the USA [19] .
Many questions remain with regard to the clinical significance of ECoV. The outbreak at a draft-horse racetrack in Japan in 2009 affected 132 of approximately 600 horses and resulted in non-starters and the implementation of movement restrictions [4] . However, draft horses appear to have a higher infection rate than other breeds and an outbreak of similar severity has not been reported in Thoroughbred racehorses [10, 20] . The much higher incidence of ECoV positive Thoroughbred foals identified in Kentucky compared to similar populations internationally suggests an increased susceptibility to ECoV infection in that population. In the past, specific environmental factors were associated with extensive reproductive loss in the Kentucky area and to a lesser extent in other states [21] , but predisposing regional factors such as differences in management, environment or husbandry have not been identified for ECoV. It has been suggested that ECoV is a coinfecting agent in foals with diarrhoea and clinical infections have predominantly been reported in adult horses with a mono-infection with EcoV [10] . There was no indication from the results of this study that coronavirus is a major cause of diarrhoea in Irish horses but the introduction of rRT-PCR as a routine diagnostic test will assist in elucidating the significance of this virus to the Irish breeding, racing and sports industries. The primary focus in future will be on testing adult horses that present with anorexia, lethargy, fever and changes in faecal character as a significant association has been demonstrated between this clinical status and molecular detection of ECoV in faeces [11] . | 1,548 | What suggests that Irish equine coronaviruses may have a low genetic diversity? | {
"answer_start": [
10276
],
"text": [
"high level of homology between viruses"
]
} | 2,127 |
1,402 | The First Detection of Equine Coronavirus in Adult Horses and Foals in Ireland
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832964/
SHA: eee5a9068ade4c6776f189045115a90a5785e983
Authors: Nemoto, Manabu; Schofield, Warren; Cullinane, Ann
Date: 2019-10-14
DOI: 10.3390/v11100946
License: cc-by
Abstract: The objective of this study was to investigate the presence of equine coronavirus (ECoV) in clinical samples submitted to a diagnostic laboratory in Ireland. A total of 424 clinical samples were examined from equids with enteric disease in 24 Irish counties between 2011 and 2015. A real-time reverse transcription polymerase chain reaction was used to detect ECoV RNA. Nucleocapsid, spike and the region from the p4.7 to p12.7 genes of positive samples were sequenced, and sequence and phylogenetic analyses were conducted. Five samples (1.2%) collected in 2011 and 2013 tested positive for ECoV. Positive samples were collected from adult horses, Thoroughbred foals and a donkey foal. Sequence and/or phylogenetic analysis showed that nucleocapsid, spike and p12.7 genes were highly conserved and were closely related to ECoVs identified in other countries. In contrast, the region from p4.7 and the non-coding region following the p4.7 gene had deletions or insertions. The differences in the p4.7 region between the Irish ECoVs and other ECoVs indicated that the Irish viruses were distinguishable from those circulating in other countries. This is the first report of ECoV detected in both foals and adult horses in Ireland.
Text: Equine coronavirus (ECoV) is a positive-stranded RNA virus and belongs to the species Betacoronavirus 1 in the genus Betacoronavirus [1, 2] . The clinical signs associated with ECoV infection during outbreaks in the USA [3] and Japan [4] [5] [6] were fever, anorexia, lethargy and diarrhoea. The same clinical signs were also recorded in an experimental challenge study using Japanese draft horses [7] . The main transmission route is considered to be faecal-oral [7] and ECoV is usually detected in faecal samples. However, the molecular detection of ECoV in faeces from horses with diarrhoea, does not prove causation. Coronaviruses can cause both enteric and respiratory disease in many avian and mammalian species but ECoV is less likely to be found in respiratory secretions than in faeces [8, 9] .
Both molecular and seroepidemiology studies suggest that ECoV may be more prevalent in the USA than in other countries [10] . ECoV was detected in samples collected from equids in 48 states of the USA [11] . In central Kentucky, approximately 30% of both healthy and diarrheic Thoroughbred foals were infected with ECoV [12] . All of the qPCR positive foals with diarrhoea were co-infected with other pathogens such as rotavirus or Clostridium perfringens, suggesting that there was potential for ECoV to be over-diagnosed as a causative agent in complex diseases. In contrast in Japan, although an outbreak of diarrhoea occurred among ECoV-infected draft horses at one racecourse [4] [5] [6] , there have been no similar outbreaks subsequently, and all rectal swabs collected from diarrheic Thoroughbred foals were negative. Furthermore, only 2.5% of the rectal swabs collected from healthy foals in the largest Thoroughbred horse breeding region in Japan were positive for ECoV [13] . In France, 2.8% of 395 faecal samples and 0.5% of 200 respiratory samples collected in 58 counties tested positive for ECoV [9] . Similar to the reports from Japan and France, a low prevalence of ECoV was also observed in the UK [14] , Saudi Arabia and Oman [15] . The objective of this study was to investigate the presence of ECoV in clinical samples submitted to a diagnostic laboratory in Ireland. The samples were tested by real-time reverse transcription polymerase chain reaction (rRT-PCR) as it has been shown to be the most sensitive diagnostic method for ECoV [16] and is routinely employed as an alternative to virus isolation in diagnostic laboratories worldwide, both for timely diagnosis and in epidemiological studies [9, 10] . Virus isolation and biological characterisation were beyond the capacity of this study, which was similar in scope to that of the studies in horse populations in the USA, Europe and Asia [8, 9, 13, 14] . The rRT-PCR assay was performed as previously described using a primer set targeting the nucleocapsid (N) gene (ECoV-380f, ECoV-522r and ECoV-436p) [3] (Table 1) and AgPath-ID One-Step RT-PCR Kit (Thermo Fisher Scientific, MA, USA) according to the manufacturer's instructions. To prove that the extraction was successful and that there was no inhibition during rRT-PCR amplification, an internal positive control primer/probe (PrimerDesign, Southampton, UK) was added to the master mix. Thermal cycling conditions were; 48 • C for 10 min and 95 • C for 10 min, followed by 40 cycles at 94 • C for 15 s and 60 • C for 45 s. The SuperScript III One-Step RT-PCR System with Platinum Taq High Fidelity (Thermo Fisher Scientific, MA, USA) was used for sequencing analysis of two of the five ECoV samples identified. There was inadequate viral nucleic acid in the other three samples for sequencing. The primer sets used to amplify the nucleocapsid (N) gene [4] , the partial spike (S) gene [9] , and the region from the p4.7 to p12.7 genes of non-structural proteins (Oue, personal communication) are shown in Table 1 . The RT-PCR products were sequenced commercially by GATC Biotech (Cologne, Germany). Sequence analysis was performed using the BLAST and CLUSTALW programs, and Vector NTI Advance 11.5 software (Thermo Fisher Scientific, MA, USA). Phylogenetic analysis of nucleotide sequences was conducted with MEGA software Version 5.2 [17] . A phylogenetic tree was constructed based on nucleotide sequences of the K2+G (N gene) and TN93 (S gene) using the maximum likelihood method. MEGA software was used to select the optimal substitution models. Statistical analysis of the tree was performed with the bootstrap test (1000 replicates) for multiple alignments. The complete genome sequences of NC99 (EF446615) [2] , Tokachi09 (LC061272), Obihiro12-1 (LC061273) and Obihiro12-2 (LC061274) [1] , the N (AB671298) and S (AB671299) genes of Obihiro2004, the N gene of Hidaka-No.61/2012 (LC054263) and Hidaka-No.119/2012 (LC054264) [13] , the S gene of ECoV_FRA_2011/1 (KC178705), ECoV_FRA_2011/2 (KC178704), ECoV_FRA_2012/1 (KC178703), ECoV_FRA_2012/2 (KC178702) and ECoV_FRA_2012/3 (KC178701) [9] were used in sequence and/or phylogenetic analysis.
The accession numbers registered in GenBank/EMBL/DDBJ are as follows: the complete sequences of the N gene; 11V11708/IRL (LC149485) and 13V08313/IRL (LC149486), the partial sequences of the S gene; 11V11708/IRL (LC149487) and13V08313/IRL (LC149488) and the complete sequences from the p4.7 to p12.7 genes; 11V11708/IRL (LC149489) and13V08313/IRL (LC149490). One six-week-old foal was the only clinical case on a public Thoroughbred stud farm with approximately 30 mares when it presented with diarrhoea. Recovery took over three weeks during which it received fluid therapy, probiotics, antiulcer medication and antibiotics. The second foal was a 14-day-old filly, which had been hospitalised with diarrhoea two days prior to sample collection. The foal responded well to supportive treatment and at the time of sample collection, the diarrhoea had resolved. The five ECoV positive samples tested negative for equine rotavirus.
The nucleotide sequences of the complete N gene, the partial S gene and the region from the p4.7 to p12.7 genes of two positive samples (11V11708/IRL/2011 and 13V08313/IRL/2013) were determined. The nucleotide identities of the N and S genes of the two Irish ECoVs were 99.8% (1338/1341 nucleotides) and 99.5% (650/653 nucleotides), respectively. The nucleotide identities of the N gene of the two Irish ECoVs and the ECoVs from other continents are summarised in Table 2 .
Phylogenetic analysis was performed for the nucleotide sequences of the complete N and partial S genes (Figure 1 ). The analysis for the N gene showed that Irish ECoVs were independently clustered although they were closely related to Japanese viruses identified after 2009. In the phylogenetic tree of the S gene, Irish ECoVs were closely related to all other ECoVs analysed.
The length of the region from the p4.7 to p12.7 genes in the two viruses was 544 base pairs. Compared with NC99, Irish ECoVs, had a total of 37 nucleotide deletions within p4.7 and the non-coding region following the p4.7 gene. Compared with Obihiro 12-1 and 12-2, Irish ECoVs had a three-nucleotide insertion. When compared with Tokachi09, the Irish ECoVs had a 148-nucleotide insertion (see Figure S1 ). The p12.7 gene of the two Irish ECoVs did not have deletions or insertions, and the nucleotide identities were 98.8-99.7% between these viruses and the other ECoVs (NC99, Tokachi09, Obihiro12-1 and Obihiro12-2).
This study provides the first report of ECoV circulating in Ireland, the third European country with a significant horse industry where the virus has been detected in horses with enteric disease. However, detection of ECoV in faeces samples from horses with enteric disease does not prove
This study provides the first report of ECoV circulating in Ireland, the third European country with a significant horse industry where the virus has been detected in horses with enteric disease. However, detection of ECoV in faeces samples from horses with enteric disease does not prove causation. In this study, 424 samples collected between 2011 and 2015 from equids with enteric disease were tested, and only five samples (1.2%) were positive for ECoV. The inclusion of an internal positive control in the rRT-PCR eliminated the possibility of false negative results due to the presence of PCR inhibitors but the high content of nucleases associated with faeces samples may have caused some RNA degradation. However, this low prevalence of ECoV is similar to that identified in France [9] and among Thoroughbred foals in Japan [13] .
Although ECoV has been identified on three continents, little is known about the genetic and pathogenic diversity in field viruses. In this study, sequence and phylogenetic analysis (Figure 1 ) demonstrated a high level of homology between viruses detected in a donkey and a horse in two provinces in Ireland in different years. This suggests that Irish ECoVs may have low genetic diversity. Compared with the ECoVs of other countries, the N, S and p12.7 genes of the two Irish viruses were highly conserved. In contrast, the region from p4.7 and the non-coding region following the p4.7 gene had deletions or insertions ( Figure S1 ). Because of polymorphism in this region, this region could be useful for epidemiological investigation [5] . The differences in the p4.7 region between the Irish ECoVs and other ECoVs indicated that the viruses in Ireland may be distinguishable from those circulating in other countries. The positive samples were collected in November (1), March (1) and April (3) in this study. Higher case numbers are identified in the USA during the colder months (October to April) [11] , and our results were consistent with the circulation period in USA. It has been reported that outbreaks mainly occurred among adult riding, racing and show horses in USA [11] . The choice of cases to include in the current study may not have been optimal for detection of ECoV as the majority of samples were from foals. However, two positive samples were collected from adult horses in a combined riding school/show jumping yard in the West of Ireland. At the time of sample collection in April 2013, the monthly mean temperatures were below long-term average and in parts of the West, were the coldest in 24 years [18] . Cold weather may have been a predisposing factor to the ECoV infection on the farm.
Two positive samples were collected from Thoroughbred foals. A faeces sample collected from one foal with severe watery diarrhoea and inappetance was positive for ECoV but a sample collected three days later tested negative. A potential difficulty in detecting ECoV from naturally infected horses has been noted previously as serial samples from seven sick horses in the USA suggested that ECoV only persisted for three to nine days in faeces [3] . In both cases, the diarrhoea may have been caused by other unidentified coinfecting pathogens as has been suggested by investigators in the USA [12] . This is the first report of ECoV detection in faeces samples from both foals and adult horses in Ireland. The viruses identified in Ireland are genetically closely related to the Japanese viruses and the results of this study give no indication of significant genetic or phenotypic diversity. In recent years, there has been an increase in awareness and testing for ECoV in the USA and elsewhere [10] . Horse breeding and racing activities in Ireland are the most prominent and important of any country on a per capita basis. There are over 50 Thoroughbred horses per 10,000 of population in Ireland, compared to between three and five for Great Britain, France and the USA [19] . Thus, an investigation of ECoV in Ireland is pertinent not only to increase awareness nationally of the epidemiology of the virus and promote discussion on its clinical importance, but also to inform the industry globally of the health status of Irish horses. Ireland exports horses all over the world. By illustration, in 2016 the country was the second biggest seller of bloodstock at public auctions second only to the USA [19] .
Many questions remain with regard to the clinical significance of ECoV. The outbreak at a draft-horse racetrack in Japan in 2009 affected 132 of approximately 600 horses and resulted in non-starters and the implementation of movement restrictions [4] . However, draft horses appear to have a higher infection rate than other breeds and an outbreak of similar severity has not been reported in Thoroughbred racehorses [10, 20] . The much higher incidence of ECoV positive Thoroughbred foals identified in Kentucky compared to similar populations internationally suggests an increased susceptibility to ECoV infection in that population. In the past, specific environmental factors were associated with extensive reproductive loss in the Kentucky area and to a lesser extent in other states [21] , but predisposing regional factors such as differences in management, environment or husbandry have not been identified for ECoV. It has been suggested that ECoV is a coinfecting agent in foals with diarrhoea and clinical infections have predominantly been reported in adult horses with a mono-infection with EcoV [10] . There was no indication from the results of this study that coronavirus is a major cause of diarrhoea in Irish horses but the introduction of rRT-PCR as a routine diagnostic test will assist in elucidating the significance of this virus to the Irish breeding, racing and sports industries. The primary focus in future will be on testing adult horses that present with anorexia, lethargy, fever and changes in faecal character as a significant association has been demonstrated between this clinical status and molecular detection of ECoV in faeces [11] . | 1,548 | Where have most outbreaks of equine coronavirus occurred in the United States? | {
"answer_start": [
11305
],
"text": [
"adult riding, racing and show horses"
]
} | 2,128 |
1,403 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | How many COVID-19 cases were confirmed on the Diamond Princess cruise ship? | {
"answer_start": [
451
],
"text": [
"199"
]
} | 1,187 |
1,404 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | What was the time period of peak infection of COVID-19 on the Diamond Princess cruise ship? | {
"answer_start": [
710
],
"text": [
"2 to 4 February 2020,"
]
} | 1,188 |
1,405 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | With the intervention of movement restrictions starting on 5th February 2020, what were the confirmed cases for COVID-19, were limited to? | {
"answer_start": [
1194
],
"text": [
"102 and 47 cases, respectively."
]
} | 1,190 |
1,406 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | Who was the first COVID-19 identified case patient on the Diamond Princess cruise ship? | {
"answer_start": [
1795
],
"text": [
"case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards."
]
} | 1,191 |
1,407 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | When was the first passenger patient on the Diamond Princess cruise ship diagnosed with COVID-19? | {
"answer_start": [
1792
],
"text": [
"he case was diagnosed on 1 February"
]
} | 1,192 |
1,408 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | How many COVID-19 cases were confirmed on the Diamond Princess cruise ship? | {
"answer_start": [
2039
],
"text": [
"Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported"
]
} | 1,193 |
1,409 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | What is the estimated mean incubation period for COVID-19 infection on the Diamond Princess cruise ship? | {
"answer_start": [
2739
],
"text": [
"about 5.0 days"
]
} | 1,194 |
1,410 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | What was the effect of movement restriction policy on the Diamond Princess cruise ship started on 5th February 2020. | {
"answer_start": [
7231
],
"text": [
"highly successful in greatly reducing the number of secondary transmissions on board."
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} | 1,196 |
1,411 | Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
https://doi.org/10.3390/jcm9030657
SHA: 0938d2fb07611897abf38cea727ddbeea77b73d9
Authors: Nishiura, Hiroshi
Date: 2020
DOI: 10.3390/jcm9030657
License: cc-by
Abstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As the case was diagnosed on 1 February, the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported.
One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure.
I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR.
We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy
where E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership.
Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :
where is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively.
A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored.
The author declares no conflict of interest. | 2,555 | What would have the number of confirmed cases on the Diamond Princess cruise ship, without a movement restriction starting on the 5th February 2020? | {
"answer_start": [
1008
],
"text": [
" the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases,"
]
} | 1,189 |
1,412 | Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078228/
SHA: 1cf54d1c77b7f0494ab971429d26e0e199952d09
Authors: Liu, Jia; Cao, Ruiyuan; Xu, Mingyue; Wang, Xi; Zhang, Huanyu; Hu, Hengrui; Li, Yufeng; Hu, Zhihong; Zhong, Wu; Wang, Manli
Date: 2020-03-18
DOI: 10.1038/s41421-020-0156-0
License: cc-by
Abstract: nan
Text: Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro Jia Liu 1 , Ruiyuan Cao 2 , Mingyue Xu 1,3 , Xi Wang 1 , Huanyu Zhang 1,3 , Hengrui Hu 1,3 , Yufeng Li 1,3 , Zhihong Hu 1 , Wu Zhong 2 and Manli Wang 1 Dear Editor, The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/2019-nCoV) poses a serious threat to global public health and local economies. As of March 3, 2020, over 80,000 cases have been confirmed in China, including 2946 deaths as well as over 10,566 confirmed cases in 72 other countries. Such huge numbers of infected and dead people call for an urgent demand of effective, available, and affordable drugs to control and diminish the epidemic.
We have recently reported that two drugs, remdesivir (GS-5734) and chloroquine (CQ) phosphate, efficiently inhibited SARS-CoV-2 infection in vitro 1 . Remdesivir is a nucleoside analog prodrug developed by Gilead Sciences (USA). A recent case report showed that treatment with remdesivir improved the clinical condition of the first patient infected by SARS-CoV-2 in the United States 2 , and a phase III clinical trial of remdesivir against SARS-CoV-2 was launched in Wuhan on February 4, 2020. However, as an experimental drug, remdesivir is not expected to be largely available for treating a very large number of patients in a timely manner. Therefore, of the two potential drugs, CQ appears to be the drug of choice for large-scale use due to its availability, proven safety record, and a relatively low cost. In light of the preliminary clinical data, CQ has been added to the list of trial drugs in the Guidelines for the Diagnosis and Treatment of COVID-19 (sixth edition) published by National Health Commission of the People's Republic of China. CQ (N4-(7-Chloro-4-quinolinyl)-N1,N1-diethyl-1,4pentanediamine) has long been used to treat malaria and amebiasis. However, Plasmodium falciparum developed widespread resistance to it, and with the development of new antimalarials, it has become a choice for the prophylaxis of malaria. In addition, an overdose of CQ can cause acute poisoning and death 3 . In the past years, due to infrequent utilization of CQ in clinical practice, its production and market supply was greatly reduced, at least in China. Hydroxychloroquine (HCQ) sulfate, a derivative of CQ, was first synthesized in 1946 by introducing a hydroxyl group into CQ and was demonstrated to be much less (~40%) toxic than CQ in animals 4 . More importantly, HCQ is still widely available to treat autoimmune diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Since CQ and HCQ share similar chemical structures and mechanisms of acting as a weak base and immunomodulator, it is easy to conjure up the idea that HCQ may be a potent candidate to treat infection by SARS-CoV-2. Actually, as of February 23, 2020, seven clinical trial registries were found in Chinese Clinical Trial Registry (http://www.chictr.org.cn) for using HCQ to treat COVID-19. Whether HCQ is as efficacious as CQ in treating SARS-CoV-2 infection still lacks the experimental evidence.
To this end, we evaluated the antiviral effect of HCQ against SARS-CoV-2 infection in comparison to CQ in vitro. First, the cytotoxicity of HCQ and CQ in African green monkey kidney VeroE6 cells (ATCC-1586) was measured by standard CCK8 assay, and the result showed © The Author(s) 2020
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. (Fig. 1a) . To better compare the antiviral activity of CQ versus HCQ, the dose-response curves of the two compounds against SARS-CoV-2 were determined at four different multiplicities of infection (MOIs) by quantification of viral RNA copy numbers in the cell supernatant at 48 h post infection (p.i.). The data summarized in Fig. 1a and Supplementary Table S1 show that, at all MOIs (0.01, 0.02, 0.2, and 0.8), the 50% maximal effective concentration (EC 50 ) for CQ (2.71, 3.81, 7.14, and 7.36 μM) was lower than that of HCQ (4.51, 4.06, 17.31, and 12.96 μM). The differences in EC 50 values were statistically significant at an MOI of 0.01 (P < 0.05) and MOI of 0.2 (P < 0.001) (Supplementary Table S1 ). It is worth noting that the EC 50 values of CQ seemed to be a little higher than that in our previous report (1.13 μM at an MOI of 0.05) 1 , which is likely due to the adaptation of the virus in cell culture that significantly increased viral infectivity upon continuous passaging. Consequently, the selectivity index (SI = CC 50 /EC 50 ) of CQ (100.81, 71.71, 38.26, and 37.12) was higher than that of HCQ (55.32, 61.45, 14.41, 19.25) at MOIs of 0.01, 0.02, 0.2, and 0.8, respectively. These results were corroborated by immunofluorescence microscopy as evidenced by different expression levels of virus nucleoprotein (NP) at the indicated drug concentrations at 48 h p.i. (Supplementary Fig. S1 ). Taken together, the data suggest that the anti-SARS-CoV-2 activity of HCQ seems to be less potent compared to CQ, at least at certain MOIs.
Both CQ and HCQ are weak bases that are known to elevate the pH of acidic intracellular organelles, such as endosomes/lysosomes, essential for membrane fusion 5 . In addition, CQ could inhibit SARS-CoV entry through changing the glycosylation of ACE2 receptor and spike protein 6 . Time-of-addition experiment confirmed that HCQ effectively inhibited the entry step, as well as the post-entry stages of SARS-CoV-2, which was also found upon CQ treatment (Supplementary Fig. S2 ). To further explore the detailed mechanism of action of CQ and HCQ in inhibiting virus entry, co-localization of virions with early endosomes (EEs) or endolysosomes (ELs) was analyzed by immunofluorescence analysis (IFA) and confocal microscopy. Quantification analysis showed that, at 90 min p.i. in untreated cells, 16.2% of internalized virions (anti-NP, red) were observed in early endosome antigen 1 (EEA1)-positive EEs (green), while more virions (34.3%) were transported into the late endosomal-lysosomal protein LAMP1 + ELs (green) (n > 30 cells for each group). By contrast, in the presence of CQ or HCQ, significantly more virions (35.3% for CQ and 29.2% for HCQ; P < 0.001) were detected in the EEs, while only very few virions (2.4% for CQ and 0.03% for HCQ; P < 0.001) were found to be co-localized with LAMP1 + ELs (n > 30 cells) (Fig. 1b, c) . This suggested that both CQ and HCQ blocked the transport of SARS-CoV-2 from EEs to ELs, which appears to be a requirement to release the viral genome as in the case of SARS-CoV 7 .
Interestingly, we found that CQ and HCQ treatment caused noticeable changes in the number and size/morphology of EEs and ELs (Fig. 1c) . In the untreated cells, most EEs were much smaller than ELs (Fig. 1c) . In CQand HCQ-treated cells, abnormally enlarged EE vesicles were observed (Fig. 1c , arrows in the upper panels), many of which are even larger than ELs in the untreated cells. This is in agreement with previous report that treatment with CQ induced the formation of expanded cytoplasmic vesicles 8 . Within the EE vesicles, virions (red) were localized around the membrane (green) of the vesicle. CQ treatment did not cause obvious changes in the number and size of ELs; however, the regular vesicle structure seemed to be disrupted, at least partially. By contrast, in HCQ-treated cells, the size and number of ELs increased significantly (Fig. 1c , arrows in the lower panels).
Since acidification is crucial for endosome maturation and function, we surmise that endosome maturation might be blocked at intermediate stages of endocytosis, resulting in failure of further transport of virions to the ultimate releasing site. CQ was reported to elevate the pH (see figure on previous page) Fig. 1 Comparative antiviral efficacy and mechanism of action of CQ and HCQ against SARS-CoV-2 infection in vitro. a Cytotoxicity and antiviral activities of CQ and HCQ. The cytotoxicity of the two drugs in Vero E6 cells was determined by CCK-8 assays. Vero E6 cells were treated with different doses of either compound or with PBS in the controls for 1 h and then infected with SARS-CoV-2 at MOIs of 0.01, 0.02, 0.2, and 0.8. The virus yield in the cell supernatant was quantified by qRT-PCR at 48 h p.i. Y-axis represents the mean of percent inhibition normalized to the PBS group. The experiments were repeated twice. b, c Mechanism of CQ and HCQ in inhibiting virus entry. Vero E6 cells were treated with CQ or HCQ (50 μM) for 1 h, followed by virus binding (MOI = 10) at 4°C for 1 h. Then the unbound virions were removed, and the cells were further supplemented with fresh drug-containing medium at 37°C for 90 min before being fixed and stained with IFA using anti-NP antibody for virions (red) and antibodies against EEA1 for EEs (green) or LAMP1 for ELs (green). The nuclei (blue) were stained with Hoechst dye. The portion of virions that co-localized with EEs or ELs in each group (n > 30 cells) was quantified and is shown in b. Representative confocal microscopic images of viral particles (red), EEA1 + EEs (green), or LAMP1 + ELs (green) in each group are displayed in c. The enlarged images in the boxes indicate a single vesicle-containing virion. The arrows indicated the abnormally enlarged vesicles. Bars, 5 μm. Statistical analysis was performed using a one-way analysis of variance (ANOVA) with GraphPad Prism (F = 102.8, df = 5,182, ***P < 0.001).
of lysosome from about 4.5 to 6.5 at 100 μM 9 . To our knowledge, there is a lack of studies on the impact of HCQ on the morphology and pH values of endosomes/ lysosomes. Our observations suggested that the mode of actions of CQ and HCQ appear to be distinct in certain aspects.
It has been reported that oral absorption of CQ and HCQ in humans is very efficient. In animals, both drugs share similar tissue distribution patterns, with high concentrations in the liver, spleen, kidney, and lung reaching levels of 200-700 times higher than those in the plasma 10 . It was reported that safe dosage (6-6.5 mg/kg per day) of HCQ sulfate could generate serum levels of 1.4-1.5 μM in humans 11 . Therefore, with a safe dosage, HCQ concentration in the above tissues is likely to be achieved to inhibit SARS-CoV-2 infection.
Clinical investigation found that high concentration of cytokines were detected in the plasma of critically ill patients infected with SARS-CoV-2, suggesting that cytokine storm was associated with disease severity 12 . Other than its direct antiviral activity, HCQ is a safe and successful anti-inflammatory agent that has been used extensively in autoimmune diseases and can significantly decrease the production of cytokines and, in particular, pro-inflammatory factors. Therefore, in COVID-19 patients, HCQ may also contribute to attenuating the inflammatory response. In conclusion, our results show that HCQ can efficiently inhibit SARS-CoV-2 infection in vitro. In combination with its anti-inflammatory function, we predict that the drug has a good potential to combat the disease. This possibility awaits confirmation by clinical trials. We need to point out, although HCQ is less toxic than CQ, prolonged and overdose usage can still cause poisoning. And the relatively low SI of HCQ requires careful designing and conducting of clinical trials to achieve efficient and safe control of the SARS-CoV-2 infection. | 2,439 | In vitro comparison of antiviral activity of Chloroquine(CQ) and Hydroxychloroquine(HCQ) against COVID-19? | {
"answer_start": [
4794
],
"text": [
"compare the antiviral activity of CQ versus HCQ, the dose-response curves"
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} | 655 |
1,413 | Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078228/
SHA: 1cf54d1c77b7f0494ab971429d26e0e199952d09
Authors: Liu, Jia; Cao, Ruiyuan; Xu, Mingyue; Wang, Xi; Zhang, Huanyu; Hu, Hengrui; Li, Yufeng; Hu, Zhihong; Zhong, Wu; Wang, Manli
Date: 2020-03-18
DOI: 10.1038/s41421-020-0156-0
License: cc-by
Abstract: nan
Text: Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro Jia Liu 1 , Ruiyuan Cao 2 , Mingyue Xu 1,3 , Xi Wang 1 , Huanyu Zhang 1,3 , Hengrui Hu 1,3 , Yufeng Li 1,3 , Zhihong Hu 1 , Wu Zhong 2 and Manli Wang 1 Dear Editor, The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/2019-nCoV) poses a serious threat to global public health and local economies. As of March 3, 2020, over 80,000 cases have been confirmed in China, including 2946 deaths as well as over 10,566 confirmed cases in 72 other countries. Such huge numbers of infected and dead people call for an urgent demand of effective, available, and affordable drugs to control and diminish the epidemic.
We have recently reported that two drugs, remdesivir (GS-5734) and chloroquine (CQ) phosphate, efficiently inhibited SARS-CoV-2 infection in vitro 1 . Remdesivir is a nucleoside analog prodrug developed by Gilead Sciences (USA). A recent case report showed that treatment with remdesivir improved the clinical condition of the first patient infected by SARS-CoV-2 in the United States 2 , and a phase III clinical trial of remdesivir against SARS-CoV-2 was launched in Wuhan on February 4, 2020. However, as an experimental drug, remdesivir is not expected to be largely available for treating a very large number of patients in a timely manner. Therefore, of the two potential drugs, CQ appears to be the drug of choice for large-scale use due to its availability, proven safety record, and a relatively low cost. In light of the preliminary clinical data, CQ has been added to the list of trial drugs in the Guidelines for the Diagnosis and Treatment of COVID-19 (sixth edition) published by National Health Commission of the People's Republic of China. CQ (N4-(7-Chloro-4-quinolinyl)-N1,N1-diethyl-1,4pentanediamine) has long been used to treat malaria and amebiasis. However, Plasmodium falciparum developed widespread resistance to it, and with the development of new antimalarials, it has become a choice for the prophylaxis of malaria. In addition, an overdose of CQ can cause acute poisoning and death 3 . In the past years, due to infrequent utilization of CQ in clinical practice, its production and market supply was greatly reduced, at least in China. Hydroxychloroquine (HCQ) sulfate, a derivative of CQ, was first synthesized in 1946 by introducing a hydroxyl group into CQ and was demonstrated to be much less (~40%) toxic than CQ in animals 4 . More importantly, HCQ is still widely available to treat autoimmune diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Since CQ and HCQ share similar chemical structures and mechanisms of acting as a weak base and immunomodulator, it is easy to conjure up the idea that HCQ may be a potent candidate to treat infection by SARS-CoV-2. Actually, as of February 23, 2020, seven clinical trial registries were found in Chinese Clinical Trial Registry (http://www.chictr.org.cn) for using HCQ to treat COVID-19. Whether HCQ is as efficacious as CQ in treating SARS-CoV-2 infection still lacks the experimental evidence.
To this end, we evaluated the antiviral effect of HCQ against SARS-CoV-2 infection in comparison to CQ in vitro. First, the cytotoxicity of HCQ and CQ in African green monkey kidney VeroE6 cells (ATCC-1586) was measured by standard CCK8 assay, and the result showed © The Author(s) 2020
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. (Fig. 1a) . To better compare the antiviral activity of CQ versus HCQ, the dose-response curves of the two compounds against SARS-CoV-2 were determined at four different multiplicities of infection (MOIs) by quantification of viral RNA copy numbers in the cell supernatant at 48 h post infection (p.i.). The data summarized in Fig. 1a and Supplementary Table S1 show that, at all MOIs (0.01, 0.02, 0.2, and 0.8), the 50% maximal effective concentration (EC 50 ) for CQ (2.71, 3.81, 7.14, and 7.36 μM) was lower than that of HCQ (4.51, 4.06, 17.31, and 12.96 μM). The differences in EC 50 values were statistically significant at an MOI of 0.01 (P < 0.05) and MOI of 0.2 (P < 0.001) (Supplementary Table S1 ). It is worth noting that the EC 50 values of CQ seemed to be a little higher than that in our previous report (1.13 μM at an MOI of 0.05) 1 , which is likely due to the adaptation of the virus in cell culture that significantly increased viral infectivity upon continuous passaging. Consequently, the selectivity index (SI = CC 50 /EC 50 ) of CQ (100.81, 71.71, 38.26, and 37.12) was higher than that of HCQ (55.32, 61.45, 14.41, 19.25) at MOIs of 0.01, 0.02, 0.2, and 0.8, respectively. These results were corroborated by immunofluorescence microscopy as evidenced by different expression levels of virus nucleoprotein (NP) at the indicated drug concentrations at 48 h p.i. (Supplementary Fig. S1 ). Taken together, the data suggest that the anti-SARS-CoV-2 activity of HCQ seems to be less potent compared to CQ, at least at certain MOIs.
Both CQ and HCQ are weak bases that are known to elevate the pH of acidic intracellular organelles, such as endosomes/lysosomes, essential for membrane fusion 5 . In addition, CQ could inhibit SARS-CoV entry through changing the glycosylation of ACE2 receptor and spike protein 6 . Time-of-addition experiment confirmed that HCQ effectively inhibited the entry step, as well as the post-entry stages of SARS-CoV-2, which was also found upon CQ treatment (Supplementary Fig. S2 ). To further explore the detailed mechanism of action of CQ and HCQ in inhibiting virus entry, co-localization of virions with early endosomes (EEs) or endolysosomes (ELs) was analyzed by immunofluorescence analysis (IFA) and confocal microscopy. Quantification analysis showed that, at 90 min p.i. in untreated cells, 16.2% of internalized virions (anti-NP, red) were observed in early endosome antigen 1 (EEA1)-positive EEs (green), while more virions (34.3%) were transported into the late endosomal-lysosomal protein LAMP1 + ELs (green) (n > 30 cells for each group). By contrast, in the presence of CQ or HCQ, significantly more virions (35.3% for CQ and 29.2% for HCQ; P < 0.001) were detected in the EEs, while only very few virions (2.4% for CQ and 0.03% for HCQ; P < 0.001) were found to be co-localized with LAMP1 + ELs (n > 30 cells) (Fig. 1b, c) . This suggested that both CQ and HCQ blocked the transport of SARS-CoV-2 from EEs to ELs, which appears to be a requirement to release the viral genome as in the case of SARS-CoV 7 .
Interestingly, we found that CQ and HCQ treatment caused noticeable changes in the number and size/morphology of EEs and ELs (Fig. 1c) . In the untreated cells, most EEs were much smaller than ELs (Fig. 1c) . In CQand HCQ-treated cells, abnormally enlarged EE vesicles were observed (Fig. 1c , arrows in the upper panels), many of which are even larger than ELs in the untreated cells. This is in agreement with previous report that treatment with CQ induced the formation of expanded cytoplasmic vesicles 8 . Within the EE vesicles, virions (red) were localized around the membrane (green) of the vesicle. CQ treatment did not cause obvious changes in the number and size of ELs; however, the regular vesicle structure seemed to be disrupted, at least partially. By contrast, in HCQ-treated cells, the size and number of ELs increased significantly (Fig. 1c , arrows in the lower panels).
Since acidification is crucial for endosome maturation and function, we surmise that endosome maturation might be blocked at intermediate stages of endocytosis, resulting in failure of further transport of virions to the ultimate releasing site. CQ was reported to elevate the pH (see figure on previous page) Fig. 1 Comparative antiviral efficacy and mechanism of action of CQ and HCQ against SARS-CoV-2 infection in vitro. a Cytotoxicity and antiviral activities of CQ and HCQ. The cytotoxicity of the two drugs in Vero E6 cells was determined by CCK-8 assays. Vero E6 cells were treated with different doses of either compound or with PBS in the controls for 1 h and then infected with SARS-CoV-2 at MOIs of 0.01, 0.02, 0.2, and 0.8. The virus yield in the cell supernatant was quantified by qRT-PCR at 48 h p.i. Y-axis represents the mean of percent inhibition normalized to the PBS group. The experiments were repeated twice. b, c Mechanism of CQ and HCQ in inhibiting virus entry. Vero E6 cells were treated with CQ or HCQ (50 μM) for 1 h, followed by virus binding (MOI = 10) at 4°C for 1 h. Then the unbound virions were removed, and the cells were further supplemented with fresh drug-containing medium at 37°C for 90 min before being fixed and stained with IFA using anti-NP antibody for virions (red) and antibodies against EEA1 for EEs (green) or LAMP1 for ELs (green). The nuclei (blue) were stained with Hoechst dye. The portion of virions that co-localized with EEs or ELs in each group (n > 30 cells) was quantified and is shown in b. Representative confocal microscopic images of viral particles (red), EEA1 + EEs (green), or LAMP1 + ELs (green) in each group are displayed in c. The enlarged images in the boxes indicate a single vesicle-containing virion. The arrows indicated the abnormally enlarged vesicles. Bars, 5 μm. Statistical analysis was performed using a one-way analysis of variance (ANOVA) with GraphPad Prism (F = 102.8, df = 5,182, ***P < 0.001).
of lysosome from about 4.5 to 6.5 at 100 μM 9 . To our knowledge, there is a lack of studies on the impact of HCQ on the morphology and pH values of endosomes/ lysosomes. Our observations suggested that the mode of actions of CQ and HCQ appear to be distinct in certain aspects.
It has been reported that oral absorption of CQ and HCQ in humans is very efficient. In animals, both drugs share similar tissue distribution patterns, with high concentrations in the liver, spleen, kidney, and lung reaching levels of 200-700 times higher than those in the plasma 10 . It was reported that safe dosage (6-6.5 mg/kg per day) of HCQ sulfate could generate serum levels of 1.4-1.5 μM in humans 11 . Therefore, with a safe dosage, HCQ concentration in the above tissues is likely to be achieved to inhibit SARS-CoV-2 infection.
Clinical investigation found that high concentration of cytokines were detected in the plasma of critically ill patients infected with SARS-CoV-2, suggesting that cytokine storm was associated with disease severity 12 . Other than its direct antiviral activity, HCQ is a safe and successful anti-inflammatory agent that has been used extensively in autoimmune diseases and can significantly decrease the production of cytokines and, in particular, pro-inflammatory factors. Therefore, in COVID-19 patients, HCQ may also contribute to attenuating the inflammatory response. In conclusion, our results show that HCQ can efficiently inhibit SARS-CoV-2 infection in vitro. In combination with its anti-inflammatory function, we predict that the drug has a good potential to combat the disease. This possibility awaits confirmation by clinical trials. We need to point out, although HCQ is less toxic than CQ, prolonged and overdose usage can still cause poisoning. And the relatively low SI of HCQ requires careful designing and conducting of clinical trials to achieve efficient and safe control of the SARS-CoV-2 infection. | 2,439 | What will be the drug of choice for treating COVID-19 between Chloroquine and Remdesivir? | {
"answer_start": [
1897
],
"text": [
" two potential drugs, CQ appears to be the drug of choice for large-scale use due to its availability, proven safety record, and a relatively low cost."
]
} | 651 |
1,414 | Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078228/
SHA: 1cf54d1c77b7f0494ab971429d26e0e199952d09
Authors: Liu, Jia; Cao, Ruiyuan; Xu, Mingyue; Wang, Xi; Zhang, Huanyu; Hu, Hengrui; Li, Yufeng; Hu, Zhihong; Zhong, Wu; Wang, Manli
Date: 2020-03-18
DOI: 10.1038/s41421-020-0156-0
License: cc-by
Abstract: nan
Text: Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro Jia Liu 1 , Ruiyuan Cao 2 , Mingyue Xu 1,3 , Xi Wang 1 , Huanyu Zhang 1,3 , Hengrui Hu 1,3 , Yufeng Li 1,3 , Zhihong Hu 1 , Wu Zhong 2 and Manli Wang 1 Dear Editor, The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/2019-nCoV) poses a serious threat to global public health and local economies. As of March 3, 2020, over 80,000 cases have been confirmed in China, including 2946 deaths as well as over 10,566 confirmed cases in 72 other countries. Such huge numbers of infected and dead people call for an urgent demand of effective, available, and affordable drugs to control and diminish the epidemic.
We have recently reported that two drugs, remdesivir (GS-5734) and chloroquine (CQ) phosphate, efficiently inhibited SARS-CoV-2 infection in vitro 1 . Remdesivir is a nucleoside analog prodrug developed by Gilead Sciences (USA). A recent case report showed that treatment with remdesivir improved the clinical condition of the first patient infected by SARS-CoV-2 in the United States 2 , and a phase III clinical trial of remdesivir against SARS-CoV-2 was launched in Wuhan on February 4, 2020. However, as an experimental drug, remdesivir is not expected to be largely available for treating a very large number of patients in a timely manner. Therefore, of the two potential drugs, CQ appears to be the drug of choice for large-scale use due to its availability, proven safety record, and a relatively low cost. In light of the preliminary clinical data, CQ has been added to the list of trial drugs in the Guidelines for the Diagnosis and Treatment of COVID-19 (sixth edition) published by National Health Commission of the People's Republic of China. CQ (N4-(7-Chloro-4-quinolinyl)-N1,N1-diethyl-1,4pentanediamine) has long been used to treat malaria and amebiasis. However, Plasmodium falciparum developed widespread resistance to it, and with the development of new antimalarials, it has become a choice for the prophylaxis of malaria. In addition, an overdose of CQ can cause acute poisoning and death 3 . In the past years, due to infrequent utilization of CQ in clinical practice, its production and market supply was greatly reduced, at least in China. Hydroxychloroquine (HCQ) sulfate, a derivative of CQ, was first synthesized in 1946 by introducing a hydroxyl group into CQ and was demonstrated to be much less (~40%) toxic than CQ in animals 4 . More importantly, HCQ is still widely available to treat autoimmune diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Since CQ and HCQ share similar chemical structures and mechanisms of acting as a weak base and immunomodulator, it is easy to conjure up the idea that HCQ may be a potent candidate to treat infection by SARS-CoV-2. Actually, as of February 23, 2020, seven clinical trial registries were found in Chinese Clinical Trial Registry (http://www.chictr.org.cn) for using HCQ to treat COVID-19. Whether HCQ is as efficacious as CQ in treating SARS-CoV-2 infection still lacks the experimental evidence.
To this end, we evaluated the antiviral effect of HCQ against SARS-CoV-2 infection in comparison to CQ in vitro. First, the cytotoxicity of HCQ and CQ in African green monkey kidney VeroE6 cells (ATCC-1586) was measured by standard CCK8 assay, and the result showed © The Author(s) 2020
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. (Fig. 1a) . To better compare the antiviral activity of CQ versus HCQ, the dose-response curves of the two compounds against SARS-CoV-2 were determined at four different multiplicities of infection (MOIs) by quantification of viral RNA copy numbers in the cell supernatant at 48 h post infection (p.i.). The data summarized in Fig. 1a and Supplementary Table S1 show that, at all MOIs (0.01, 0.02, 0.2, and 0.8), the 50% maximal effective concentration (EC 50 ) for CQ (2.71, 3.81, 7.14, and 7.36 μM) was lower than that of HCQ (4.51, 4.06, 17.31, and 12.96 μM). The differences in EC 50 values were statistically significant at an MOI of 0.01 (P < 0.05) and MOI of 0.2 (P < 0.001) (Supplementary Table S1 ). It is worth noting that the EC 50 values of CQ seemed to be a little higher than that in our previous report (1.13 μM at an MOI of 0.05) 1 , which is likely due to the adaptation of the virus in cell culture that significantly increased viral infectivity upon continuous passaging. Consequently, the selectivity index (SI = CC 50 /EC 50 ) of CQ (100.81, 71.71, 38.26, and 37.12) was higher than that of HCQ (55.32, 61.45, 14.41, 19.25) at MOIs of 0.01, 0.02, 0.2, and 0.8, respectively. These results were corroborated by immunofluorescence microscopy as evidenced by different expression levels of virus nucleoprotein (NP) at the indicated drug concentrations at 48 h p.i. (Supplementary Fig. S1 ). Taken together, the data suggest that the anti-SARS-CoV-2 activity of HCQ seems to be less potent compared to CQ, at least at certain MOIs.
Both CQ and HCQ are weak bases that are known to elevate the pH of acidic intracellular organelles, such as endosomes/lysosomes, essential for membrane fusion 5 . In addition, CQ could inhibit SARS-CoV entry through changing the glycosylation of ACE2 receptor and spike protein 6 . Time-of-addition experiment confirmed that HCQ effectively inhibited the entry step, as well as the post-entry stages of SARS-CoV-2, which was also found upon CQ treatment (Supplementary Fig. S2 ). To further explore the detailed mechanism of action of CQ and HCQ in inhibiting virus entry, co-localization of virions with early endosomes (EEs) or endolysosomes (ELs) was analyzed by immunofluorescence analysis (IFA) and confocal microscopy. Quantification analysis showed that, at 90 min p.i. in untreated cells, 16.2% of internalized virions (anti-NP, red) were observed in early endosome antigen 1 (EEA1)-positive EEs (green), while more virions (34.3%) were transported into the late endosomal-lysosomal protein LAMP1 + ELs (green) (n > 30 cells for each group). By contrast, in the presence of CQ or HCQ, significantly more virions (35.3% for CQ and 29.2% for HCQ; P < 0.001) were detected in the EEs, while only very few virions (2.4% for CQ and 0.03% for HCQ; P < 0.001) were found to be co-localized with LAMP1 + ELs (n > 30 cells) (Fig. 1b, c) . This suggested that both CQ and HCQ blocked the transport of SARS-CoV-2 from EEs to ELs, which appears to be a requirement to release the viral genome as in the case of SARS-CoV 7 .
Interestingly, we found that CQ and HCQ treatment caused noticeable changes in the number and size/morphology of EEs and ELs (Fig. 1c) . In the untreated cells, most EEs were much smaller than ELs (Fig. 1c) . In CQand HCQ-treated cells, abnormally enlarged EE vesicles were observed (Fig. 1c , arrows in the upper panels), many of which are even larger than ELs in the untreated cells. This is in agreement with previous report that treatment with CQ induced the formation of expanded cytoplasmic vesicles 8 . Within the EE vesicles, virions (red) were localized around the membrane (green) of the vesicle. CQ treatment did not cause obvious changes in the number and size of ELs; however, the regular vesicle structure seemed to be disrupted, at least partially. By contrast, in HCQ-treated cells, the size and number of ELs increased significantly (Fig. 1c , arrows in the lower panels).
Since acidification is crucial for endosome maturation and function, we surmise that endosome maturation might be blocked at intermediate stages of endocytosis, resulting in failure of further transport of virions to the ultimate releasing site. CQ was reported to elevate the pH (see figure on previous page) Fig. 1 Comparative antiviral efficacy and mechanism of action of CQ and HCQ against SARS-CoV-2 infection in vitro. a Cytotoxicity and antiviral activities of CQ and HCQ. The cytotoxicity of the two drugs in Vero E6 cells was determined by CCK-8 assays. Vero E6 cells were treated with different doses of either compound or with PBS in the controls for 1 h and then infected with SARS-CoV-2 at MOIs of 0.01, 0.02, 0.2, and 0.8. The virus yield in the cell supernatant was quantified by qRT-PCR at 48 h p.i. Y-axis represents the mean of percent inhibition normalized to the PBS group. The experiments were repeated twice. b, c Mechanism of CQ and HCQ in inhibiting virus entry. Vero E6 cells were treated with CQ or HCQ (50 μM) for 1 h, followed by virus binding (MOI = 10) at 4°C for 1 h. Then the unbound virions were removed, and the cells were further supplemented with fresh drug-containing medium at 37°C for 90 min before being fixed and stained with IFA using anti-NP antibody for virions (red) and antibodies against EEA1 for EEs (green) or LAMP1 for ELs (green). The nuclei (blue) were stained with Hoechst dye. The portion of virions that co-localized with EEs or ELs in each group (n > 30 cells) was quantified and is shown in b. Representative confocal microscopic images of viral particles (red), EEA1 + EEs (green), or LAMP1 + ELs (green) in each group are displayed in c. The enlarged images in the boxes indicate a single vesicle-containing virion. The arrows indicated the abnormally enlarged vesicles. Bars, 5 μm. Statistical analysis was performed using a one-way analysis of variance (ANOVA) with GraphPad Prism (F = 102.8, df = 5,182, ***P < 0.001).
of lysosome from about 4.5 to 6.5 at 100 μM 9 . To our knowledge, there is a lack of studies on the impact of HCQ on the morphology and pH values of endosomes/ lysosomes. Our observations suggested that the mode of actions of CQ and HCQ appear to be distinct in certain aspects.
It has been reported that oral absorption of CQ and HCQ in humans is very efficient. In animals, both drugs share similar tissue distribution patterns, with high concentrations in the liver, spleen, kidney, and lung reaching levels of 200-700 times higher than those in the plasma 10 . It was reported that safe dosage (6-6.5 mg/kg per day) of HCQ sulfate could generate serum levels of 1.4-1.5 μM in humans 11 . Therefore, with a safe dosage, HCQ concentration in the above tissues is likely to be achieved to inhibit SARS-CoV-2 infection.
Clinical investigation found that high concentration of cytokines were detected in the plasma of critically ill patients infected with SARS-CoV-2, suggesting that cytokine storm was associated with disease severity 12 . Other than its direct antiviral activity, HCQ is a safe and successful anti-inflammatory agent that has been used extensively in autoimmune diseases and can significantly decrease the production of cytokines and, in particular, pro-inflammatory factors. Therefore, in COVID-19 patients, HCQ may also contribute to attenuating the inflammatory response. In conclusion, our results show that HCQ can efficiently inhibit SARS-CoV-2 infection in vitro. In combination with its anti-inflammatory function, we predict that the drug has a good potential to combat the disease. This possibility awaits confirmation by clinical trials. We need to point out, although HCQ is less toxic than CQ, prolonged and overdose usage can still cause poisoning. And the relatively low SI of HCQ requires careful designing and conducting of clinical trials to achieve efficient and safe control of the SARS-CoV-2 infection. | 2,439 | Mechanism of action of Chloroquine(CQ) and Hydroxychloroquine(HCQ) against COVID-19? | {
"answer_start": [
6327
],
"text": [
"CQ and HCQ are weak bases that are known to elevate the pH of acidic intracellular organelles"
]
} | 658 |
1,415 | Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078228/
SHA: 1cf54d1c77b7f0494ab971429d26e0e199952d09
Authors: Liu, Jia; Cao, Ruiyuan; Xu, Mingyue; Wang, Xi; Zhang, Huanyu; Hu, Hengrui; Li, Yufeng; Hu, Zhihong; Zhong, Wu; Wang, Manli
Date: 2020-03-18
DOI: 10.1038/s41421-020-0156-0
License: cc-by
Abstract: nan
Text: Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro Jia Liu 1 , Ruiyuan Cao 2 , Mingyue Xu 1,3 , Xi Wang 1 , Huanyu Zhang 1,3 , Hengrui Hu 1,3 , Yufeng Li 1,3 , Zhihong Hu 1 , Wu Zhong 2 and Manli Wang 1 Dear Editor, The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/2019-nCoV) poses a serious threat to global public health and local economies. As of March 3, 2020, over 80,000 cases have been confirmed in China, including 2946 deaths as well as over 10,566 confirmed cases in 72 other countries. Such huge numbers of infected and dead people call for an urgent demand of effective, available, and affordable drugs to control and diminish the epidemic.
We have recently reported that two drugs, remdesivir (GS-5734) and chloroquine (CQ) phosphate, efficiently inhibited SARS-CoV-2 infection in vitro 1 . Remdesivir is a nucleoside analog prodrug developed by Gilead Sciences (USA). A recent case report showed that treatment with remdesivir improved the clinical condition of the first patient infected by SARS-CoV-2 in the United States 2 , and a phase III clinical trial of remdesivir against SARS-CoV-2 was launched in Wuhan on February 4, 2020. However, as an experimental drug, remdesivir is not expected to be largely available for treating a very large number of patients in a timely manner. Therefore, of the two potential drugs, CQ appears to be the drug of choice for large-scale use due to its availability, proven safety record, and a relatively low cost. In light of the preliminary clinical data, CQ has been added to the list of trial drugs in the Guidelines for the Diagnosis and Treatment of COVID-19 (sixth edition) published by National Health Commission of the People's Republic of China. CQ (N4-(7-Chloro-4-quinolinyl)-N1,N1-diethyl-1,4pentanediamine) has long been used to treat malaria and amebiasis. However, Plasmodium falciparum developed widespread resistance to it, and with the development of new antimalarials, it has become a choice for the prophylaxis of malaria. In addition, an overdose of CQ can cause acute poisoning and death 3 . In the past years, due to infrequent utilization of CQ in clinical practice, its production and market supply was greatly reduced, at least in China. Hydroxychloroquine (HCQ) sulfate, a derivative of CQ, was first synthesized in 1946 by introducing a hydroxyl group into CQ and was demonstrated to be much less (~40%) toxic than CQ in animals 4 . More importantly, HCQ is still widely available to treat autoimmune diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Since CQ and HCQ share similar chemical structures and mechanisms of acting as a weak base and immunomodulator, it is easy to conjure up the idea that HCQ may be a potent candidate to treat infection by SARS-CoV-2. Actually, as of February 23, 2020, seven clinical trial registries were found in Chinese Clinical Trial Registry (http://www.chictr.org.cn) for using HCQ to treat COVID-19. Whether HCQ is as efficacious as CQ in treating SARS-CoV-2 infection still lacks the experimental evidence.
To this end, we evaluated the antiviral effect of HCQ against SARS-CoV-2 infection in comparison to CQ in vitro. First, the cytotoxicity of HCQ and CQ in African green monkey kidney VeroE6 cells (ATCC-1586) was measured by standard CCK8 assay, and the result showed © The Author(s) 2020
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. (Fig. 1a) . To better compare the antiviral activity of CQ versus HCQ, the dose-response curves of the two compounds against SARS-CoV-2 were determined at four different multiplicities of infection (MOIs) by quantification of viral RNA copy numbers in the cell supernatant at 48 h post infection (p.i.). The data summarized in Fig. 1a and Supplementary Table S1 show that, at all MOIs (0.01, 0.02, 0.2, and 0.8), the 50% maximal effective concentration (EC 50 ) for CQ (2.71, 3.81, 7.14, and 7.36 μM) was lower than that of HCQ (4.51, 4.06, 17.31, and 12.96 μM). The differences in EC 50 values were statistically significant at an MOI of 0.01 (P < 0.05) and MOI of 0.2 (P < 0.001) (Supplementary Table S1 ). It is worth noting that the EC 50 values of CQ seemed to be a little higher than that in our previous report (1.13 μM at an MOI of 0.05) 1 , which is likely due to the adaptation of the virus in cell culture that significantly increased viral infectivity upon continuous passaging. Consequently, the selectivity index (SI = CC 50 /EC 50 ) of CQ (100.81, 71.71, 38.26, and 37.12) was higher than that of HCQ (55.32, 61.45, 14.41, 19.25) at MOIs of 0.01, 0.02, 0.2, and 0.8, respectively. These results were corroborated by immunofluorescence microscopy as evidenced by different expression levels of virus nucleoprotein (NP) at the indicated drug concentrations at 48 h p.i. (Supplementary Fig. S1 ). Taken together, the data suggest that the anti-SARS-CoV-2 activity of HCQ seems to be less potent compared to CQ, at least at certain MOIs.
Both CQ and HCQ are weak bases that are known to elevate the pH of acidic intracellular organelles, such as endosomes/lysosomes, essential for membrane fusion 5 . In addition, CQ could inhibit SARS-CoV entry through changing the glycosylation of ACE2 receptor and spike protein 6 . Time-of-addition experiment confirmed that HCQ effectively inhibited the entry step, as well as the post-entry stages of SARS-CoV-2, which was also found upon CQ treatment (Supplementary Fig. S2 ). To further explore the detailed mechanism of action of CQ and HCQ in inhibiting virus entry, co-localization of virions with early endosomes (EEs) or endolysosomes (ELs) was analyzed by immunofluorescence analysis (IFA) and confocal microscopy. Quantification analysis showed that, at 90 min p.i. in untreated cells, 16.2% of internalized virions (anti-NP, red) were observed in early endosome antigen 1 (EEA1)-positive EEs (green), while more virions (34.3%) were transported into the late endosomal-lysosomal protein LAMP1 + ELs (green) (n > 30 cells for each group). By contrast, in the presence of CQ or HCQ, significantly more virions (35.3% for CQ and 29.2% for HCQ; P < 0.001) were detected in the EEs, while only very few virions (2.4% for CQ and 0.03% for HCQ; P < 0.001) were found to be co-localized with LAMP1 + ELs (n > 30 cells) (Fig. 1b, c) . This suggested that both CQ and HCQ blocked the transport of SARS-CoV-2 from EEs to ELs, which appears to be a requirement to release the viral genome as in the case of SARS-CoV 7 .
Interestingly, we found that CQ and HCQ treatment caused noticeable changes in the number and size/morphology of EEs and ELs (Fig. 1c) . In the untreated cells, most EEs were much smaller than ELs (Fig. 1c) . In CQand HCQ-treated cells, abnormally enlarged EE vesicles were observed (Fig. 1c , arrows in the upper panels), many of which are even larger than ELs in the untreated cells. This is in agreement with previous report that treatment with CQ induced the formation of expanded cytoplasmic vesicles 8 . Within the EE vesicles, virions (red) were localized around the membrane (green) of the vesicle. CQ treatment did not cause obvious changes in the number and size of ELs; however, the regular vesicle structure seemed to be disrupted, at least partially. By contrast, in HCQ-treated cells, the size and number of ELs increased significantly (Fig. 1c , arrows in the lower panels).
Since acidification is crucial for endosome maturation and function, we surmise that endosome maturation might be blocked at intermediate stages of endocytosis, resulting in failure of further transport of virions to the ultimate releasing site. CQ was reported to elevate the pH (see figure on previous page) Fig. 1 Comparative antiviral efficacy and mechanism of action of CQ and HCQ against SARS-CoV-2 infection in vitro. a Cytotoxicity and antiviral activities of CQ and HCQ. The cytotoxicity of the two drugs in Vero E6 cells was determined by CCK-8 assays. Vero E6 cells were treated with different doses of either compound or with PBS in the controls for 1 h and then infected with SARS-CoV-2 at MOIs of 0.01, 0.02, 0.2, and 0.8. The virus yield in the cell supernatant was quantified by qRT-PCR at 48 h p.i. Y-axis represents the mean of percent inhibition normalized to the PBS group. The experiments were repeated twice. b, c Mechanism of CQ and HCQ in inhibiting virus entry. Vero E6 cells were treated with CQ or HCQ (50 μM) for 1 h, followed by virus binding (MOI = 10) at 4°C for 1 h. Then the unbound virions were removed, and the cells were further supplemented with fresh drug-containing medium at 37°C for 90 min before being fixed and stained with IFA using anti-NP antibody for virions (red) and antibodies against EEA1 for EEs (green) or LAMP1 for ELs (green). The nuclei (blue) were stained with Hoechst dye. The portion of virions that co-localized with EEs or ELs in each group (n > 30 cells) was quantified and is shown in b. Representative confocal microscopic images of viral particles (red), EEA1 + EEs (green), or LAMP1 + ELs (green) in each group are displayed in c. The enlarged images in the boxes indicate a single vesicle-containing virion. The arrows indicated the abnormally enlarged vesicles. Bars, 5 μm. Statistical analysis was performed using a one-way analysis of variance (ANOVA) with GraphPad Prism (F = 102.8, df = 5,182, ***P < 0.001).
of lysosome from about 4.5 to 6.5 at 100 μM 9 . To our knowledge, there is a lack of studies on the impact of HCQ on the morphology and pH values of endosomes/ lysosomes. Our observations suggested that the mode of actions of CQ and HCQ appear to be distinct in certain aspects.
It has been reported that oral absorption of CQ and HCQ in humans is very efficient. In animals, both drugs share similar tissue distribution patterns, with high concentrations in the liver, spleen, kidney, and lung reaching levels of 200-700 times higher than those in the plasma 10 . It was reported that safe dosage (6-6.5 mg/kg per day) of HCQ sulfate could generate serum levels of 1.4-1.5 μM in humans 11 . Therefore, with a safe dosage, HCQ concentration in the above tissues is likely to be achieved to inhibit SARS-CoV-2 infection.
Clinical investigation found that high concentration of cytokines were detected in the plasma of critically ill patients infected with SARS-CoV-2, suggesting that cytokine storm was associated with disease severity 12 . Other than its direct antiviral activity, HCQ is a safe and successful anti-inflammatory agent that has been used extensively in autoimmune diseases and can significantly decrease the production of cytokines and, in particular, pro-inflammatory factors. Therefore, in COVID-19 patients, HCQ may also contribute to attenuating the inflammatory response. In conclusion, our results show that HCQ can efficiently inhibit SARS-CoV-2 infection in vitro. In combination with its anti-inflammatory function, we predict that the drug has a good potential to combat the disease. This possibility awaits confirmation by clinical trials. We need to point out, although HCQ is less toxic than CQ, prolonged and overdose usage can still cause poisoning. And the relatively low SI of HCQ requires careful designing and conducting of clinical trials to achieve efficient and safe control of the SARS-CoV-2 infection. | 2,439 | What is the effect of Chloroquine(CQ) and Hydroxychloroquine(HCQ) on endosomal maturation and endocytosis in COVID-19 treatment? | {
"answer_start": [
8734
],
"text": [
"Since acidification is crucial for endosome maturation and function, we surmise that endosome maturation might be blocked at intermediate stages of endocytosis,"
]
} | 661 |
1,416 | Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078228/
SHA: 1cf54d1c77b7f0494ab971429d26e0e199952d09
Authors: Liu, Jia; Cao, Ruiyuan; Xu, Mingyue; Wang, Xi; Zhang, Huanyu; Hu, Hengrui; Li, Yufeng; Hu, Zhihong; Zhong, Wu; Wang, Manli
Date: 2020-03-18
DOI: 10.1038/s41421-020-0156-0
License: cc-by
Abstract: nan
Text: Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro Jia Liu 1 , Ruiyuan Cao 2 , Mingyue Xu 1,3 , Xi Wang 1 , Huanyu Zhang 1,3 , Hengrui Hu 1,3 , Yufeng Li 1,3 , Zhihong Hu 1 , Wu Zhong 2 and Manli Wang 1 Dear Editor, The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/2019-nCoV) poses a serious threat to global public health and local economies. As of March 3, 2020, over 80,000 cases have been confirmed in China, including 2946 deaths as well as over 10,566 confirmed cases in 72 other countries. Such huge numbers of infected and dead people call for an urgent demand of effective, available, and affordable drugs to control and diminish the epidemic.
We have recently reported that two drugs, remdesivir (GS-5734) and chloroquine (CQ) phosphate, efficiently inhibited SARS-CoV-2 infection in vitro 1 . Remdesivir is a nucleoside analog prodrug developed by Gilead Sciences (USA). A recent case report showed that treatment with remdesivir improved the clinical condition of the first patient infected by SARS-CoV-2 in the United States 2 , and a phase III clinical trial of remdesivir against SARS-CoV-2 was launched in Wuhan on February 4, 2020. However, as an experimental drug, remdesivir is not expected to be largely available for treating a very large number of patients in a timely manner. Therefore, of the two potential drugs, CQ appears to be the drug of choice for large-scale use due to its availability, proven safety record, and a relatively low cost. In light of the preliminary clinical data, CQ has been added to the list of trial drugs in the Guidelines for the Diagnosis and Treatment of COVID-19 (sixth edition) published by National Health Commission of the People's Republic of China. CQ (N4-(7-Chloro-4-quinolinyl)-N1,N1-diethyl-1,4pentanediamine) has long been used to treat malaria and amebiasis. However, Plasmodium falciparum developed widespread resistance to it, and with the development of new antimalarials, it has become a choice for the prophylaxis of malaria. In addition, an overdose of CQ can cause acute poisoning and death 3 . In the past years, due to infrequent utilization of CQ in clinical practice, its production and market supply was greatly reduced, at least in China. Hydroxychloroquine (HCQ) sulfate, a derivative of CQ, was first synthesized in 1946 by introducing a hydroxyl group into CQ and was demonstrated to be much less (~40%) toxic than CQ in animals 4 . More importantly, HCQ is still widely available to treat autoimmune diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Since CQ and HCQ share similar chemical structures and mechanisms of acting as a weak base and immunomodulator, it is easy to conjure up the idea that HCQ may be a potent candidate to treat infection by SARS-CoV-2. Actually, as of February 23, 2020, seven clinical trial registries were found in Chinese Clinical Trial Registry (http://www.chictr.org.cn) for using HCQ to treat COVID-19. Whether HCQ is as efficacious as CQ in treating SARS-CoV-2 infection still lacks the experimental evidence.
To this end, we evaluated the antiviral effect of HCQ against SARS-CoV-2 infection in comparison to CQ in vitro. First, the cytotoxicity of HCQ and CQ in African green monkey kidney VeroE6 cells (ATCC-1586) was measured by standard CCK8 assay, and the result showed © The Author(s) 2020
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. (Fig. 1a) . To better compare the antiviral activity of CQ versus HCQ, the dose-response curves of the two compounds against SARS-CoV-2 were determined at four different multiplicities of infection (MOIs) by quantification of viral RNA copy numbers in the cell supernatant at 48 h post infection (p.i.). The data summarized in Fig. 1a and Supplementary Table S1 show that, at all MOIs (0.01, 0.02, 0.2, and 0.8), the 50% maximal effective concentration (EC 50 ) for CQ (2.71, 3.81, 7.14, and 7.36 μM) was lower than that of HCQ (4.51, 4.06, 17.31, and 12.96 μM). The differences in EC 50 values were statistically significant at an MOI of 0.01 (P < 0.05) and MOI of 0.2 (P < 0.001) (Supplementary Table S1 ). It is worth noting that the EC 50 values of CQ seemed to be a little higher than that in our previous report (1.13 μM at an MOI of 0.05) 1 , which is likely due to the adaptation of the virus in cell culture that significantly increased viral infectivity upon continuous passaging. Consequently, the selectivity index (SI = CC 50 /EC 50 ) of CQ (100.81, 71.71, 38.26, and 37.12) was higher than that of HCQ (55.32, 61.45, 14.41, 19.25) at MOIs of 0.01, 0.02, 0.2, and 0.8, respectively. These results were corroborated by immunofluorescence microscopy as evidenced by different expression levels of virus nucleoprotein (NP) at the indicated drug concentrations at 48 h p.i. (Supplementary Fig. S1 ). Taken together, the data suggest that the anti-SARS-CoV-2 activity of HCQ seems to be less potent compared to CQ, at least at certain MOIs.
Both CQ and HCQ are weak bases that are known to elevate the pH of acidic intracellular organelles, such as endosomes/lysosomes, essential for membrane fusion 5 . In addition, CQ could inhibit SARS-CoV entry through changing the glycosylation of ACE2 receptor and spike protein 6 . Time-of-addition experiment confirmed that HCQ effectively inhibited the entry step, as well as the post-entry stages of SARS-CoV-2, which was also found upon CQ treatment (Supplementary Fig. S2 ). To further explore the detailed mechanism of action of CQ and HCQ in inhibiting virus entry, co-localization of virions with early endosomes (EEs) or endolysosomes (ELs) was analyzed by immunofluorescence analysis (IFA) and confocal microscopy. Quantification analysis showed that, at 90 min p.i. in untreated cells, 16.2% of internalized virions (anti-NP, red) were observed in early endosome antigen 1 (EEA1)-positive EEs (green), while more virions (34.3%) were transported into the late endosomal-lysosomal protein LAMP1 + ELs (green) (n > 30 cells for each group). By contrast, in the presence of CQ or HCQ, significantly more virions (35.3% for CQ and 29.2% for HCQ; P < 0.001) were detected in the EEs, while only very few virions (2.4% for CQ and 0.03% for HCQ; P < 0.001) were found to be co-localized with LAMP1 + ELs (n > 30 cells) (Fig. 1b, c) . This suggested that both CQ and HCQ blocked the transport of SARS-CoV-2 from EEs to ELs, which appears to be a requirement to release the viral genome as in the case of SARS-CoV 7 .
Interestingly, we found that CQ and HCQ treatment caused noticeable changes in the number and size/morphology of EEs and ELs (Fig. 1c) . In the untreated cells, most EEs were much smaller than ELs (Fig. 1c) . In CQand HCQ-treated cells, abnormally enlarged EE vesicles were observed (Fig. 1c , arrows in the upper panels), many of which are even larger than ELs in the untreated cells. This is in agreement with previous report that treatment with CQ induced the formation of expanded cytoplasmic vesicles 8 . Within the EE vesicles, virions (red) were localized around the membrane (green) of the vesicle. CQ treatment did not cause obvious changes in the number and size of ELs; however, the regular vesicle structure seemed to be disrupted, at least partially. By contrast, in HCQ-treated cells, the size and number of ELs increased significantly (Fig. 1c , arrows in the lower panels).
Since acidification is crucial for endosome maturation and function, we surmise that endosome maturation might be blocked at intermediate stages of endocytosis, resulting in failure of further transport of virions to the ultimate releasing site. CQ was reported to elevate the pH (see figure on previous page) Fig. 1 Comparative antiviral efficacy and mechanism of action of CQ and HCQ against SARS-CoV-2 infection in vitro. a Cytotoxicity and antiviral activities of CQ and HCQ. The cytotoxicity of the two drugs in Vero E6 cells was determined by CCK-8 assays. Vero E6 cells were treated with different doses of either compound or with PBS in the controls for 1 h and then infected with SARS-CoV-2 at MOIs of 0.01, 0.02, 0.2, and 0.8. The virus yield in the cell supernatant was quantified by qRT-PCR at 48 h p.i. Y-axis represents the mean of percent inhibition normalized to the PBS group. The experiments were repeated twice. b, c Mechanism of CQ and HCQ in inhibiting virus entry. Vero E6 cells were treated with CQ or HCQ (50 μM) for 1 h, followed by virus binding (MOI = 10) at 4°C for 1 h. Then the unbound virions were removed, and the cells were further supplemented with fresh drug-containing medium at 37°C for 90 min before being fixed and stained with IFA using anti-NP antibody for virions (red) and antibodies against EEA1 for EEs (green) or LAMP1 for ELs (green). The nuclei (blue) were stained with Hoechst dye. The portion of virions that co-localized with EEs or ELs in each group (n > 30 cells) was quantified and is shown in b. Representative confocal microscopic images of viral particles (red), EEA1 + EEs (green), or LAMP1 + ELs (green) in each group are displayed in c. The enlarged images in the boxes indicate a single vesicle-containing virion. The arrows indicated the abnormally enlarged vesicles. Bars, 5 μm. Statistical analysis was performed using a one-way analysis of variance (ANOVA) with GraphPad Prism (F = 102.8, df = 5,182, ***P < 0.001).
of lysosome from about 4.5 to 6.5 at 100 μM 9 . To our knowledge, there is a lack of studies on the impact of HCQ on the morphology and pH values of endosomes/ lysosomes. Our observations suggested that the mode of actions of CQ and HCQ appear to be distinct in certain aspects.
It has been reported that oral absorption of CQ and HCQ in humans is very efficient. In animals, both drugs share similar tissue distribution patterns, with high concentrations in the liver, spleen, kidney, and lung reaching levels of 200-700 times higher than those in the plasma 10 . It was reported that safe dosage (6-6.5 mg/kg per day) of HCQ sulfate could generate serum levels of 1.4-1.5 μM in humans 11 . Therefore, with a safe dosage, HCQ concentration in the above tissues is likely to be achieved to inhibit SARS-CoV-2 infection.
Clinical investigation found that high concentration of cytokines were detected in the plasma of critically ill patients infected with SARS-CoV-2, suggesting that cytokine storm was associated with disease severity 12 . Other than its direct antiviral activity, HCQ is a safe and successful anti-inflammatory agent that has been used extensively in autoimmune diseases and can significantly decrease the production of cytokines and, in particular, pro-inflammatory factors. Therefore, in COVID-19 patients, HCQ may also contribute to attenuating the inflammatory response. In conclusion, our results show that HCQ can efficiently inhibit SARS-CoV-2 infection in vitro. In combination with its anti-inflammatory function, we predict that the drug has a good potential to combat the disease. This possibility awaits confirmation by clinical trials. We need to point out, although HCQ is less toxic than CQ, prolonged and overdose usage can still cause poisoning. And the relatively low SI of HCQ requires careful designing and conducting of clinical trials to achieve efficient and safe control of the SARS-CoV-2 infection. | 2,439 | Evidence of Hydroxychloroquine(HCQ) being anti inflammatory in SARS-CoV-2 critically ill patients with elevated plasma cytokines? | {
"answer_start": [
11799
],
"text": [
" HCQ is a safe and successful anti-inflammatory agent"
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