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COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic
BACKGROUND: Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, cont...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130991/ https://www.ncbi.nlm.nih.gov/pubmed/35614394 http://dx.doi.org/10.1186/s12879-022-07469-1 |
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author | Imai, Natsuko Gaythorpe, Katy A. M. Bhatia, Sangeeta Mangal, Tara D. Cuomo-Dannenburg, Gina Unwin, H. Juliette T. Jauneikaite, Elita Ferguson, Neil M. |
author_facet | Imai, Natsuko Gaythorpe, Katy A. M. Bhatia, Sangeeta Mangal, Tara D. Cuomo-Dannenburg, Gina Unwin, H. Juliette T. Jauneikaite, Elita Ferguson, Neil M. |
author_sort | Imai, Natsuko |
collection | PubMed |
description | BACKGROUND: Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. METHODS: We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, R(t), correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs. RESULTS: The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ± 2 days). Early transmission was driven primarily by returning travellers with R(t) peaking at 2.4 (95% CrI: 1.6, 3.3) nationally. In the final week of the trusted period (16–23 March 2020), R(t) accounting for importations diverged from overall R(t) at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6), respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients < 20 years old developing pneumonia or severe respiratory symptoms. CONCLUSIONS: Information collected in the early phases of an outbreak are important in characterising any novel pathogen. The availability of timely and detailed data and appropriate analyses is critical to estimate and understand a pathogen’s transmissibility, high-risk settings for transmission, and key symptoms. These insights can help to inform urgent response strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07469-1. |
format | Online Article Text |
id | pubmed-9130991 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91309912022-05-25 COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic Imai, Natsuko Gaythorpe, Katy A. M. Bhatia, Sangeeta Mangal, Tara D. Cuomo-Dannenburg, Gina Unwin, H. Juliette T. Jauneikaite, Elita Ferguson, Neil M. BMC Infect Dis Research BACKGROUND: Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. METHODS: We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, R(t), correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs. RESULTS: The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ± 2 days). Early transmission was driven primarily by returning travellers with R(t) peaking at 2.4 (95% CrI: 1.6, 3.3) nationally. In the final week of the trusted period (16–23 March 2020), R(t) accounting for importations diverged from overall R(t) at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6), respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients < 20 years old developing pneumonia or severe respiratory symptoms. CONCLUSIONS: Information collected in the early phases of an outbreak are important in characterising any novel pathogen. The availability of timely and detailed data and appropriate analyses is critical to estimate and understand a pathogen’s transmissibility, high-risk settings for transmission, and key symptoms. These insights can help to inform urgent response strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07469-1. BioMed Central 2022-05-25 /pmc/articles/PMC9130991/ /pubmed/35614394 http://dx.doi.org/10.1186/s12879-022-07469-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Imai, Natsuko Gaythorpe, Katy A. M. Bhatia, Sangeeta Mangal, Tara D. Cuomo-Dannenburg, Gina Unwin, H. Juliette T. Jauneikaite, Elita Ferguson, Neil M. COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic |
title | COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic |
title_full | COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic |
title_fullStr | COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic |
title_full_unstemmed | COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic |
title_short | COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic |
title_sort | covid-19 in japan, january–march 2020: insights from the first three months of the epidemic |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130991/ https://www.ncbi.nlm.nih.gov/pubmed/35614394 http://dx.doi.org/10.1186/s12879-022-07469-1 |
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