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Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020
BACKGROUND: Estimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies. AIM: We estimate the generation interval, serial interval, proportion of pre-symptomatic transmission and effective reprod...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Centre for Disease Prevention and Control (ECDC)
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201952/ https://www.ncbi.nlm.nih.gov/pubmed/32372755 http://dx.doi.org/10.2807/1560-7917.ES.2020.25.17.2000257 |
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author | Ganyani, Tapiwa Kremer, Cécile Chen, Dongxuan Torneri, Andrea Faes, Christel Wallinga, Jacco Hens, Niel |
author_facet | Ganyani, Tapiwa Kremer, Cécile Chen, Dongxuan Torneri, Andrea Faes, Christel Wallinga, Jacco Hens, Niel |
author_sort | Ganyani, Tapiwa |
collection | PubMed |
description | BACKGROUND: Estimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies. AIM: We estimate the generation interval, serial interval, proportion of pre-symptomatic transmission and effective reproduction number of COVID-19. We illustrate that reproduction numbers calculated based on serial interval estimates can be biased. METHODS: We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates, we obtained the serial interval, proportions of pre-symptomatic transmission and reproduction numbers. RESULTS: The mean generation interval was 5.20 days (95% credible interval (CrI): 3.78–6.78) for Singapore and 3.95 days (95% CrI: 3.01–4.91) for Tianjin. The proportion of pre-symptomatic transmission was 48% (95% CrI: 32–67) for Singapore and 62% (95% CrI: 50–76) for Tianjin. Reproduction number estimates based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Sensitivity analyses showed that estimating these quantities from outbreak data requires detailed contact tracing information. CONCLUSION: High estimates of the proportion of pre-symptomatic transmission imply that case finding and contact tracing need to be supplemented by physical distancing measures in order to control the COVID-19 outbreak. Notably, quarantine and other containment measures were already in place at the time of data collection, which may inflate the proportion of infections from pre-symptomatic individuals. |
format | Online Article Text |
id | pubmed-7201952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | European Centre for Disease Prevention and Control (ECDC) |
record_format | MEDLINE/PubMed |
spelling | pubmed-72019522020-05-08 Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 Ganyani, Tapiwa Kremer, Cécile Chen, Dongxuan Torneri, Andrea Faes, Christel Wallinga, Jacco Hens, Niel Euro Surveill Research BACKGROUND: Estimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies. AIM: We estimate the generation interval, serial interval, proportion of pre-symptomatic transmission and effective reproduction number of COVID-19. We illustrate that reproduction numbers calculated based on serial interval estimates can be biased. METHODS: We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates, we obtained the serial interval, proportions of pre-symptomatic transmission and reproduction numbers. RESULTS: The mean generation interval was 5.20 days (95% credible interval (CrI): 3.78–6.78) for Singapore and 3.95 days (95% CrI: 3.01–4.91) for Tianjin. The proportion of pre-symptomatic transmission was 48% (95% CrI: 32–67) for Singapore and 62% (95% CrI: 50–76) for Tianjin. Reproduction number estimates based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Sensitivity analyses showed that estimating these quantities from outbreak data requires detailed contact tracing information. CONCLUSION: High estimates of the proportion of pre-symptomatic transmission imply that case finding and contact tracing need to be supplemented by physical distancing measures in order to control the COVID-19 outbreak. Notably, quarantine and other containment measures were already in place at the time of data collection, which may inflate the proportion of infections from pre-symptomatic individuals. European Centre for Disease Prevention and Control (ECDC) 2020-04-30 /pmc/articles/PMC7201952/ /pubmed/32372755 http://dx.doi.org/10.2807/1560-7917.ES.2020.25.17.2000257 Text en This article is copyright of the authors or their affiliated institutions, 2020. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made. |
spellingShingle | Research Ganyani, Tapiwa Kremer, Cécile Chen, Dongxuan Torneri, Andrea Faes, Christel Wallinga, Jacco Hens, Niel Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 |
title | Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 |
title_full | Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 |
title_fullStr | Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 |
title_full_unstemmed | Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 |
title_short | Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 |
title_sort | estimating the generation interval for coronavirus disease (covid-19) based on symptom onset data, march 2020 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201952/ https://www.ncbi.nlm.nih.gov/pubmed/32372755 http://dx.doi.org/10.2807/1560-7917.ES.2020.25.17.2000257 |
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