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Improved time-varying reproduction numbers using the generation interval for COVID-19
Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation interval (GI) and latent period, is essential to quantify the transmissibility and effects of various interventions of COVID-19. These key parameters play a critical role in quantifying the basic r...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10348824/ https://www.ncbi.nlm.nih.gov/pubmed/37457248 http://dx.doi.org/10.3389/fpubh.2023.1185854 |
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author | Kim, Tobhin Lee, Hyojung Kim, Sungchan Kim, Changhoon Son, Hyunjin Lee, Sunmi |
author_facet | Kim, Tobhin Lee, Hyojung Kim, Sungchan Kim, Changhoon Son, Hyunjin Lee, Sunmi |
author_sort | Kim, Tobhin |
collection | PubMed |
description | Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation interval (GI) and latent period, is essential to quantify the transmissibility and effects of various interventions of COVID-19. These key parameters play a critical role in quantifying the basic reproduction number. With the hard work of epidemiological investigators in South Korea, estimating these key parameters has become possible based on infector-infectee surveillance data of COVID-19 between February 2020 and April 2021. Herein, the mean incubation period was estimated to be 4.9 days (95% CI: 4.2, 5.7) and the mean generation interval was estimated to be 4.3 days (95% CI: 4.2, 4.4). The mean serial interval was estimated to be 4.3, with a standard deviation of 4.2. It is also revealed that the proportion of presymptomatic transmission was ~57%, which indicates the potential risk of transmission before the disease onset. We compared the time-varying reproduction number based on GI and SI and found that the time-varying reproduction number based on GI may result in a larger estimation of [Formula: see text] , which refers to the COVID-19 transmission potential around the rapid increase of cases. This highlights the importance of considering presymptomatic transmission and generation intervals when estimating the time-varying reproduction number. |
format | Online Article Text |
id | pubmed-10348824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103488242023-07-15 Improved time-varying reproduction numbers using the generation interval for COVID-19 Kim, Tobhin Lee, Hyojung Kim, Sungchan Kim, Changhoon Son, Hyunjin Lee, Sunmi Front Public Health Public Health Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation interval (GI) and latent period, is essential to quantify the transmissibility and effects of various interventions of COVID-19. These key parameters play a critical role in quantifying the basic reproduction number. With the hard work of epidemiological investigators in South Korea, estimating these key parameters has become possible based on infector-infectee surveillance data of COVID-19 between February 2020 and April 2021. Herein, the mean incubation period was estimated to be 4.9 days (95% CI: 4.2, 5.7) and the mean generation interval was estimated to be 4.3 days (95% CI: 4.2, 4.4). The mean serial interval was estimated to be 4.3, with a standard deviation of 4.2. It is also revealed that the proportion of presymptomatic transmission was ~57%, which indicates the potential risk of transmission before the disease onset. We compared the time-varying reproduction number based on GI and SI and found that the time-varying reproduction number based on GI may result in a larger estimation of [Formula: see text] , which refers to the COVID-19 transmission potential around the rapid increase of cases. This highlights the importance of considering presymptomatic transmission and generation intervals when estimating the time-varying reproduction number. Frontiers Media S.A. 2023-06-30 /pmc/articles/PMC10348824/ /pubmed/37457248 http://dx.doi.org/10.3389/fpubh.2023.1185854 Text en Copyright © 2023 Kim, Lee, Kim, Kim, Son and Lee. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Kim, Tobhin Lee, Hyojung Kim, Sungchan Kim, Changhoon Son, Hyunjin Lee, Sunmi Improved time-varying reproduction numbers using the generation interval for COVID-19 |
title | Improved time-varying reproduction numbers using the generation interval for COVID-19 |
title_full | Improved time-varying reproduction numbers using the generation interval for COVID-19 |
title_fullStr | Improved time-varying reproduction numbers using the generation interval for COVID-19 |
title_full_unstemmed | Improved time-varying reproduction numbers using the generation interval for COVID-19 |
title_short | Improved time-varying reproduction numbers using the generation interval for COVID-19 |
title_sort | improved time-varying reproduction numbers using the generation interval for covid-19 |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10348824/ https://www.ncbi.nlm.nih.gov/pubmed/37457248 http://dx.doi.org/10.3389/fpubh.2023.1185854 |
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