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Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19

We report key epidemiologic parameter estimates for coronavirus disease identified in peer-reviewed publications, preprint articles, and online reports. Range estimates for incubation period were 1.8–6.9 days, serial interval 4.0–7.5 days, and doubling time 2.3–7.4 days. The effective reproductive n...

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Autores principales: Biggerstaff, Matthew, Cowling, Benjamin J., Cucunubá, Zulma M., Dinh, Linh, Ferguson, Neil M., Gao, Huizhi, Hill, Verity, Imai, Natsuko, Johansson, Michael A., Kada, Sarah, Morgan, Oliver, Pastore y Piontti, Ana, Polonsky, Jonathan A., Prasad, Pragati Venkata, Quandelacy, Talia M., Rambaut, Andrew, Tappero, Jordan W., Vandemaele, Katelijn A., Vespignani, Alessandro, Warmbrod, K. Lane, Wong, Jessica Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588530/
https://www.ncbi.nlm.nih.gov/pubmed/32917290
http://dx.doi.org/10.3201/eid2611.201074
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author Biggerstaff, Matthew
Cowling, Benjamin J.
Cucunubá, Zulma M.
Dinh, Linh
Ferguson, Neil M.
Gao, Huizhi
Hill, Verity
Imai, Natsuko
Johansson, Michael A.
Kada, Sarah
Morgan, Oliver
Pastore y Piontti, Ana
Polonsky, Jonathan A.
Prasad, Pragati Venkata
Quandelacy, Talia M.
Rambaut, Andrew
Tappero, Jordan W.
Vandemaele, Katelijn A.
Vespignani, Alessandro
Warmbrod, K. Lane
Wong, Jessica Y.
author_facet Biggerstaff, Matthew
Cowling, Benjamin J.
Cucunubá, Zulma M.
Dinh, Linh
Ferguson, Neil M.
Gao, Huizhi
Hill, Verity
Imai, Natsuko
Johansson, Michael A.
Kada, Sarah
Morgan, Oliver
Pastore y Piontti, Ana
Polonsky, Jonathan A.
Prasad, Pragati Venkata
Quandelacy, Talia M.
Rambaut, Andrew
Tappero, Jordan W.
Vandemaele, Katelijn A.
Vespignani, Alessandro
Warmbrod, K. Lane
Wong, Jessica Y.
author_sort Biggerstaff, Matthew
collection PubMed
description We report key epidemiologic parameter estimates for coronavirus disease identified in peer-reviewed publications, preprint articles, and online reports. Range estimates for incubation period were 1.8–6.9 days, serial interval 4.0–7.5 days, and doubling time 2.3–7.4 days. The effective reproductive number varied widely, with reductions attributable to interventions. Case burden and infection fatality ratios increased with patient age. Implementation of combined interventions could reduce cases and delay epidemic peak up to 1 month. These parameters for transmission, disease severity, and intervention effectiveness are critical for guiding policy decisions. Estimates will likely change as new information becomes available.
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spelling pubmed-75885302020-11-01 Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19 Biggerstaff, Matthew Cowling, Benjamin J. Cucunubá, Zulma M. Dinh, Linh Ferguson, Neil M. Gao, Huizhi Hill, Verity Imai, Natsuko Johansson, Michael A. Kada, Sarah Morgan, Oliver Pastore y Piontti, Ana Polonsky, Jonathan A. Prasad, Pragati Venkata Quandelacy, Talia M. Rambaut, Andrew Tappero, Jordan W. Vandemaele, Katelijn A. Vespignani, Alessandro Warmbrod, K. Lane Wong, Jessica Y. Emerg Infect Dis Online Report We report key epidemiologic parameter estimates for coronavirus disease identified in peer-reviewed publications, preprint articles, and online reports. Range estimates for incubation period were 1.8–6.9 days, serial interval 4.0–7.5 days, and doubling time 2.3–7.4 days. The effective reproductive number varied widely, with reductions attributable to interventions. Case burden and infection fatality ratios increased with patient age. Implementation of combined interventions could reduce cases and delay epidemic peak up to 1 month. These parameters for transmission, disease severity, and intervention effectiveness are critical for guiding policy decisions. Estimates will likely change as new information becomes available. Centers for Disease Control and Prevention 2020-11 /pmc/articles/PMC7588530/ /pubmed/32917290 http://dx.doi.org/10.3201/eid2611.201074 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.
spellingShingle Online Report
Biggerstaff, Matthew
Cowling, Benjamin J.
Cucunubá, Zulma M.
Dinh, Linh
Ferguson, Neil M.
Gao, Huizhi
Hill, Verity
Imai, Natsuko
Johansson, Michael A.
Kada, Sarah
Morgan, Oliver
Pastore y Piontti, Ana
Polonsky, Jonathan A.
Prasad, Pragati Venkata
Quandelacy, Talia M.
Rambaut, Andrew
Tappero, Jordan W.
Vandemaele, Katelijn A.
Vespignani, Alessandro
Warmbrod, K. Lane
Wong, Jessica Y.
Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19
title Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19
title_full Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19
title_fullStr Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19
title_full_unstemmed Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19
title_short Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19
title_sort early insights from statistical and mathematical modeling of key epidemiologic parameters of covid-19
topic Online Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588530/
https://www.ncbi.nlm.nih.gov/pubmed/32917290
http://dx.doi.org/10.3201/eid2611.201074
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