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

Bibliographic Details
Title: Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19
Authors: Matthew Biggerstaff, Benjamin J. Cowling, Zulma M. Cucunubá, Linh Dinh, Neil M. Ferguson, Huizhi Gao, Verity Hill, Natsuko Imai, Michael A. Johansson, Sarah Kada, Oliver Morgan, Ana Pastore y Piontti, Jonathan A. Polonsky, Pragati Venkata Prasad, Talia M. Quandelacy, Andrew Rambaut, Jordan W. Tappero, Katelijn A. Vandemaele, Alessandro Vespignani, K. Lane Warmbrod, Jessica Y. Wong
Source: Emerging Infectious Diseases, Vol 26, Iss 11, Pp - (2020)
Publisher Information: Centers for Disease Control and Prevention, 2020.
Publication Year: 2020
Collection: LCC:Medicine
LCC:Infectious and parasitic diseases
Subject Terms: COVID-19, epidemiological parameters, mathematical modeling, World Health Organization, coronavirus, viruses, Medicine, Infectious and parasitic diseases, RC109-216
More Details: 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1080-6040
1080-6059
Relation: https://wwwnc.cdc.gov/eid/article/26/11/20-1074_article; https://doaj.org/toc/1080-6040; https://doaj.org/toc/1080-6059
DOI: 10.3201/eid2611.201074
Access URL: https://doaj.org/article/6a9644cf96214ec9998997d7d572e80a
Accession Number: edsdoj.6a9644cf96214ec9998997d7d572e80a
Database: Directory of Open Access Journals
More Details
ISSN:10806040
10806059
DOI:10.3201/eid2611.201074
Published in:Emerging Infectious Diseases
Language:English