Scientific article
OA Policy
English

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

Published inEmerging infectious diseases, vol. 26, no. 11, e201074
Publication date2020-11
Abstract

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.

Keywords
  • 2019 novel coronavirus disease
  • COVID-19
  • SARS-CoV-2
  • World Health Organization
  • Coronavirus
  • Epidemiological parameters
  • Mathematical modeling
  • Severe acute respiratory syndrome coronavirus 2
  • Viruses
  • Zoonoses
Affiliation entities Not a UNIGE publication
Funding
  • Medical Research Council - [MC_PC_19012]
  • UK Research and Innovation - MRC Centre for Global Infectious Disease Analysis [MR/R015600/1]
Citation (ISO format)
BIGGERSTAFF, Matthew et al. Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19. In: Emerging infectious diseases, 2020, vol. 26, n° 11, p. e201074. doi: 10.3201/eid2611.201074
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Article (Published version)
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Identifiers
Journal ISSN1080-6040
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Technical informations

Creation29/05/2024 08:31:19
First validation05/07/2024 14:49:47
Update time05/07/2024 14:49:47
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