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Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19
- Source :
- Biggerstaff, M, Cowling, B J, Cucunubá, Z M, Dinh, L, Ferguson, N M, Gao, H, Hill, V, Imai, N, Johansson, M A, Kada, S, Morgan, O, Pastore y Piontti, A, Polonsky, J A, Venkata Prasad, P, Quandelacy, T M, Rambaut, A, Tappero, J W, Vandemaele, K A, Vespignani, A, Warmbrod, K L & Wong, J Y 2020, ' Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19 ', Emerging Infectious Diseases, vol. 26, no. 11 . https://doi.org/10.3201/eid2611.201074, Emerging Infectious Diseases, Emerging Infectious Diseases, Vol 26, Iss 11, Pp-(2020)
- Publication Year :
- 2020
- Publisher :
- Centers for Disease Control and Prevention (CDC), 2020.
-
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.
- Subjects :
- Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19
Epidemiology
Psychological intervention
coronavirus
lcsh:Medicine
Disease
law.invention
0302 clinical medicine
law
1108 Medical Microbiology
Pandemic
Medicine
030212 general & internal medicine
mathematical modeling
Online Report
Infectious Diseases
Transmission (mechanics)
Coronavirus Infections
Serial interval
severe acute respiratory syndrome coronavirus 2
Microbiology (medical)
Coronavirus disease 2019 (COVID-19)
030231 tropical medicine
Pneumonia, Viral
epidemiological parameters
World Health Organization
Microbiology
Incubation period
lcsh:Infectious and parasitic diseases
2019 novel coronavirus disease
1117 Public Health and Health Services
03 medical and health sciences
Betacoronavirus
Disease severity
Disease Transmission, Infectious
Humans
lcsh:RC109-216
viruses
mathematical modelling
Pandemics
Models, Statistical
business.industry
SARS-CoV-2
lcsh:R
COVID-19
1103 Clinical Sciences
Models, Theoretical
zoonoses
business
Demography
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Biggerstaff, M, Cowling, B J, Cucunubá, Z M, Dinh, L, Ferguson, N M, Gao, H, Hill, V, Imai, N, Johansson, M A, Kada, S, Morgan, O, Pastore y Piontti, A, Polonsky, J A, Venkata Prasad, P, Quandelacy, T M, Rambaut, A, Tappero, J W, Vandemaele, K A, Vespignani, A, Warmbrod, K L & Wong, J Y 2020, ' Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19 ', Emerging Infectious Diseases, vol. 26, no. 11 . https://doi.org/10.3201/eid2611.201074, Emerging Infectious Diseases, Emerging Infectious Diseases, Vol 26, Iss 11, Pp-(2020)
- Accession number :
- edsair.doi.dedup.....d986694b38cec2ea6265585cd702cf92
- Full Text :
- https://doi.org/10.3201/eid2611.201074