Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification, United States.
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ABSTRACT:
SUBMITTER: Lin YT
PROVIDER: S-EPMC7920670 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification, United States.
Lin Yen Ting YT Neumann Jacob J Miller Ely F EF Posner Richard G RG Mallela Abhishek A Safta Cosmin C Ray Jaideep J Thakur Gautam G Chinthavali Supriya S Hlavacek William S WS
Emerging infectious diseases 20210101 3
To increase situational awareness and support evidence-based policymaking, we formulated a mathematical model for coronavirus disease transmission within a regional population. This compartmental model accounts for quarantine, self-isolation, social distancing, a nonexponentially distributed incubation period, asymptomatic persons, and mild and severe forms of symptomatic disease. We used Bayesian inference to calibrate region-specific models for consistency with daily reports of confirmed cases ...[more]
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