Data-driven mechanistic framework with stratified immunity and effective transmissibility for COVID-19 scenario projections.

ABSTRACT: Scenario-based modeling frameworks have been widely used to support policy-making at state and federal levels in the United States during the COVID-19 response. While custom-built models can be used to support one-off studies, sustained updates to projections under changing pandemic conditions requires a robust, integrated, and adaptive framework. In this paper, we describe one such framework, UVA-adaptive, that was built to support the CDC-aligned Scenario Modeling Hub (SMH) across multiple rounds, as well as weekly/biweekly projections to Virginia Department of Health (VDH) and US Department of Defense during the COVID-19 response. Building upon an existing metapopulation framework, PatchSim, UVA-adaptive uses a calibration mechanism relying on adjustable effective transmissibility as a

SUBMITTER: Porebski P 

PROVIDER: S-EPMC11205267 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature