2024 journal article
COVSIM: A stochastic agent-based COVID-19 SIMulation model for North Carolina
EPIDEMICS, 46.
author keywords: COVID-19 scenario modeling hub; Stochastic agent-based simulation; Health equity; Local public health decision making; Infectious disease modeling
open access via doi.org (publisher)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
11. Sustainable Cities and Communities
(OpenAlex)
Source: Web Of Science
Added: May 7, 2024
We document the evolution and use of the stochastic agent-based COVID-19 SIMu-lation model (COVSIM) to study the impact of population behaviors and public health policy on disease spread within age, race/ethnicity, and urbanicity subpopulations in North Carolina. We detail the methodologies used to model the complexities of COVID-19, including multiple agent attributes (i.e., age, race/ethnicity, high-risk medical status), census tract-level interaction network, disease state network, agent behavior (i.e., masking, pharmaceutical intervention (PI) uptake, quarantine, mobility), and variants. We describe its uses outside of the COVID-19 Scenario Modeling Hub (CSMH), which has focused on the interplay of nonpharmaceutical and pharmaceutical interventions, equitability of vaccine distribution, and supporting local county decision-makers in North Carolina. This work has led to multiple publications and meetings with a variety of local stakeholders. When COVSIM joined the CSMH in January 2022, we found it was a sustainable way to support new COVID-19 challenges and allowed the group to focus on broader scientific questions. The CSMH has informed adaptions to our modeling approach, including redesigning our high-performance computing implementation.