Characterizing Environment Factors in Local COVID-19 Emergent Phenomenon
Year: 2020
Type: conference-abstract
Abstract: Background: COVID-19 emerged in December 2019 and rapidly spread into a global pandemic. Designing optimal community responses (social distancing, vaccination) is dependent on the stage of the disease progression, discovery of asymptomatic, changes in virulence of the pathogen, and current level of herd immunity. In addition, local environmental and social factors can potentially play a role in limiting transmission. Warmer weather, higher solar ultraviolet radiation, humidity levels and good air quality have all been shown to play a role in reducing community level rates for other viruses, but the effect on COVID-19 remains uncertain. Living and working in built and controlled environments may limit the effects of these natural environmental factors. As observed in previous pandemics, social determinants of health (SDOH) are likely influence the ability of individuals and families to follow COVID-19 public health guidelines and may alter health outcomes.Methods: In order to address these complex “What if” questions, we are extending the agent-based model, SpatioTemporal Human Activity Model (STHAM) for COVID-19 simulating transmission dynamics.Results: Conceptually, individuals in STHAM are represented as agents belonging to households and work organizations, and residing in particular environments. Agents have properties representing individuals’ characteristics of demographics, occupation, socioeconomic, and immune status. The environment has its own characteristics that include weather, UV radiation and air quality. Rules describe what happens when different classes of agents interact in their environment (e.g., transmission of virus based on established rates), and the type of interactions possible under different public health scenarios.Discussion: The principle cause of spread of COVID-19 is movement and interaction of individuals within a community. As next steps, we will evaluate our concept for the effects of the environment and selective movement of individuals across time and demographic groups in the evolution of the disease for the state of Utah.
Source: ISEE Conference Abstracts
Authors: R. Gouripeddi, K. Sward, K. Davis, C. Cambron, J. Horel, J. Facelli
Institutions: University of Utah, Utah Department of Health
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3170748299