Integrating psychosocial variables and societal diversity in epidemic models for predicting COVID-19 transmission dynamics.

ABSTRACT: During the current COVID-19 pandemic, governments must make decisions based on a variety of information including estimations of infection spread, health care capacity, economic and psychosocial considerations. The disparate validity of current short-term forecasts of these factors is a major challenge to governments. By causally linking an established epidemiological spread model with dynamically evolving psychosocial variables, using Bayesian inference we estimate the strength and direction of these interactions for German and Danish data of disease spread, human mobility, and psychosocial factors based on the serial cross-sectional COVID-19 Snapshot Monitoring (COSMO; N = 16,981). We demonstrate that the strength of cumulative influence of psychosocial variables on infection rates is of

SUBMITTER: Jirsa VK 

PROVIDER: S-EPMC9931295 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature