In:
PLOS Digital Health, Public Library of Science (PLoS), Vol. 1, No. 8 ( 2022-8-31), p. e0000098-
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 a similar magnitude as the influence of physical distancing. We further show that the efficacy of political interventions to contain the disease strongly depends on societal diversity, in particular group-specific sensitivity to affective risk perception. As a consequence, the model may assist in quantifying the effect and timing of interventions, forecasting future scenarios, and differentiating the impact on diverse groups as a function of their societal organization. Importantly, the careful handling of societal factors, including support to the more vulnerable groups, adds another direct instrument to the battery of political interventions fighting epidemic spread.
Type of Medium:
Online Resource
ISSN:
2767-3170
DOI:
10.1371/journal.pdig.0000098
DOI:
10.1371/journal.pdig.0000098.g001
DOI:
10.1371/journal.pdig.0000098.g002
DOI:
10.1371/journal.pdig.0000098.g003
DOI:
10.1371/journal.pdig.0000098.g004
DOI:
10.1371/journal.pdig.0000098.g005
DOI:
10.1371/journal.pdig.0000098.s001
DOI:
10.1371/journal.pdig.0000098.s002
DOI:
10.1371/journal.pdig.0000098.s003
DOI:
10.1371/journal.pdig.0000098.s004
DOI:
10.1371/journal.pdig.0000098.s005
DOI:
10.1371/journal.pdig.0000098.s006
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
3106944-7