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Influence of Lived Experiences on Public Responses to Future Diseases via (De)Sensitization of Concern

Authors :
Alexander J. Pritchard
Matthew J. Silk
Nina H. Fefferman
Source :
Disaster Medicine and Public Health Preparedness. 17
Publication Year :
2022
Publisher :
Cambridge University Press (CUP), 2022.

Abstract

Objectives: Public responses to a future novel disease might be influenced by a subset of individuals who are either sensitized or desensitized to concern-generating processes through their lived experiences during the coronavirus disease 2019 (COVID-19) pandemic. Such influences may be critical for shaping public health messaging during the next emerging threat. Methods: This study explored the potential outcomes of the influence of lived experiences by using a dynamic multiplex network model to simulate a COVID-19 outbreak in a population of 2000 individuals, connected by means of disease and communication layers. Then a new disease was introduced, and a subset of individuals (50% or 100% of hospitalized during the COVID-19 outbreak) was assumed to be either sensitized or desensitized to concern-generating processes relative to the general population, which alters their adoption of non-pharmaceutical interventions (social distancing). Results: Altered perceptions and behaviors from lived experiences with COVID-19 did not necessarily result in a strong mitigating effect for the novel outbreak. When public disease response is already strong or sensitization is assumed to be a robust effect, then a sensitized subset may enhance public mitigation of an outbreak through social distancing. Conclusions: In preparing for future outbreaks, assuming an experienced and disease-aware public may compromise effective design of effective public health messaging and mitigative action.

Details

ISSN :
1938744X and 19357893
Volume :
17
Database :
OpenAIRE
Journal :
Disaster Medicine and Public Health Preparedness
Accession number :
edsair.doi.dedup.....c0a50054eff081c5d95884ea0003f4bf
Full Text :
https://doi.org/10.1017/dmp.2022.240