Asymptomatic individuals can increase the final epidemic size under adaptive human behavior.

Tytuł:: Asymptomatic individuals can increase the final epidemic size under adaptive human behavior.
Autorzy:: Espinoza B; Biocomplexity Institute and Initiative, Network Systems Science and Advanced Computing Division, University of Virginia, Charlottesville, VA, USA. .
Marathe M; Biocomplexity Institute and Initiative, Network Systems Science and Advanced Computing Division, University of Virginia, Charlottesville, VA, USA.
Swarup S; Biocomplexity Institute and Initiative, Network Systems Science and Advanced Computing Division, University of Virginia, Charlottesville, VA, USA.
Thakur M; Biocomplexity Institute and Initiative, Network Systems Science and Advanced Computing Division, University of Virginia, Charlottesville, VA, USA.
Źródło:: Scientific reports [Sci Rep] 2021 Oct 05; Vol. 11 (1), pp. 19744. Date of Electronic Publication: 2021 Oct 05.
Typ publikacji:: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.
Język:: English
Imprint Name(s):: Original Publication: London : Nature Publishing Group, copyright 2011-
MeSH Terms:: Behavior*
Asymptomatic Diseases/*psychology
COVID-19/*epidemiology
Asymptomatic Diseases/epidemiology ; COVID-19/pathology ; COVID-19/virology ; Humans ; Models, Theoretical ; Perception ; SARS-CoV-2/isolation & purification
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Grant Information:: 1R01GM109718 United States NH NIH HHS; 1R01 GM109718 United States NH NIH HHS; R01 GM109718 United States GM NIGMS NIH HHS; 75D30119C05935 United States CC CDC HHS
Entry Date(s):: Date Created: 20211006 Date Completed: 20211013 Latest Revision: 20231108
Update Code:: 20240104
PubMed Central ID:: PMC8492713
DOI:: 10.1038/s41598-021-98999-2
PMID:: 34611199
: Czasopismo naukowe

Pełny tekst

Infections produced by non-symptomatic (pre-symptomatic and asymptomatic) individuals have been identified as major drivers of COVID-19 transmission. Non-symptomatic individuals, unaware of the infection risk they pose to others, may perceive themselves-and be perceived by others-as not presenting a risk of infection. Yet, many epidemiological models currently in use do not include a behavioral component, and do not address the potential consequences of risk misperception. To study the impact of behavioral adaptations to the perceived infection risk, we use a mathematical model that incorporates the behavioral decisions of individuals, based on a projection of the system's future state over a finite planning horizon. We found that individuals' risk misperception in the presence of non-symptomatic individuals may increase or reduce the final epidemic size. Moreover, under behavioral response the impact of non-symptomatic infections is modulated by symptomatic individuals' behavior. Finally, we found that there is an optimal planning horizon that minimizes the final epidemic size.
(© 2021. The Author(s).)

Update of: Res Sq. 2021 Feb 23;:. (PMID: 33655240)

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