Local risk perception enhances epidemic control

Detalhes bibliográficos
Autor(a) principal: Herrera-Diestra, José L. [UNESP]
Data de Publicação: 2019
Outros Autores: Meyers, Lauren Ancel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1371/journal.pone.0225576
http://hdl.handle.net/11449/199763
Resumo: As infectious disease outbreaks emerge, public health agencies often enact vaccination and social distancing measures to slow transmission. Their success depends on not only strategies and resources, but also public adherence. Individual willingness to take precautions may be influenced by global factors, such as news media, or local factors, such as infected family members or friends. Here, we compare three modes of epidemiological decision-making in the midst of a growing outbreak using network-based mathematical models that capture plausible heterogeneity in human contact patterns. Individuals decide whether to adopt a recommended intervention based on overall disease prevalence, the proportion of social contacts infected, or the number of social contacts infected. While all strategies can substantially mitigate transmission, vaccinating (or self isolating) based on the number of infected acquaintances is expected to prevent the most infections while requiring the fewest intervention resources. Unlike the other strategies, it has a substantial herd effect, providing indirect protection to a large fraction of the population.
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spelling Local risk perception enhances epidemic controlAs infectious disease outbreaks emerge, public health agencies often enact vaccination and social distancing measures to slow transmission. Their success depends on not only strategies and resources, but also public adherence. Individual willingness to take precautions may be influenced by global factors, such as news media, or local factors, such as infected family members or friends. Here, we compare three modes of epidemiological decision-making in the midst of a growing outbreak using network-based mathematical models that capture plausible heterogeneity in human contact patterns. Individuals decide whether to adopt a recommended intervention based on overall disease prevalence, the proportion of social contacts infected, or the number of social contacts infected. While all strategies can substantially mitigate transmission, vaccinating (or self isolating) based on the number of infected acquaintances is expected to prevent the most infections while requiring the fewest intervention resources. Unlike the other strategies, it has a substantial herd effect, providing indirect protection to a large fraction of the population.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)ICTP South American Institute for Fundamental ResearchIFT-UNESPCeSiMo Facultad de Ingeniería Universidad de Los AndesDepartment of Integrative Biology University of Texas at AustinIFT-UNESPFAPESP: 2016/01343-7FAPESP: 2017/00344-2ICTP South American Institute for Fundamental ResearchUniversidade Estadual Paulista (Unesp)Universidad de Los AndesUniversity of Texas at AustinHerrera-Diestra, José L. [UNESP]Meyers, Lauren Ancel2020-12-12T01:48:38Z2020-12-12T01:48:38Z2019-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1371/journal.pone.0225576PLoS ONE, v. 14, n. 12, 2019.1932-6203http://hdl.handle.net/11449/19976310.1371/journal.pone.02255762-s2.0-85076027950Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPLoS ONEinfo:eu-repo/semantics/openAccess2021-10-23T09:34:06Zoai:repositorio.unesp.br:11449/199763Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:56:05.047798Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Local risk perception enhances epidemic control
title Local risk perception enhances epidemic control
spellingShingle Local risk perception enhances epidemic control
Herrera-Diestra, José L. [UNESP]
title_short Local risk perception enhances epidemic control
title_full Local risk perception enhances epidemic control
title_fullStr Local risk perception enhances epidemic control
title_full_unstemmed Local risk perception enhances epidemic control
title_sort Local risk perception enhances epidemic control
author Herrera-Diestra, José L. [UNESP]
author_facet Herrera-Diestra, José L. [UNESP]
Meyers, Lauren Ancel
author_role author
author2 Meyers, Lauren Ancel
author2_role author
dc.contributor.none.fl_str_mv ICTP South American Institute for Fundamental Research
Universidade Estadual Paulista (Unesp)
Universidad de Los Andes
University of Texas at Austin
dc.contributor.author.fl_str_mv Herrera-Diestra, José L. [UNESP]
Meyers, Lauren Ancel
description As infectious disease outbreaks emerge, public health agencies often enact vaccination and social distancing measures to slow transmission. Their success depends on not only strategies and resources, but also public adherence. Individual willingness to take precautions may be influenced by global factors, such as news media, or local factors, such as infected family members or friends. Here, we compare three modes of epidemiological decision-making in the midst of a growing outbreak using network-based mathematical models that capture plausible heterogeneity in human contact patterns. Individuals decide whether to adopt a recommended intervention based on overall disease prevalence, the proportion of social contacts infected, or the number of social contacts infected. While all strategies can substantially mitigate transmission, vaccinating (or self isolating) based on the number of infected acquaintances is expected to prevent the most infections while requiring the fewest intervention resources. Unlike the other strategies, it has a substantial herd effect, providing indirect protection to a large fraction of the population.
publishDate 2019
dc.date.none.fl_str_mv 2019-12-01
2020-12-12T01:48:38Z
2020-12-12T01:48:38Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1371/journal.pone.0225576
PLoS ONE, v. 14, n. 12, 2019.
1932-6203
http://hdl.handle.net/11449/199763
10.1371/journal.pone.0225576
2-s2.0-85076027950
url http://dx.doi.org/10.1371/journal.pone.0225576
http://hdl.handle.net/11449/199763
identifier_str_mv PLoS ONE, v. 14, n. 12, 2019.
1932-6203
10.1371/journal.pone.0225576
2-s2.0-85076027950
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv PLoS ONE
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
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