Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro

Detalhes bibliográficos
Autor(a) principal: Dodero-Rojas, Esteban
Data de Publicação: 2020
Outros Autores: Ferreira, Luiza G., Leite, Vitor B.P. [UNESP], Onuchic, José N., Contessoto, Vinícius G.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1371/journal.pone.0222900
http://hdl.handle.net/11449/198464
Resumo: Mosquito-borne diseases have become a significant health issue in many regions around the world. For tropical countries, diseases such as Dengue, Zika, and Chikungunya, became epidemic in the last decades. Health surveillance reports during this period were crucial in providing scientific-based information to guide decision making and resources allocation to control outbreaks. In this work, we perform data analysis of the last Chikungunya epidemics in the city of Rio de Janeiro by applying a compartmental mathematical model. Sensitivity analyses were performed in order to describe the contribution of each parameter to the outbreak incidence. We estimate the basic reproduction number for those outbreaks and predict the potential epidemic outbreak of the Mayaro virus. We also simulated several scenarios with different public interventions to decrease the number of infected people. Such scenarios should provide insights about possible strategies to control future outbreaks.
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spelling Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de JaneiroMosquito-borne diseases have become a significant health issue in many regions around the world. For tropical countries, diseases such as Dengue, Zika, and Chikungunya, became epidemic in the last decades. Health surveillance reports during this period were crucial in providing scientific-based information to guide decision making and resources allocation to control outbreaks. In this work, we perform data analysis of the last Chikungunya epidemics in the city of Rio de Janeiro by applying a compartmental mathematical model. Sensitivity analyses were performed in order to describe the contribution of each parameter to the outbreak incidence. We estimate the basic reproduction number for those outbreaks and predict the potential epidemic outbreak of the Mayaro virus. We also simulated several scenarios with different public interventions to decrease the number of infected people. Such scenarios should provide insights about possible strategies to control future outbreaks.Center for Theoretical Biological Physics Rice UniversityTheoretical and Computational Physics Laboratory University of Costa RicaDepartment of Chemistry Rice UniversityDepartment of Physics Institute of Biosciences Letters and Exact Sciences São Paulo State University - UNESPDepartment of Physics and Astronomy Rice UniversityDepartment of Biosciences Rice UniversityBrazilian Biorenewables National Laboratory - LNBR Brazilian Center for Research in Energy and Materials - CNPEMDepartment of Physics Institute of Biosciences Letters and Exact Sciences São Paulo State University - UNESPRice UniversityUniversity of Costa RicaUniversidade Estadual Paulista (Unesp)Brazilian Center for Research in Energy and Materials - CNPEMDodero-Rojas, EstebanFerreira, Luiza G.Leite, Vitor B.P. [UNESP]Onuchic, José N.Contessoto, Vinícius G.2020-12-12T01:13:38Z2020-12-12T01:13:38Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1371/journal.pone.0222900PLoS ONE, v. 15, n. 1, 2020.1932-6203http://hdl.handle.net/11449/19846410.1371/journal.pone.02229002-s2.0-85078688285Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPLoS ONEinfo:eu-repo/semantics/openAccess2021-10-22T12:25:07Zoai:repositorio.unesp.br:11449/198464Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-22T12:25:07Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
title Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
spellingShingle Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
Dodero-Rojas, Esteban
title_short Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
title_full Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
title_fullStr Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
title_full_unstemmed Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
title_sort Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
author Dodero-Rojas, Esteban
author_facet Dodero-Rojas, Esteban
Ferreira, Luiza G.
Leite, Vitor B.P. [UNESP]
Onuchic, José N.
Contessoto, Vinícius G.
author_role author
author2 Ferreira, Luiza G.
Leite, Vitor B.P. [UNESP]
Onuchic, José N.
Contessoto, Vinícius G.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Rice University
University of Costa Rica
Universidade Estadual Paulista (Unesp)
Brazilian Center for Research in Energy and Materials - CNPEM
dc.contributor.author.fl_str_mv Dodero-Rojas, Esteban
Ferreira, Luiza G.
Leite, Vitor B.P. [UNESP]
Onuchic, José N.
Contessoto, Vinícius G.
description Mosquito-borne diseases have become a significant health issue in many regions around the world. For tropical countries, diseases such as Dengue, Zika, and Chikungunya, became epidemic in the last decades. Health surveillance reports during this period were crucial in providing scientific-based information to guide decision making and resources allocation to control outbreaks. In this work, we perform data analysis of the last Chikungunya epidemics in the city of Rio de Janeiro by applying a compartmental mathematical model. Sensitivity analyses were performed in order to describe the contribution of each parameter to the outbreak incidence. We estimate the basic reproduction number for those outbreaks and predict the potential epidemic outbreak of the Mayaro virus. We also simulated several scenarios with different public interventions to decrease the number of infected people. Such scenarios should provide insights about possible strategies to control future outbreaks.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-12T01:13:38Z
2020-12-12T01:13:38Z
2020-01-01
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.0222900
PLoS ONE, v. 15, n. 1, 2020.
1932-6203
http://hdl.handle.net/11449/198464
10.1371/journal.pone.0222900
2-s2.0-85078688285
url http://dx.doi.org/10.1371/journal.pone.0222900
http://hdl.handle.net/11449/198464
identifier_str_mv PLoS ONE, v. 15, n. 1, 2020.
1932-6203
10.1371/journal.pone.0222900
2-s2.0-85078688285
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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