Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
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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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:29462024-08-05T20:27:43.949759Repositório 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) |
repository.mail.fl_str_mv |
|
_version_ |
1808129205537341440 |