Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.

Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 20...

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Autores principales:	Leandro Layter Xavier, Nildimar Alves Honório, José Francisco Moreira Pessanha, Paulo César Peiter
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f338db46671d481c8e17daf078b4d076
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spelling	oai:doaj.org-article:f338db46671d481c8e17daf078b4d0762021-11-25T06:23:45ZAnalysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.1932-620310.1371/journal.pone.0251403https://doaj.org/article/f338db46671d481c8e17daf078b4d0762021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0251403https://doaj.org/toc/1932-6203Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 2019, which means an incidence rate of 735 for every 100 thousand inhabitants. Climate is an important factor in the temporal and spatial distribution of vector-borne diseases, such as dengue. Thus, rainfall and temperature are considered macro-factors determinants for dengue, since they directly influence the population density of Aedes aegypti, which is subject to seasonal fluctuations, mainly due to these variables. This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables data obtained from remote sensing via artificial satellites in the metropolitan region of Rio de Janeiro, Brazil. The mathematical model that best fits the data is based on an auto-regressive moving average with exogenous inputs (ARMAX). It reproduced the values of incidence rates in the study period and managed to predict with good precision in a one-year horizon. The approach described in present work may be replicated in cities around the world by the public health managers, to build auxiliary operational tools for control and prevention tasks of dengue, as well of other arbovirus diseases.Leandro Layter XavierNildimar Alves HonórioJosé Francisco Moreira PessanhaPaulo César PeiterPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0251403 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Leandro Layter Xavier Nildimar Alves Honório José Francisco Moreira Pessanha Paulo César Peiter Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.
description	Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 2019, which means an incidence rate of 735 for every 100 thousand inhabitants. Climate is an important factor in the temporal and spatial distribution of vector-borne diseases, such as dengue. Thus, rainfall and temperature are considered macro-factors determinants for dengue, since they directly influence the population density of Aedes aegypti, which is subject to seasonal fluctuations, mainly due to these variables. This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables data obtained from remote sensing via artificial satellites in the metropolitan region of Rio de Janeiro, Brazil. The mathematical model that best fits the data is based on an auto-regressive moving average with exogenous inputs (ARMAX). It reproduced the values of incidence rates in the study period and managed to predict with good precision in a one-year horizon. The approach described in present work may be replicated in cities around the world by the public health managers, to build auxiliary operational tools for control and prevention tasks of dengue, as well of other arbovirus diseases.
format	article
author	Leandro Layter Xavier Nildimar Alves Honório José Francisco Moreira Pessanha Paulo César Peiter
author_facet	Leandro Layter Xavier Nildimar Alves Honório José Francisco Moreira Pessanha Paulo César Peiter
author_sort	Leandro Layter Xavier
title	Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.
title_short	Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.
title_full	Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.
title_fullStr	Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.
title_full_unstemmed	Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.
title_sort	analysis of climate factors and dengue incidence in the metropolitan region of rio de janeiro, brazil.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/f338db46671d481c8e17daf078b4d076
work_keys_str_mv	AT leandrolayterxavier analysisofclimatefactorsanddengueincidenceinthemetropolitanregionofriodejaneirobrazil AT nildimaralveshonorio analysisofclimatefactorsanddengueincidenceinthemetropolitanregionofriodejaneirobrazil AT josefranciscomoreirapessanha analysisofclimatefactorsanddengueincidenceinthemetropolitanregionofriodejaneirobrazil AT paulocesarpeiter analysisofclimatefactorsanddengueincidenceinthemetropolitanregionofriodejaneirobrazil
_version_	1718413778893144064

Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.

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