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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136695/ https://www.ncbi.nlm.nih.gov/pubmed/34014989 http://dx.doi.org/10.1371/journal.pone.0251403 |
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author | Xavier, Leandro Layter Honório, Nildimar Alves Pessanha, José Francisco Moreira Peiter, Paulo César |
author_facet | Xavier, Leandro Layter Honório, Nildimar Alves Pessanha, José Francisco Moreira Peiter, Paulo César |
author_sort | Xavier, Leandro Layter |
collection | PubMed |
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 | Online Article Text |
id | pubmed-8136695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-81366952021-06-02 Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil Xavier, Leandro Layter Honório, Nildimar Alves Pessanha, José Francisco Moreira Peiter, Paulo César PLoS One Research Article 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. Public Library of Science 2021-05-20 /pmc/articles/PMC8136695/ /pubmed/34014989 http://dx.doi.org/10.1371/journal.pone.0251403 Text en © 2021 Xavier et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Xavier, Leandro Layter Honório, Nildimar Alves Pessanha, José Francisco Moreira Peiter, Paulo César Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil |
title | 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_short | 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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136695/ https://www.ncbi.nlm.nih.gov/pubmed/34014989 http://dx.doi.org/10.1371/journal.pone.0251403 |
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