Cargando…

On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis

BACKGROUND: Malaria incidence in Brazil reversed its decreasing trend when cases from recent years, as recent as 2015, exhibited an increase in the Brazilian Amazon basin, the area with the highest transmission of Plasmodium vivax and Plasmodium falciparum. In fact, an increase of more than 20% in t...

Descripción completa

Detalles Bibliográficos
Autores principales: Ayala, Mario J. C., Bastos, Leonardo S., Villela, Daniel A. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851784/
https://www.ncbi.nlm.nih.gov/pubmed/35177095
http://dx.doi.org/10.1186/s12936-021-04037-x
_version_ 1784652895059181568
author Ayala, Mario J. C.
Bastos, Leonardo S.
Villela, Daniel A. M.
author_facet Ayala, Mario J. C.
Bastos, Leonardo S.
Villela, Daniel A. M.
author_sort Ayala, Mario J. C.
collection PubMed
description BACKGROUND: Malaria incidence in Brazil reversed its decreasing trend when cases from recent years, as recent as 2015, exhibited an increase in the Brazilian Amazon basin, the area with the highest transmission of Plasmodium vivax and Plasmodium falciparum. In fact, an increase of more than 20% in the years 2016 and 2017 revealed possible vulnerabilities in the national malaria-control programme. METHODS: Factors potentially associated with this reversal, including migration, economic activities, and deforestation, were studied. Past incidences of malaria cases due to P. vivax and P. falciparum were analysed with a spatio-temporal Bayesian model using more than 5 million individual records of malaria cases from January of 2003 to December of 2018 in the Brazilian Amazon to establish the municipalities with unexpected increases in cases. RESULTS: Plasmodium vivax incidence surpassed the past trends in Amazonas (AM), Amapá (AP), Acre (AC), Pará (PA), Roraima (RR), and Rondônia (RO), implying a rebound of these states between 2015 and 2018. On the other hand, P. falciparum also surpassed the past trends in AM, AC, AP, and RR with less severity than P. vivax incidence. Outdoor activities, agricultural activities, accumulated deforestation, and travelling might explain the rebound in malaria cases in RR, AM, PA, and RO, mainly in P. vivax cases. These variables, however, did not explain the rebound of either P. vivax and P. falciparum cases in AC and AP states or P. falciparum cases in RR and RO states. CONCLUSION: The Amazon basin has experienced an unexpected increase in malaria cases, mainly in P. vivax cases, in some regions of the states of Amazonas, Acre, Pará, Amapá, Roraima, and Rondônia from 2015 to 2018 and agricultural activities, outdoor activities, travelling activities, and accumulated deforestation appear linked to this rebound of cases in particular regions with different impact. This shows the multifactorial effects and the heterogeneity of the Amazon basin, boosting the necessity of focusing the malaria control programme on particular social, economic, and environmental conditions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-021-04037-x.
format Online
Article
Text
id pubmed-8851784
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-88517842022-02-22 On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis Ayala, Mario J. C. Bastos, Leonardo S. Villela, Daniel A. M. Malar J Research BACKGROUND: Malaria incidence in Brazil reversed its decreasing trend when cases from recent years, as recent as 2015, exhibited an increase in the Brazilian Amazon basin, the area with the highest transmission of Plasmodium vivax and Plasmodium falciparum. In fact, an increase of more than 20% in the years 2016 and 2017 revealed possible vulnerabilities in the national malaria-control programme. METHODS: Factors potentially associated with this reversal, including migration, economic activities, and deforestation, were studied. Past incidences of malaria cases due to P. vivax and P. falciparum were analysed with a spatio-temporal Bayesian model using more than 5 million individual records of malaria cases from January of 2003 to December of 2018 in the Brazilian Amazon to establish the municipalities with unexpected increases in cases. RESULTS: Plasmodium vivax incidence surpassed the past trends in Amazonas (AM), Amapá (AP), Acre (AC), Pará (PA), Roraima (RR), and Rondônia (RO), implying a rebound of these states between 2015 and 2018. On the other hand, P. falciparum also surpassed the past trends in AM, AC, AP, and RR with less severity than P. vivax incidence. Outdoor activities, agricultural activities, accumulated deforestation, and travelling might explain the rebound in malaria cases in RR, AM, PA, and RO, mainly in P. vivax cases. These variables, however, did not explain the rebound of either P. vivax and P. falciparum cases in AC and AP states or P. falciparum cases in RR and RO states. CONCLUSION: The Amazon basin has experienced an unexpected increase in malaria cases, mainly in P. vivax cases, in some regions of the states of Amazonas, Acre, Pará, Amapá, Roraima, and Rondônia from 2015 to 2018 and agricultural activities, outdoor activities, travelling activities, and accumulated deforestation appear linked to this rebound of cases in particular regions with different impact. This shows the multifactorial effects and the heterogeneity of the Amazon basin, boosting the necessity of focusing the malaria control programme on particular social, economic, and environmental conditions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-021-04037-x. BioMed Central 2022-02-17 /pmc/articles/PMC8851784/ /pubmed/35177095 http://dx.doi.org/10.1186/s12936-021-04037-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ayala, Mario J. C.
Bastos, Leonardo S.
Villela, Daniel A. M.
On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis
title On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis
title_full On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis
title_fullStr On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis
title_full_unstemmed On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis
title_short On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis
title_sort on multifactorial drivers for malaria rebound in brazil: a spatio-temporal analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851784/
https://www.ncbi.nlm.nih.gov/pubmed/35177095
http://dx.doi.org/10.1186/s12936-021-04037-x
work_keys_str_mv AT ayalamariojc onmultifactorialdriversformalariareboundinbrazilaspatiotemporalanalysis
AT bastosleonardos onmultifactorialdriversformalariareboundinbrazilaspatiotemporalanalysis
AT villeladanielam onmultifactorialdriversformalariareboundinbrazilaspatiotemporalanalysis