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Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model
BACKGROUND: In Brazil, malaria is caused mainly by the Plasmodium vivax and Plasmodium falciparum species. Its transmission occurs in endemic and non-endemic areas. Malaria geography in Brazil has retracted and is now concentrated in the North region. The Brazilian Amazon region accounts for 99% of...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9153870/ https://www.ncbi.nlm.nih.gov/pubmed/35641976 http://dx.doi.org/10.1186/s12936-022-04162-1 |
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author | Garcia, Klauss Kleydmann Sabino Abrahão, Amanda Amaral Oliveira, Ana Flávia de Morais Henriques, Karina Medeiros de Deus de Pina-Costa, Anielle Siqueira, André Machado Ramalho, Walter Massa |
author_facet | Garcia, Klauss Kleydmann Sabino Abrahão, Amanda Amaral Oliveira, Ana Flávia de Morais Henriques, Karina Medeiros de Deus de Pina-Costa, Anielle Siqueira, André Machado Ramalho, Walter Massa |
author_sort | Garcia, Klauss Kleydmann Sabino |
collection | PubMed |
description | BACKGROUND: In Brazil, malaria is caused mainly by the Plasmodium vivax and Plasmodium falciparum species. Its transmission occurs in endemic and non-endemic areas. Malaria geography in Brazil has retracted and is now concentrated in the North region. The Brazilian Amazon region accounts for 99% of Brazil's cases. Brazil’s extra-Amazon region has a high frequency of imported cases and in 2019 presented a mortality rate 123 times higher than the Amazon region. Extra-Amazon cases present risks of reintroduction. This study aims to characterize the epidemiological scenario for malaria in the extra-Amazon region of Brazil from 2011 to 2020 with a two-year forecast. METHODS: Time-series study with description of malaria cases and deaths registered in Brazilian extra-Amazon region from 2011 to 2020. Public data from the Notifiable Diseases Information System (Sinan) and the Mortality Information System (SIM) were used. Descriptive analysis, incidence, and notification rates were calculated. Flow charts analysed the flux between Places of Probable Infection (PI) and places of notification. The prediction model utilized a multiplicative Holt-winters model for trend and seasonality components. RESULTS: A total of 6849 cases were registered. Cases were predominantly white males with 9 to 11 years of education, mostly between 30 and 39 years old. Imported cases accounted for 78.9% of cases. Most frequent occupations for imported cases are related to travelling and tourism activities. Among autochthonous cases, there is a higher frequency of agriculture and domestic economic activities. In the period there were 118 deaths due to malaria, of which 34.7% were caused by P. falciparum infections and 48.3% were not specified. The most intense flows of imported cases are from Amazonas and Rondônia to São Paulo, Rio de Janeiro, and Paraná. The prediction estimates around 611 cases for each of the following two years. CONCLUSION: The time series allows a vast epidemiological visualization with a short-term prediction analysis that supports public health planning. Government actions need to be better directed in the extra-Amazon region so the objective of eliminating malaria in Brazil is achieved. Carrying out quality assessments for information systems and qualifying personnel is advisable. Malaria outside the Amazon region is mainly due to imported cases and delay in diagnosis is associated with a higher fatality rate. Better strategies to diagnose and treat suspected cases can lead to lower risk of deaths and local outbreaks that will be important for achieving malaria elimination in Brazil. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-022-04162-1. |
format | Online Article Text |
id | pubmed-9153870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91538702022-06-02 Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model Garcia, Klauss Kleydmann Sabino Abrahão, Amanda Amaral Oliveira, Ana Flávia de Morais Henriques, Karina Medeiros de Deus de Pina-Costa, Anielle Siqueira, André Machado Ramalho, Walter Massa Malar J Research BACKGROUND: In Brazil, malaria is caused mainly by the Plasmodium vivax and Plasmodium falciparum species. Its transmission occurs in endemic and non-endemic areas. Malaria geography in Brazil has retracted and is now concentrated in the North region. The Brazilian Amazon region accounts for 99% of Brazil's cases. Brazil’s extra-Amazon region has a high frequency of imported cases and in 2019 presented a mortality rate 123 times higher than the Amazon region. Extra-Amazon cases present risks of reintroduction. This study aims to characterize the epidemiological scenario for malaria in the extra-Amazon region of Brazil from 2011 to 2020 with a two-year forecast. METHODS: Time-series study with description of malaria cases and deaths registered in Brazilian extra-Amazon region from 2011 to 2020. Public data from the Notifiable Diseases Information System (Sinan) and the Mortality Information System (SIM) were used. Descriptive analysis, incidence, and notification rates were calculated. Flow charts analysed the flux between Places of Probable Infection (PI) and places of notification. The prediction model utilized a multiplicative Holt-winters model for trend and seasonality components. RESULTS: A total of 6849 cases were registered. Cases were predominantly white males with 9 to 11 years of education, mostly between 30 and 39 years old. Imported cases accounted for 78.9% of cases. Most frequent occupations for imported cases are related to travelling and tourism activities. Among autochthonous cases, there is a higher frequency of agriculture and domestic economic activities. In the period there were 118 deaths due to malaria, of which 34.7% were caused by P. falciparum infections and 48.3% were not specified. The most intense flows of imported cases are from Amazonas and Rondônia to São Paulo, Rio de Janeiro, and Paraná. The prediction estimates around 611 cases for each of the following two years. CONCLUSION: The time series allows a vast epidemiological visualization with a short-term prediction analysis that supports public health planning. Government actions need to be better directed in the extra-Amazon region so the objective of eliminating malaria in Brazil is achieved. Carrying out quality assessments for information systems and qualifying personnel is advisable. Malaria outside the Amazon region is mainly due to imported cases and delay in diagnosis is associated with a higher fatality rate. Better strategies to diagnose and treat suspected cases can lead to lower risk of deaths and local outbreaks that will be important for achieving malaria elimination in Brazil. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-022-04162-1. BioMed Central 2022-05-31 /pmc/articles/PMC9153870/ /pubmed/35641976 http://dx.doi.org/10.1186/s12936-022-04162-1 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 Garcia, Klauss Kleydmann Sabino Abrahão, Amanda Amaral Oliveira, Ana Flávia de Morais Henriques, Karina Medeiros de Deus de Pina-Costa, Anielle Siqueira, André Machado Ramalho, Walter Massa Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model |
title | Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model |
title_full | Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model |
title_fullStr | Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model |
title_full_unstemmed | Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model |
title_short | Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model |
title_sort | malaria time series in the extra-amazon region of brazil: epidemiological scenario and a two-year prediction model |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9153870/ https://www.ncbi.nlm.nih.gov/pubmed/35641976 http://dx.doi.org/10.1186/s12936-022-04162-1 |
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