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Mapping and characterizing areas with high levels of malaria in pregnancy in Brazil: A spatiotemporal analysis
BACKGROUND: Malaria in pregnancy (MiP) is a public health problem in the Brazilian Amazon region that requires special attention due to associated serious adverse consequences, such as low birth weight, increased prematurity and spontaneous abortion rates. In Brazil, there have been no comprehensive...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903888/ https://www.ncbi.nlm.nih.gov/pubmed/36776427 http://dx.doi.org/10.1016/j.lana.2022.100285 |
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author | Dombrowski, Jamille Gregório Gomes, Laura Cordeiro Lorenz, Camila Palasio, Raquel Gardini Sanches Marchesini, Paola Epiphanio, Sabrina Marinho, Claudio Romero Farias |
author_facet | Dombrowski, Jamille Gregório Gomes, Laura Cordeiro Lorenz, Camila Palasio, Raquel Gardini Sanches Marchesini, Paola Epiphanio, Sabrina Marinho, Claudio Romero Farias |
author_sort | Dombrowski, Jamille Gregório |
collection | PubMed |
description | BACKGROUND: Malaria in pregnancy (MiP) is a public health problem in the Brazilian Amazon region that requires special attention due to associated serious adverse consequences, such as low birth weight, increased prematurity and spontaneous abortion rates. In Brazil, there have been no comprehensive epidemiological studies of MiP. In this study, we aimed to explore the spatial and spatiotemporal patterns of MiP in Brazil and epidemiologically characterize this population of pregnant women over a period of 15 years. METHODS: We performed a national-scale ecological analysis using a Bayesian space-time hierarchical model to estimate the incidence rates of MiP between 1 January 2004 and 31 December 2018. We mapped the high-incidence clusters among pregnant women aged 10-49 years old using a Poisson model, and we characterized the population based on data from the Epidemiological Surveillance Information System for Malaria (SIVEP-Malaria). FINDINGS: We consolidated the data of 61,833 women with MiP in Brazil. Our results showed a reduction of 50·1% (95% CI: 47·3 to 52·9) in the number of malaria cases over the period analysed, with Plasmodium vivax malaria having the highest incidence. MiP was widely distributed throughout the Amazon region, and spatial and spatiotemporal analyses revealed statistically significant clusters in some municipalities of Amazonas, Acre, Rondônia and Pará. In addition, we observed that younger pregnant women had a higher risk of infection, and the administration of appropriate treatment requires more attention. INTERPRETATION: This nationwide study provides robust evidence that, despite the reduction in the number of MiP cases in the country, it remains a serious public health problem, especially for young pregnant women. Our analyses highlight focus areas for strengthening interventions to control and eliminate MiP. FUNDING: FAPESP and CNPq - Brazil. |
format | Online Article Text |
id | pubmed-9903888 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99038882023-02-10 Mapping and characterizing areas with high levels of malaria in pregnancy in Brazil: A spatiotemporal analysis Dombrowski, Jamille Gregório Gomes, Laura Cordeiro Lorenz, Camila Palasio, Raquel Gardini Sanches Marchesini, Paola Epiphanio, Sabrina Marinho, Claudio Romero Farias Lancet Reg Health Am Articles BACKGROUND: Malaria in pregnancy (MiP) is a public health problem in the Brazilian Amazon region that requires special attention due to associated serious adverse consequences, such as low birth weight, increased prematurity and spontaneous abortion rates. In Brazil, there have been no comprehensive epidemiological studies of MiP. In this study, we aimed to explore the spatial and spatiotemporal patterns of MiP in Brazil and epidemiologically characterize this population of pregnant women over a period of 15 years. METHODS: We performed a national-scale ecological analysis using a Bayesian space-time hierarchical model to estimate the incidence rates of MiP between 1 January 2004 and 31 December 2018. We mapped the high-incidence clusters among pregnant women aged 10-49 years old using a Poisson model, and we characterized the population based on data from the Epidemiological Surveillance Information System for Malaria (SIVEP-Malaria). FINDINGS: We consolidated the data of 61,833 women with MiP in Brazil. Our results showed a reduction of 50·1% (95% CI: 47·3 to 52·9) in the number of malaria cases over the period analysed, with Plasmodium vivax malaria having the highest incidence. MiP was widely distributed throughout the Amazon region, and spatial and spatiotemporal analyses revealed statistically significant clusters in some municipalities of Amazonas, Acre, Rondônia and Pará. In addition, we observed that younger pregnant women had a higher risk of infection, and the administration of appropriate treatment requires more attention. INTERPRETATION: This nationwide study provides robust evidence that, despite the reduction in the number of MiP cases in the country, it remains a serious public health problem, especially for young pregnant women. Our analyses highlight focus areas for strengthening interventions to control and eliminate MiP. FUNDING: FAPESP and CNPq - Brazil. Elsevier 2022-05-27 /pmc/articles/PMC9903888/ /pubmed/36776427 http://dx.doi.org/10.1016/j.lana.2022.100285 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Articles Dombrowski, Jamille Gregório Gomes, Laura Cordeiro Lorenz, Camila Palasio, Raquel Gardini Sanches Marchesini, Paola Epiphanio, Sabrina Marinho, Claudio Romero Farias Mapping and characterizing areas with high levels of malaria in pregnancy in Brazil: A spatiotemporal analysis |
title | Mapping and characterizing areas with high levels of malaria in pregnancy in Brazil: A spatiotemporal analysis |
title_full | Mapping and characterizing areas with high levels of malaria in pregnancy in Brazil: A spatiotemporal analysis |
title_fullStr | Mapping and characterizing areas with high levels of malaria in pregnancy in Brazil: A spatiotemporal analysis |
title_full_unstemmed | Mapping and characterizing areas with high levels of malaria in pregnancy in Brazil: A spatiotemporal analysis |
title_short | Mapping and characterizing areas with high levels of malaria in pregnancy in Brazil: A spatiotemporal analysis |
title_sort | mapping and characterizing areas with high levels of malaria in pregnancy in brazil: a spatiotemporal analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903888/ https://www.ncbi.nlm.nih.gov/pubmed/36776427 http://dx.doi.org/10.1016/j.lana.2022.100285 |
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