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Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders
India has made tremendous progress in reducing malaria mortality and morbidity in the last decade. Mizoram State in North-East India is one of the few malaria-endemic regions where malaria transmission has continued to remain high. As Mizoram shares international borders with Bangladesh and Myanmar,...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025798/ https://www.ncbi.nlm.nih.gov/pubmed/36941291 http://dx.doi.org/10.1038/s41598-023-31632-6 |
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author | Lalmalsawma, Pachuau Balasubramani, K. James, Meenu Mariya Pautu, Lalfakzuala Prasad, Kumar Arun Sarma, Devojit Kumar Balabaskaran Nina, Praveen |
author_facet | Lalmalsawma, Pachuau Balasubramani, K. James, Meenu Mariya Pautu, Lalfakzuala Prasad, Kumar Arun Sarma, Devojit Kumar Balabaskaran Nina, Praveen |
author_sort | Lalmalsawma, Pachuau |
collection | PubMed |
description | India has made tremendous progress in reducing malaria mortality and morbidity in the last decade. Mizoram State in North-East India is one of the few malaria-endemic regions where malaria transmission has continued to remain high. As Mizoram shares international borders with Bangladesh and Myanmar, malaria control in this region is critical for malaria elimination efforts in all the three countries. For identifying hotspots for targeted intervention, malaria data from 385 public health sub-centers across Mizoram were analyzed in the Geographic Information System. Almost all the sub-centers reporting high Annual Parasite Index (> 10) are located in Mizoram’s districts that border Bangladesh. Getis-Ord G(i)* statistic shows most of the sub-centers located along the Bangladesh border in the Lawngtlai and Lunglei districts to be the malaria hotspots. The hotspots also extended into the Mamit and Siaha districts, especially along the borders of Lawngtlai and Lunglei. Analysis of terrain, climatic, and land use/land cover datasets obtained from the Global Modelling and Assimilation Office and satellite images show Mizoram’s western part (Lawngtlai, Lunglei, and Mamit districts) to experience similar topographic and climatic conditions as the bordering Rangamati district in the Chittagong division of Bangladesh. Climatic trends in this region from 1981 to 2021, estimated by the Mann–Kendall test and Sen's slope estimates, show an increasing trend in minimum temperature, relative humidity, rainfall, and the associated shift of climatic pattern (temperate to tropical monsoon) could facilitate malaria transmission. The quasi-Poisson regression model estimates a strong association (p < 0.001) between total malaria cases, temperature range, and elevation. The Kruskal–Wallis H test shows a statistically significant association between malaria cases and forest classes (p < 0.001). A regional coordination and strategic plan are required to eliminate malaria from this hyper-endemic malaria region of North-East India. |
format | Online Article Text |
id | pubmed-10025798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100257982023-03-21 Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders Lalmalsawma, Pachuau Balasubramani, K. James, Meenu Mariya Pautu, Lalfakzuala Prasad, Kumar Arun Sarma, Devojit Kumar Balabaskaran Nina, Praveen Sci Rep Article India has made tremendous progress in reducing malaria mortality and morbidity in the last decade. Mizoram State in North-East India is one of the few malaria-endemic regions where malaria transmission has continued to remain high. As Mizoram shares international borders with Bangladesh and Myanmar, malaria control in this region is critical for malaria elimination efforts in all the three countries. For identifying hotspots for targeted intervention, malaria data from 385 public health sub-centers across Mizoram were analyzed in the Geographic Information System. Almost all the sub-centers reporting high Annual Parasite Index (> 10) are located in Mizoram’s districts that border Bangladesh. Getis-Ord G(i)* statistic shows most of the sub-centers located along the Bangladesh border in the Lawngtlai and Lunglei districts to be the malaria hotspots. The hotspots also extended into the Mamit and Siaha districts, especially along the borders of Lawngtlai and Lunglei. Analysis of terrain, climatic, and land use/land cover datasets obtained from the Global Modelling and Assimilation Office and satellite images show Mizoram’s western part (Lawngtlai, Lunglei, and Mamit districts) to experience similar topographic and climatic conditions as the bordering Rangamati district in the Chittagong division of Bangladesh. Climatic trends in this region from 1981 to 2021, estimated by the Mann–Kendall test and Sen's slope estimates, show an increasing trend in minimum temperature, relative humidity, rainfall, and the associated shift of climatic pattern (temperate to tropical monsoon) could facilitate malaria transmission. The quasi-Poisson regression model estimates a strong association (p < 0.001) between total malaria cases, temperature range, and elevation. The Kruskal–Wallis H test shows a statistically significant association between malaria cases and forest classes (p < 0.001). A regional coordination and strategic plan are required to eliminate malaria from this hyper-endemic malaria region of North-East India. Nature Publishing Group UK 2023-03-20 /pmc/articles/PMC10025798/ /pubmed/36941291 http://dx.doi.org/10.1038/s41598-023-31632-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) . |
spellingShingle | Article Lalmalsawma, Pachuau Balasubramani, K. James, Meenu Mariya Pautu, Lalfakzuala Prasad, Kumar Arun Sarma, Devojit Kumar Balabaskaran Nina, Praveen Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders |
title | Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders |
title_full | Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders |
title_fullStr | Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders |
title_full_unstemmed | Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders |
title_short | Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders |
title_sort | malaria hotspots and climate change trends in the hyper-endemic malaria settings of mizoram along the india–bangladesh borders |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025798/ https://www.ncbi.nlm.nih.gov/pubmed/36941291 http://dx.doi.org/10.1038/s41598-023-31632-6 |
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