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Low parasite connectivity among three malaria hotspots in Thailand
Identifying sources and sinks of malaria transmission is critical for designing effective intervention strategies particularly as countries approach elimination. The number of malaria cases in Thailand decreased 90% between 2012 and 2020, yet elimination has remained a major public health challenge...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640040/ https://www.ncbi.nlm.nih.gov/pubmed/34857842 http://dx.doi.org/10.1038/s41598-021-02746-6 |
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author | Chang, Hsiao-Han Chang, Meng-Chun Kiang, Mathew Mahmud, Ayesha S. Ekapirat, Nattwut Engø-Monsen, Kenth Sudathip, Prayuth Buckee, Caroline O. Maude, Richard J. |
author_facet | Chang, Hsiao-Han Chang, Meng-Chun Kiang, Mathew Mahmud, Ayesha S. Ekapirat, Nattwut Engø-Monsen, Kenth Sudathip, Prayuth Buckee, Caroline O. Maude, Richard J. |
author_sort | Chang, Hsiao-Han |
collection | PubMed |
description | Identifying sources and sinks of malaria transmission is critical for designing effective intervention strategies particularly as countries approach elimination. The number of malaria cases in Thailand decreased 90% between 2012 and 2020, yet elimination has remained a major public health challenge with persistent transmission foci and ongoing importation. There are three main hotspots of malaria transmission in Thailand: Ubon Ratchathani and Sisaket in the Northeast; Tak in the West; and Yala in the South. However, the degree to which these hotspots are connected via travel and importation has not been well characterized. Here, we develop a metapopulation model parameterized by mobile phone call detail record data to estimate parasite flow among these regions. We show that parasite connectivity among these regions was limited, and that each of these provinces independently drove the malaria transmission in nearby provinces. Overall, our results suggest that due to the low probability of domestic importation between the transmission hotspots, control and elimination strategies can be considered separately for each region. |
format | Online Article Text |
id | pubmed-8640040 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86400402021-12-06 Low parasite connectivity among three malaria hotspots in Thailand Chang, Hsiao-Han Chang, Meng-Chun Kiang, Mathew Mahmud, Ayesha S. Ekapirat, Nattwut Engø-Monsen, Kenth Sudathip, Prayuth Buckee, Caroline O. Maude, Richard J. Sci Rep Article Identifying sources and sinks of malaria transmission is critical for designing effective intervention strategies particularly as countries approach elimination. The number of malaria cases in Thailand decreased 90% between 2012 and 2020, yet elimination has remained a major public health challenge with persistent transmission foci and ongoing importation. There are three main hotspots of malaria transmission in Thailand: Ubon Ratchathani and Sisaket in the Northeast; Tak in the West; and Yala in the South. However, the degree to which these hotspots are connected via travel and importation has not been well characterized. Here, we develop a metapopulation model parameterized by mobile phone call detail record data to estimate parasite flow among these regions. We show that parasite connectivity among these regions was limited, and that each of these provinces independently drove the malaria transmission in nearby provinces. Overall, our results suggest that due to the low probability of domestic importation between the transmission hotspots, control and elimination strategies can be considered separately for each region. Nature Publishing Group UK 2021-12-02 /pmc/articles/PMC8640040/ /pubmed/34857842 http://dx.doi.org/10.1038/s41598-021-02746-6 Text en © The Author(s) 2021 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 Chang, Hsiao-Han Chang, Meng-Chun Kiang, Mathew Mahmud, Ayesha S. Ekapirat, Nattwut Engø-Monsen, Kenth Sudathip, Prayuth Buckee, Caroline O. Maude, Richard J. Low parasite connectivity among three malaria hotspots in Thailand |
title | Low parasite connectivity among three malaria hotspots in Thailand |
title_full | Low parasite connectivity among three malaria hotspots in Thailand |
title_fullStr | Low parasite connectivity among three malaria hotspots in Thailand |
title_full_unstemmed | Low parasite connectivity among three malaria hotspots in Thailand |
title_short | Low parasite connectivity among three malaria hotspots in Thailand |
title_sort | low parasite connectivity among three malaria hotspots in thailand |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640040/ https://www.ncbi.nlm.nih.gov/pubmed/34857842 http://dx.doi.org/10.1038/s41598-021-02746-6 |
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