‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments
Abstract Background In the Greater Mekong Subregion, case–control studies and national-level analyses have shown an association between malaria transmission and forest activities. The term ‘forest malaria’ hides the diversity of ecosystems in the GMS, which likely do not share a uniform malaria risk...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-09-01
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| Series: | Parasites & Vectors |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13071-023-05915-w |
| _version_ | 1797577808576249856 |
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| author | Eva Legendre Florian Girond Vincent Herbreteau Sokeang Hoeun Stanislas Rebaudet Aung Myint Thu Jade Dean Rae Laurent Lehot Sokhna Dieng Gilles Delmas François Nosten Jean Gaudart Jordi Landier |
| author_facet | Eva Legendre Florian Girond Vincent Herbreteau Sokeang Hoeun Stanislas Rebaudet Aung Myint Thu Jade Dean Rae Laurent Lehot Sokhna Dieng Gilles Delmas François Nosten Jean Gaudart Jordi Landier |
| author_sort | Eva Legendre |
| collection | DOAJ |
| description | Abstract Background In the Greater Mekong Subregion, case–control studies and national-level analyses have shown an association between malaria transmission and forest activities. The term ‘forest malaria’ hides the diversity of ecosystems in the GMS, which likely do not share a uniform malaria risk. To reach malaria elimination goals, it is crucial to document accurately (both spatially and temporally) the influence of environmental factors on malaria to improve resource allocation and policy planning within given areas. The aim of this ecological study is to characterize the association between malaria dynamics and detailed ecological environments determined at village level over a period of several years in Kayin State, Myanmar. Methods We characterized malaria incidence profiles at village scale based on intra- and inter-annual variations in amplitude, seasonality, and trend over 4 years (2016–2020). Environment was described independently of village localization by overlaying a 2-km hexagonal grid over the region. Specifically, hierarchical classification on principal components, using remote sensing data of high spatial resolution, was used to assign a landscape and a climate type to each grid cell. We used conditional inference trees and random forests to study the association between the malaria incidence profile of each village, climate and landscape. Finally, we constructed eco-epidemiological zones to stratify and map malaria risk in the region by summarizing incidence and environment association information. Results We identified a high diversity of landscapes (n = 19) corresponding to a gradient from pristine to highly anthropogenically modified landscapes. Within this diversity of landscapes, only three were associated with malaria-affected profiles. These landscapes were composed of a mosaic of dense and sparse forest fragmented by small agricultural patches. A single climate with moderate rainfall and a temperature range suitable for mosquito presence was also associated with malaria-affected profiles. Based on these environmental associations, we identified three eco-epidemiological zones marked by later persistence of Plasmodium falciparum, high Plasmodium vivax incidence after 2018, or a seasonality pattern in the rainy season. Conclusions The term forest malaria covers a multitude of contexts of malaria persistence, dynamics and populations at risk. Intervention planning and surveillance could benefit from consideration of the diversity of landscapes to focus on those specifically associated with malaria transmission. Graphical Abstract |
| first_indexed | 2024-03-10T22:13:15Z |
| format | Article |
| id | doaj.art-5a09badde4814a8ab46372124335eede |
| institution | Directory Open Access Journal |
| issn | 1756-3305 |
| language | English |
| last_indexed | 2024-03-10T22:13:15Z |
| publishDate | 2023-09-01 |
| publisher | BMC |
| record_format | Article |
| series | Parasites & Vectors |
| spelling | doaj.art-5a09badde4814a8ab46372124335eede2023-11-19T12:31:28ZengBMCParasites & Vectors1756-33052023-09-0116111510.1186/s13071-023-05915-w‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environmentsEva Legendre0Florian Girond1Vincent Herbreteau2Sokeang Hoeun3Stanislas Rebaudet4Aung Myint Thu5Jade Dean Rae6Laurent Lehot7Sokhna Dieng8Gilles Delmas9François Nosten10Jean Gaudart11Jordi Landier12Aix Marseille Univ, IRD, INSERM, SESSTIM, ISSPAMInstitut de Recherche pour le Développement, UMR 228 Espace-Dev (IRD, UA, UG, UM, UR)Institut de Recherche pour le Développement, UMR 228 Espace-Dev (IRD, UA, UG, UM, UR)Institut de Recherche pour le Développement, UMR 228 Espace-Dev (IRD, UA, UG, UM, UR)Aix Marseille Univ, IRD, INSERM, SESSTIM, ISSPAMShoklo Malaria Research Unit, Mahidol Oxford Tropical Medicine Research UnitShoklo Malaria Research Unit, Mahidol Oxford Tropical Medicine Research UnitAix Marseille Univ, IRD, INSERM, SESSTIM, ISSPAMAix Marseille Univ, IRD, INSERM, SESSTIM, ISSPAMShoklo Malaria Research Unit, Mahidol Oxford Tropical Medicine Research UnitShoklo Malaria Research Unit, Mahidol Oxford Tropical Medicine Research UnitAix Marseille Univ, IRD, INSERM, AP-HM, SESSTIM, La Timone Hospital, BioSTIC, Biostatistics and ICTAix Marseille Univ, IRD, INSERM, SESSTIM, ISSPAMAbstract Background In the Greater Mekong Subregion, case–control studies and national-level analyses have shown an association between malaria transmission and forest activities. The term ‘forest malaria’ hides the diversity of ecosystems in the GMS, which likely do not share a uniform malaria risk. To reach malaria elimination goals, it is crucial to document accurately (both spatially and temporally) the influence of environmental factors on malaria to improve resource allocation and policy planning within given areas. The aim of this ecological study is to characterize the association between malaria dynamics and detailed ecological environments determined at village level over a period of several years in Kayin State, Myanmar. Methods We characterized malaria incidence profiles at village scale based on intra- and inter-annual variations in amplitude, seasonality, and trend over 4 years (2016–2020). Environment was described independently of village localization by overlaying a 2-km hexagonal grid over the region. Specifically, hierarchical classification on principal components, using remote sensing data of high spatial resolution, was used to assign a landscape and a climate type to each grid cell. We used conditional inference trees and random forests to study the association between the malaria incidence profile of each village, climate and landscape. Finally, we constructed eco-epidemiological zones to stratify and map malaria risk in the region by summarizing incidence and environment association information. Results We identified a high diversity of landscapes (n = 19) corresponding to a gradient from pristine to highly anthropogenically modified landscapes. Within this diversity of landscapes, only three were associated with malaria-affected profiles. These landscapes were composed of a mosaic of dense and sparse forest fragmented by small agricultural patches. A single climate with moderate rainfall and a temperature range suitable for mosquito presence was also associated with malaria-affected profiles. Based on these environmental associations, we identified three eco-epidemiological zones marked by later persistence of Plasmodium falciparum, high Plasmodium vivax incidence after 2018, or a seasonality pattern in the rainy season. Conclusions The term forest malaria covers a multitude of contexts of malaria persistence, dynamics and populations at risk. Intervention planning and surveillance could benefit from consideration of the diversity of landscapes to focus on those specifically associated with malaria transmission. Graphical Abstracthttps://doi.org/10.1186/s13071-023-05915-wMalariaEnvironmentStratificationMappingEco-epidemiological zonesGreater Mekong Subregion |
| spellingShingle | Eva Legendre Florian Girond Vincent Herbreteau Sokeang Hoeun Stanislas Rebaudet Aung Myint Thu Jade Dean Rae Laurent Lehot Sokhna Dieng Gilles Delmas François Nosten Jean Gaudart Jordi Landier ‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments Parasites & Vectors Malaria Environment Stratification Mapping Eco-epidemiological zones Greater Mekong Subregion |
| title | ‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments |
| title_full | ‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments |
| title_fullStr | ‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments |
| title_full_unstemmed | ‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments |
| title_short | ‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments |
| title_sort | forest malaria in myanmar tracking transmission landscapes in a diversity of environments |
| topic | Malaria Environment Stratification Mapping Eco-epidemiological zones Greater Mekong Subregion |
| url | https://doi.org/10.1186/s13071-023-05915-w |
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