‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments

dc.contributor.authorLegendre E.
dc.contributor.authorGirond F.
dc.contributor.authorHerbreteau V.
dc.contributor.authorHoeun S.
dc.contributor.authorRebaudet S.
dc.contributor.authorThu A.M.
dc.contributor.authorRae J.D.
dc.contributor.authorLehot L.
dc.contributor.authorDieng S.
dc.contributor.authorDelmas G.
dc.contributor.authorNosten F.
dc.contributor.authorGaudart J.
dc.contributor.authorLandier J.
dc.contributor.otherMahidol University
dc.date.accessioned2023-09-21T18:01:49Z
dc.date.available2023-09-21T18:01:49Z
dc.date.issued2023-12-01
dc.description.abstractBackground: 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: [Figure not available: see fulltext.].
dc.identifier.citationParasites and Vectors Vol.16 No.1 (2023)
dc.identifier.doi10.1186/s13071-023-05915-w
dc.identifier.eissn17563305
dc.identifier.pmid37700295
dc.identifier.scopus2-s2.0-85170708962
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/90087
dc.rights.holderSCOPUS
dc.subjectImmunology and Microbiology
dc.title‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments
dc.typeArticle
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85170708962&origin=inward
oaire.citation.issue1
oaire.citation.titleParasites and Vectors
oaire.citation.volume16
oairecerif.author.affiliationMahidol Oxford Tropical Medicine Research Unit
oairecerif.author.affiliationSciences Economiques et Sociales de la Santé et Traitement de l'Information Médicale
oairecerif.author.affiliationInstitut Pasteur du Cambodge
oairecerif.author.affiliationIRD Institut de Recherche pour le Developpement
oairecerif.author.affiliationNuffield Department of Medicine
oairecerif.author.affiliationHôpital Européen Marseille

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