Incorporating hydrology into climate suitability models changes projections of malaria transmission in Africa.

Simple item page
dc.citation.issue1
dc.citation.volume11
dc.contributor.authorSmith MW
dc.contributor.authorWillis T
dc.contributor.authorAlfieri L
dc.contributor.authorJames WHM
dc.contributor.authorTrigg MA
dc.contributor.authorYamazaki D
dc.contributor.authorHardy AJ
dc.contributor.authorBisselink B
dc.contributor.authorDe Roo A
dc.contributor.authorMacklin MG
dc.contributor.authorThomas CJ
dc.coverage.spatialEngland
dc.date.accessioned2024-11-11T19:30:45Z
dc.date.available2024-11-11T19:30:45Z
dc.date.issued2020-08-28
dc.description.abstractContinental-scale models of malaria climate suitability typically couple well-established temperature-response models with basic estimates of vector habitat availability using rainfall as a proxy. Here we show that across continental Africa, the estimated geographic range of climatic suitability for malaria transmission is more sensitive to the precipitation threshold than the thermal response curve applied. To address this problem we use downscaled daily climate predictions from seven GCMs to run a continental-scale hydrological model for a process-based representation of mosquito breeding habitat availability. A more complex pattern of malaria suitability emerges as water is routed through drainage networks and river corridors serve as year-round transmission foci. The estimated hydro-climatically suitable area for stable malaria transmission is smaller than previous models suggest and shows only a very small increase in state-of-the-art future climate scenarios. However, bigger geographical shifts are observed than with most rainfall threshold models and the pattern of that shift is very different when using a hydrological model to estimate surface water availability for vector breeding.
dc.description.confidentialfalse
dc.edition.edition2020
dc.format.pagination4353-
dc.identifier.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/32859908
dc.identifier.citationSmith MW, Willis T, Alfieri L, James WHM, Trigg MA, Yamazaki D, Hardy AJ, Bisselink B, De Roo A, Macklin MG, Thomas CJ. (2020). Incorporating hydrology into climate suitability models changes projections of malaria transmission in Africa.. Nat Commun. 11. 1. (pp. 4353-).
dc.identifier.doi10.1038/s41467-020-18239-5
dc.identifier.eissn2041-1723
dc.identifier.elements-typejournal-article
dc.identifier.issn2041-1723
dc.identifier.number4353
dc.identifier.pii10.1038/s41467-020-18239-5
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/71961
dc.languageeng
dc.publisherSpringer Nature Limited
dc.publisher.urihttps://www.nature.com/articles/s41467-020-18239-5
dc.relation.isPartOfNat Commun
dc.rights(c) 2020 The Author/s
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectAfrica
dc.subjectAnimals
dc.subjectAnopheles
dc.subjectClimate Change
dc.subjectEcology
dc.subjectEcosystem
dc.subjectGeographic Mapping
dc.subjectGeography
dc.subjectHydrology
dc.subjectMalaria
dc.subjectMosquito Vectors
dc.subjectRivers
dc.subjectSeasons
dc.subjectTemperature
dc.titleIncorporating hydrology into climate suitability models changes projections of malaria transmission in Africa.
dc.typeJournal article
pubs.elements-id434334
pubs.organisational-groupCollege of Health
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