Modeling Malaria Vector Distribution under Climate Change Scenarios in Kenya

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dc.contributor.author Ngaina, Joshua N.
dc.date.accessioned 2019-02-06T09:28:33Z
dc.date.available 2019-02-06T09:28:33Z
dc.date.issued 2017-12
dc.identifier.citation American Geophysical Union, Fall Meeting 2017, abstract #GC13G-0832 en_US
dc.identifier.uri http://adsabs.harvard.edu/abs/2017AGUFMGC13G0832N
dc.identifier.uri http://repository.seku.ac.ke/handle/123456789/4345
dc.description.abstract Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control strategies for sustaining elimination and preventing reintroduction of malaria. However, in Kenya, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of future climate change on locally dominant Anopheles vectors including Anopheles gambiae, Anopheles arabiensis, Anopheles merus, Anopheles funestus, Anopheles pharoensis and Anopheles nili. Environmental data (Climate, Land cover and elevation) and primary empirical geo-located species-presence data were identified. The principle of maximum entropy (Maxent) was used to model the species' potential distribution area under paleoclimate, current and future climates. The Maxent model was highly accurate with a statistically significant AUC value. Simulation-based estimates suggest that the environmentally suitable area (ESA) for Anopheles gambiae, An. arabiensis, An. funestus and An. pharoensis would increase under all two scenarios for mid-century (2016-2045), but decrease for end century (2071-2100). An increase in ESA of An. Funestus was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios for mid-century. Our findings can be applied in various ways such as the identification of additional localities where Anopheles malaria vectors may already exist, but has not yet been detected and the recognition of localities where it is likely to spread to. Moreover, it will help guide future sampling location decisions, help with the planning of vector control suites nationally and encourage broader research inquiry into vector species niche modeling en_US
dc.language.iso en en_US
dc.publisher American Geophysical Union en_US
dc.subject 1630 Impacts of global change en_US
dc.subject GLOBAL CHANGE en_US
dc.subject 4315 Monitoring en_US
dc.subject forecasting en_US
dc.subject prediction en_US
dc.subject NATURAL HAZARDS en_US
dc.subject 4322 Health impact en_US
dc.subject NATURAL HAZARDS en_US
dc.subject 4323 Human impact en_US
dc.subject NATURAL HAZARDS en_US
dc.title Modeling Malaria Vector Distribution under Climate Change Scenarios in Kenya en_US
dc.type Other en_US


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