Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

Leedale, Joseph ORCID: 0000-0001-9010-4126, Tompkins, Adrian M, Caminade, Cyril ORCID: 0000-0002-3846-7082, Jones, Anne E, Nikulin, Grigory and Morse, Andrew P ORCID: 0000-0002-0413-2065 (2016) Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty. GEOSPATIAL HEALTH, 11 (1 Supp). pp. 102-114.

	Text Projecting_malaria_hazard_GEOSPAT_Leedale_et_al_EDITED.docx - Unspecified Download (8MB)
	Text Leedale_etal_Malaria_CliCh_Geospat_health_393-1575-2-PB.pdf - Published version Download (2MB)

Abstract

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

Item Type:	Article
Uncontrolled Keywords:	Malaria, Climate change, Vector-borne disease, Climate model ensemble, Eastern Africa
Depositing User:	Symplectic Admin
Date Deposited:	17 Mar 2017 11:55
Last Modified:	19 Jan 2023 07:09
DOI:	10.4081/gh.2016.393
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3006469

Available Versions of this Item

• Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty. (deposited 19 Apr 2016 09:51)
  • Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty. (deposited 17 Mar 2017 11:55) [Currently Displayed]