Abstract

Hotspots constitute the major reservoir for residual malaria transmission, with higher malaria incidence than neighbouring areas, and therefore, have the potential to form the cornerstone for successful intervention strategies. Detection of malaria hotspots is hampered by their heterogenous spatial distribution, and the laborious nature and low sensitivity of the current methods used to assess transmission intensity. We adopt ecological theory underlying foraging in herbivorous insects to vector mosquito host seeking and modelling of fine-scale landscape features at the village level. The overall effect of environmental variables on the density of indoor mosquitoes, sporozoite infected mosquitoes, and malaria incidence, was determined using generalized linear models. Spatial analyses were used to identify hotspots for malaria incidence, as well as malaria vector density and associated sporozoite prevalence. We identify household occupancy and location as the main predictors of vector density, entomological inoculation rate and malaria incidence. We propose that the use of conventional vector control and malaria interventions, integrated with their intensified application targeting predicted hotspots, can be used to reduce malaria incidence in endemic and residual malaria settings.

Details

Title
Malaria hotspots explained from the perspective of ecological theory underlying insect foraging
Author
Yared, Debebe 1 ; Hill, Sharon Rose 2 ; Habte, Tekie 1 ; Sisay, Dugassa 3 ; Hopkins, Richard J 4 ; Ignell Rickard 2 

 Addis Ababa University, Department of Zoological Sciences, Addis Ababa, Ethiopia (GRID:grid.7123.7) (ISNI:0000 0001 1250 5688) 
 Swedish University of Agricultural Sciences, Unit of Chemical Ecology, Department of Plant Protection Biology, Alnarp, Sweden (GRID:grid.6341.0) (ISNI:0000 0000 8578 2742) 
 Addis Ababa University, Aklilu Lemma Institute of Pathobiology, Addis Ababa, Ethiopia (GRID:grid.7123.7) (ISNI:0000 0001 1250 5688) 
 University of Greenwich, Natural Resources Institute, London, UK (GRID:grid.36316.31) (ISNI:0000 0001 0806 5472) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2473291611
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.