Predictive analysis across spatial scales links zoonotic malaria to deforestation

Brock, P. M. , Fornace, K. M., Grigg, M. J., Anstey, N. M., William, T., Cox, J., Drakeley, C. J., Ferguson, H. M. and Kao, R. R. (2019) Predictive analysis across spatial scales links zoonotic malaria to deforestation. Proceedings of the Royal Society of London Series B: Biological Sciences, 286(1894), 20182351. (doi: 10.1098/rspb.2018.2351) (PMID:30963872) (PMCID:PMC6367187)

[img]
Preview
Text
178049.pdf - Published Version
Available under License Creative Commons Attribution.

969kB

Abstract

The complex transmission ecologies of vector-borne and zoonotic diseases pose challenges to their control, especially in changing landscapes. Human incidence of zoonotic malaria (Plasmodium knowlesi) is associated with deforestation although mechanisms are unknown. Here, a novel application of a method for predicting disease occurrence that combines machine learning and statistics is used to identify the key spatial scales that define the relationship between zoonotic malaria cases and environmental change. Using data from satellite imagery, a case–control study, and a cross-sectional survey, predictive models of household-level occurrence of P. knowlesi were fitted with 16 variables summarized at 11 spatial scales simultaneously. The method identified a strong and well-defined peak of predictive influence of the proportion of cleared land within 1 km of households on P. knowlesi occurrence. Aspect (1 and 2 km), slope (0.5 km) and canopy regrowth (0.5 km) were important at small scales. By contrast, fragmentation of deforested areas influenced P. knowlesi occurrence probability most strongly at large scales (4 and 5 km). The identification of these spatial scales narrows the field of plausible mechanisms that connect land use change and P. knowlesi, allowing for the refinement of disease occurrence predictions and the design of spatially-targeted interventions.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Kao, Professor Rowland and Ferguson, Professor Heather and Brock, Dr Patrick
Authors: Brock, P. M., Fornace, K. M., Grigg, M. J., Anstey, N. M., William, T., Cox, J., Drakeley, C. J., Ferguson, H. M., and Kao, R. R.
College/School:College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
Journal Name:Proceedings of the Royal Society of London Series B: Biological Sciences
Publisher:The Royal Society
ISSN:0962-8452
ISSN (Online):1471-2954
Published Online:16 January 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Proceedings of the Royal Society of London Series B: Biological Sciences 286(1894): 20182351
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
538423Defining the biomedical, environmental and social risk factors for human infection with Plasmodium knowlesi (a.k.a. 'Monkeybar')Heather FergusonMedical Research Council (MRC)G1100796/1RI BIODIVERSITY ANIMAL HEALTH & COMPMED