1. Fogarty International Center, National Institutes of Health, Building 16, 16 Center Drive, Bethesda, Maryland 20892, USA
2. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey 08544, USA
3. Malaria Public Health & Epidemiology Group, Centre for Geographic Medicine, KEMRI (in the grounds of the Kenyatta Hospital), PO Box 43640, 00100 Nairobi GPO, Kenya
4. Centre for Tropical Medicine, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DS, UK
5. TALA Research Group, Tinbergen Building, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK

Correspondence to: D. L. Smith¹ Correspondence and requests for materials should be addressed to D.L.S. (Email: smitdave@helix.nih.gov).

Abstract

Malaria is an important cause of global morbidity and mortality. The fact that some people are bitten more often than others has a large effect on the relationship between risk factors and prevalence of vector-borne diseases^{1, 2, 3}. Here we develop a mathematical framework that allows us to estimate the heterogeneity of infection rates from the relationship between rates of infectious bites and community prevalence. We apply this framework to a large, published data set that combines malaria measurements from more than 90 communities⁴. We find strong evidence that heterogeneous biting or heterogeneous susceptibility to infection are important and pervasive factors determining the prevalence of infection: 20% of people receive 80% of all infections. We also find that individual infections last about six months on average, per infectious bite, and children who clear infections are not immune to new infections. The results have important implications for public health interventions: the success of malaria control will depend heavily on whether efforts are targeted at those who are most at risk of infection.

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