Quantifying the Impact of Human Mobility on Malaria

Author:

Wesolowski Amy12,Eagle Nathan34,Tatem Andrew J.567,Smith David L.68,Noor Abdisalan M.910,Snow Robert W.910,Buckee Caroline O.411

Affiliation:

1. Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15221, USA.

2. Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15221, USA.

3. College of Computer and Information Science, Northeastern University, Boston, MA 02115, USA.

4. Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA.

5. Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA.

6. Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA.

7. Department of Geography, University of Florida, Gainesville, FL 32610, USA.

8. Department of Epidemiology and Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.

9. Malaria Public Health and Epidemiology Group, Centre of Geographic Medicine, KEMRI–Wellcome Trust–University of Oxford Collaborative Programme, Nairobi, Kenya.

10. Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7LJ, UK.

11. Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA 02115, USA.

Abstract

Mobile Phone “Hot Spots” An obstacle to developing effective national malaria control programs is a lack of understanding of human movements, which are an important component of disease transmission. As mobile phones have become increasingly ubiquitous, it is now possible to collect individual-level, longitudinal data on human movements on a massive scale. Wesolowski et al. (p. 267 ) analyzed mobile phone call data records representing the travel patterns of 15 million mobile phone owners in Kenya over the course of a year. This was combined with a detailed malaria risk map, to estimate malaria parasite movements across the country that could be caused by human movement. This information enabled detailed analysis of parasite sources and sinks between hundreds of local settlements. Estimates were compared with hospital data from Nairobi to show that local pockets of transmission likely occur around the periphery of Nairobi, accounting for locally acquired cases, contrary to the accepted idea that there is no transmission in the capital.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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