Comparison of alternative models of human movement and the spread of disease

Ottar N. Bjørnstad; Bryan T. Grenfell; Cecile Viboud; Aaron A. King

In this study we have used actual disease incidence data, as opposed to raw 298 measurments of human movement, to further our understanding of the principles 299 governing how human hosts spread ifectious disease across a populated landscape. We 300 have found both strong evidence of higher-order interactions among population centers, 301 and that candidate models differ significantly in their ability to capture the empirical 302 patterns. We hope our findings will help stimulate a systematic, data-driven discussion 303 of the relative merit of alternative predictive models for the probable path for spatial 304 spread of infectious disease. Clearly, the prospects are good for good for further 305 refinements and improved parameterizations. Spatial interaction models predict the flux of human movements between population centers (cities, towns, villages) as a function of the distribution of the population on the landscape. In this diagram, the relative magnitude of the fluxes from a focal town to other population centers are represented by the widths of the arrows. In the widely-employed gravity models (A), interactions among cities is strictly pairwise. Thus the addition of a new town (B) has no effect on the movement to other towns. In Fotheringham's competing destinations model (C), however, competition or synergy among nearby communities can reduce or augment fluxes. Stouffer's model of intervening opportunities and the radiation model (D) posit that movement from one city to another is diminished by the presence of opportunities in communities more proximal to the source city. author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under