COS 102-4
Fine-scale human movement: theory, data, and implications for dengue virus transmission

Thursday, August 8, 2013: 2:30 PM
L100A, Minneapolis Convention Center
T. Alex Perkins, Research and Policy for Infectious Disease Dynamics Program, Fogarty International Center, NIH
Andres J. Garcia, University of Florida
Gonzalo Vazquez-Prokopec, Emory University, Atlanta, GA
Donal Bisanzio, Emory University
Robert C. Reiner Jr., Entomology, University of California, Davis, Davis, CA
Steven T. Stoddard, Entomology, University of California, Davis, Davis, CA
David L. Smith, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health
Thomas Scott, Department of Entomology, University of California, Davis
Andrew J. Tatem, University of Southampton

From traveling on an airplane to commuting for work to visiting neighbors, human movement plays a major role in the spread of infectious diseases at a variety of scales. Models of fine-scale movement (e.g., within a city) and data to inform them have been lacking for resource-poor areas, which are afflicted by a multitude of diseases and where movement patterns are likely to depart substantially from those in developed temperate areas. Moreover, aspects of movement most relevant to the transmission of a mosquito-borne disease such as dengue fever have received little explicit consideration in existing models. We developed a new model for simulating individual human movement and fit it to interview data collected from 149 residents of the city of Iquitos, Peru. We then simulated city-wide movement networks for Iquitos and compared the properties of those networks to movement networks in other settings. Finally, we applied human movements simulated by our model to a recently developed framework for modeling mosquito-borne disease transmission.


Our model of individual human movement has five distinct components that together describe variation in how individuals allocate their time across a dynamic set of locations: the number of locations visited, what types of locations are visited, where those locations are, and how often and for how long individuals visit each location. Fitting the model to data revealed that movement differs among locations of different types, that distance from home strongly influences where people go and how often and for how long they visit, and that these aspects of movement vary with age and sex. Network properties of simulated movement across the city differ in several ways from comparable movement networks from cities in developed countries, and they are also sensitive to assumptions about secondary network structures not captured by our model; e.g., social relationships. Combining simulated movements with information about spatial variation in mosquito densities and mosquito movement, we show that disease invasion probabilities and threshold criteria for disease persistence change precipitously as fine-scale variation is homogenized at increasingly aggregated scales.