title: Using GPS technology to quantify human mobility, dynamic contacts and infectious disease dynamics in a resource-poor urban environment.
abstract: Empiric quantification of human mobility patterns is paramount for better urban planning, understanding social network structure and responding to infectious disease threats, especially in light of rapid growth in urbanization and globalization. This need is of particular relevance for developing countries, since they host the majority of the global urban population and are disproportionally affected by the burden of disease. We used Global Positioning System (GPS) data-loggers to track the fine-scale (within city) mobility patterns of 582 residents from two neighborhoods from the city of Iquitos, Peru. We used ∼2.3 million GPS data-points to quantify age-specific mobility parameters and dynamic co-location networks among all tracked individuals. Geographic space significantly affected human mobility, giving rise to highly local mobility kernels. Most (∼80%) movements occurred within 1 km of an individual's home. Potential hourly contacts among individuals were highly irregular and temporally unstructured. Only up to 38% of the tracked participants showed a regular and predictable mobility routine, a sharp contrast to the situation in the developed world. As a case study, we quantified the impact of spatially and temporally unstructured routines on the dynamics of transmission of an influenza-like pathogen within an Iquitos neighborhood. Temporally unstructured daily routines (e.g., not dominated by a single location, such as a workplace, where an individual repeatedly spent significant amount of time) increased an epidemic's final size and effective reproduction number by 20% in comparison to scenarios modeling temporally structured contacts. Our findings provide a mechanistic description of the basic rules that shape human mobility within a resource-poor urban center, and contribute to the understanding of the role of fine-scale patterns of individual movement and co-location in infectious disease dynamics. More generally, this study emphasizes the need for careful consideration of human social interactions when designing infectious disease mitigation strategies, particularly within resource-poor urban environments.
authors.affiliation: Department of Environmental Studies, Emory University, Atlanta, Georgia, USA. gmvazqu@emory.edu
authors.forename: Gonzalo M
authors.initials: GM
authors.lastname: Vazquez-Prokopec
authors.forename: Donal
authors.initials: D
authors.lastname: Bisanzio
authors.forename: Steven T
authors.initials: ST
authors.lastname: Stoddard
authors.forename: Valerie
authors.initials: V
authors.lastname: Paz-Soldan
authors.forename: Amy C
authors.initials: AC
authors.lastname: Morrison
authors.forename: John P
authors.initials: JP
authors.lastname: Elder
authors.forename: Jhon
authors.initials: J
authors.lastname: Ramirez-Paredes
authors.forename: Eric S
authors.initials: ES
authors.lastname: Halsey
authors.forename: Tadeusz J
authors.initials: TJ
authors.lastname: Kochel
authors.forename: Thomas W
authors.initials: TW
authors.lastname: Scott
authors.forename: Uriel
authors.initials: U
authors.lastname: Kitron
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D002947:Cities; D003141:Communicable Diseases / Q000635:transmission*; D005260:Female; D040362:Geographic Information Systems; D006295:Health Resources / Q000600:supply & distribution*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009068:Movement; D012111:Residence Characteristics; D062211:Spatio-Temporal Analysis; D055815:Young Adult