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Author Notes:

Correspondence: Gonzalo M. Vazquez-Prokopec, E-mail: gmvazqu@emory.edu

Authors' Contributions: Conceived and designed the experiments: GVP, UK, TWS, AM, VPS, SS, JE and TK.

Performed the experiments: GVP, DB, SS, VPS and JRP.

Analyzed the data: GVP, DB, JRP, SS and VPS.

Contributed reagents/materials/analysis tools: EH and TK.

Wrote the paper: GVP, DB, UK, TWS, VPS, JE and AM.

Acknowledgments: We would like to thank the residents of Iquitos for their support and participation in this study.

We thank our Peruvian field team (Helvio Astete Vega, Wilder Carrasco Huamán, Esther Jennifer Ríos López, Shirley Maribel Guédez Gonzales, Wendy Lorena Quiroz Flores, Diana Bazaán Ferrando, and Gabriela Vásquez La Torre) and data management personnel (Jimmy Espinosa Benavides, Angelo Mitidieri, Rommel Vasquez Alves and Alan Lozano).

Disclosures: This study counted with the approval of the Loreto Regional Health Department.

Copyright statement: authors Eric S. Halsey and Tadeusz Kochel are U.S. military service members.

This work was prepared as part of their official duties. Title 17 U.S.C. § 105 provides that ‘Copyright protection under this title is not available for any work of the United States Government’; Title 17 U.S.C. § 101 defines a U.S. Government work as a work prepared by a military service members or employees of the U.S. Government as part of those persons’ official duties.

The authors have declared that no competing interests exist.


Research Funding:

This research was funded by a grant from the U.S. National Institutes of Health – National Institute of Allergy and Infectious Diseases (NIH/NIAID) award number R01 AI069341-01 (to TWS).

Development of the ideas presented here was assisted by support from the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science and Technology Directorate, U.S. Department of Homeland Security, and the Fogarty International Center, National Institutes of Health.

Using GPS Technology to Quantify Human Mobility, Dynamic Contacts and Infectious Disease Dynamics in a Resource-Poor Urban Environment

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Journal Title:



Volume 8, Number 4


, Pages e58802-e58802

Type of Work:

Article | Final Publisher PDF


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.

Copyright information:

© 2013 Vazquez-Prokopec et al.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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