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What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of Mobility

Kathryn L. SchaberDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;

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Tamaki KobayashiDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;

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Marisa HastDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;

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Kelly M. SearleDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota;

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Timothy M. ShieldsDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;

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Harry HamapumbuMacha Research Trust, Choma District, Zambia;

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Jailos LubindaTelethon Kids Institute, Malaria Atlas Project, Nedlands, Australia;

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Philip E. ThumaDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;

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James LupiyaThe Tropical Diseases Research Centre, Ndola, Zambia;

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Mike ChapondaThe Tropical Diseases Research Centre, Ndola, Zambia;

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Shungu MunyatiBiomedical Research and Training Institute, Harare, Zimbabwe;

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Lovemore GwanzuraBiomedical Research and Training Institute, Harare, Zimbabwe;
College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe;

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Sungano MharakurwaBiomedical Research and Training Institute, Harare, Zimbabwe;
College of Health, Agriculture and Natural Sciences, Africa University, Mutare, Zimbabwe;

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William J. MossDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland

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Amy WesolowskiDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;

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on behalf of Southern and Central Africa International Center for Excellence in Malaria Research
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ABSTRACT.

Human movement drives spatial transmission patterns of infectious diseases. Population-level mobility patterns are often quantified using aggregated data sets, such as census migration surveys or mobile phone data. These data are often unable to quantify individual-level travel patterns and lack the information needed to discern how mobility varies by demographic groups. Individual-level datasets can capture additional, more precise, aspects of mobility that may impact disease risk or transmission patterns and determine how mobility differs across cohorts; however, these data are rare, particularly in locations such as sub-Saharan Africa. Using detailed GPS logger data collected from three sites in southern Africa, we explore metrics of mobility such as percent time spent outside home, number of locations visited, distance of locations, and time spent at locations to determine whether they vary by demographic, geographic, or temporal factors. We further create a composite mobility score to identify how well aggregated summary measures would capture the full extent of mobility patterns. Although sites had significant differences in all mobility metrics, no site had the highest mobility for every metric, a distinction that was not captured by the composite mobility score. Further, the effects of sex, age, and season on mobility were all dependent on site. No factor significantly influenced the number of trips to locations, a common way to aggregate datasets. When collecting and analyzing human mobility data, it is difficult to account for all the nuances; however, these analyses can help determine which metrics are most helpful and what underlying differences may be present.

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Author Notes

Address correspondence to Kathryn L. Schaber, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, E6008, Baltimore, MD 21205. E-mail: kathrynschaber@gmail.com

Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Financial support: This work was supported by funds from the National Institutes of Health awarded to the Southern and Central Africa International Centers of Excellence in Malaria Research (U19AI089680), the Bloomberg Philanthropies, and the Johns Hopkins Malaria Research Institute. K. L. S. and A. W. are supported by the U.S. National Institutes of Health through the National Library of Medicine (DP2LM013102). A. W. is also supported by the National Institute of Allergy and Infectious Diseases (1R01A1160780-01) and a Career Award at the Scientific Interface from the Burroughs Welcome Fund.

Authors’ addresses: Kathryn L. Schaber, Tamaki Kobayashi, Marisa Hast, Timothy M. Shields, and Amy Wesolowski, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, E-mails: kathrynschaber@gmail.com, tkobaya2@jhu.edu, marisahast@gmail.com, tshields@jhu.edu, and awesolowski@jhu.edu. Kelly M. Searle, Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, E-mail: ksearle@umn.edu. Harry Hamapumbu, Macha Research Trust, Choma District, Zambia, E-mail: harry.hamapumbu@macharesearch.org. Jailos Lubinda, Telethon Kids Institute, Malaria Atlas Project, Nedlands, Australia, E-mail: jailos.lubinda@telethonkids.org.au. Philip E. Thurma, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD and Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, E-mail: phil.thuma@macharesearch.org. James Lupiya and Mike Chaponda, The Tropical Diseases Research Centre, Ndola, Zambia, E-mails: jamlupiya@gmail.com and mikechaponda@yahoo.com. Shungu Munyati, Biomedical Research and Training Institute, Harare, Zimbabwe, E-mail: smunyati@brti.co.zw. Lovemore Gwanzura, Sungano Mharakurwa, Biomedical Research and Training Institute, Harare, Zimbabwe, and College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe, E-mails: gwanzura@mweb.co.zw and mharakurwas@africau.edu. William J. Moss, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; and Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, E-mail: wmoss1@jhu.edu.

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