Modeling Human Movements with Cell Phone Calling Records for Public Health Research

Authors: Xiaobai Yao*, University Of Georgia, Christopher Whalen, University of Georgia
Topics: Geographic Information Science and Systems, Transportation Geography
Keywords: Human Movements, Geospatial Big Data, Social Media Data, Infectious Disease
Session Type: Paper
Day: 4/11/2018
Start / End Time: 8:00 AM / 9:40 AM
Room: Oakley, Sheraton, 4th Floor
Presentation File: No File Uploaded

The availability of big data has enabled a plethora of innovative approaches to studying human movements. The study explores the use of location-based social media data, mobile phone calling records specifically in this case, to reconstruct human movements. The analysis results of human mobility were then used to study the impact of human interactions on the spread of an infectious disease. In this study, mobile phone activity records were obtained from mobile service providers in Kampala, Ugandan. Personal identifiable information were removed before the data were released to us. For data analysis, the major steps include (1) preprocess the calling records, georeferenced and timestamp each mobile phone calling activity, (2) construct a social network among the cellphone users (represented by arbitrarily assigned IDs), (3) identify individual movement trajectories and aggregate them to form spatial interaction flows between TSAs, and (4) analyze the spatial pattern of movements in the city, identify connections between such spatio-temporal patterns and risk of disease transmission of the infectious disease under study. The research demonstrates the feasibility to use such mobility information for the improvement of preventive disease control efforts. It further proves that location-based social media data can provide more opportunities to enhance the applicability of geospatial technology in public health research.

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