Mapping the Invisible: A Framework for Tracking COVID-19 Spread Among College Students with Google Location Data

Authors

Prajindra Sankar Krishnan, Universiti Tenaga NasionalFollow
Chai Phing Chen, Universiti Tenaga NasionalFollow
Gamal AlKawsi, Universiti Tenaga NasionalFollow
Sieh Kiong Tiong, Universiti Tenaga NasionalFollow
Luiz Fernando Capretz, University of Western OntarioFollow

Document Type

Article

Publication Date

11-23-2013

First Page

Latin American Workshop on Data Fusion (LAFUSION 2023)

URL with Digital Object Identifier

https://doi.org/10.48550/arxiv.2405.07870

Last Page

1

Abstract

The COVID-19 pandemic and the implementation of social distancing policies have rapidly changed people's visiting patterns, as reflected in mobility data that tracks mobility traffic using location trackers on cell phones. However, the frequency and duration of concurrent occupancy at specific locations govern the transmission rather than the number of customers visiting. Therefore, understanding how people interact in different locations is crucial to target policies, inform contact tracing, and prevention strategies. This study proposes an efficient way to reduce the spread of the virus among on-campus university students by developing a self-developed Google History Location Extractor and Indicator software based on real-world human mobility data. The platform enables policymakers and researchers to explore the possibility of future developments in the epidemic's spread and simulate the outcomes of human mobility and epidemic state under different epidemic control policies. It offers functions for determining potential contacts, assessing individual infection risks, and evaluating the effectiveness of on-campus policies. The proposed multi-functional platform facilitates the screening process by more accurately targeting potential virus carriers and aids in making informed decisions on epidemic control policies, ultimately contributing to preventing and managing future outbreaks.

Notes

Latin American Workshop on Data Fusion (LAFUSION 2023), November/2023, pp 1-8, Rio de Janeiro, Brazil, DOI: https://doi.org/10.48550/arxiv.2405.07870

Citation of this paper:

Krishnan P.S., Chen C.P., Alkawsi G., Tiong S.K., Capretz L.F., Mapping the Invisible: A Framework for Tracking COVID-19 Spread among College Students with Google Location Data, Latin America Workshop on Data Fusion (LAFUSION-2023), Rio de Janeiro, Brazil, 8 pages, DOI: https://doi.org/10.48550/arxiv.2405.07870, November 2023.