Using GPS-enabled mobile phones to evaluate the associations between human mobility changes and the onset of influenza illness. (February 2022)

• Record Type: Journal Article
• Authors: Eum, Youngseob; Yoo, Eun-Hye
• Is Part Of: Spatial and spatio-temporal epidemiology. Volume 40(2022)
• Publication Date: 2022-02
• Subjects: Mobile phone-based GPS -- Influenza-like symptoms (ILS) -- Mobility metrics -- Time-stratified case-crossover; Epidemiology -- Statistical methods -- Periodicals; Epidemiology -- Periodicals; 614.4072
• DOI: 10.1016/j.sste.2021.100458
• Languages: English
• ISSNs: 1877-5845

Abstract

Abstract: Due to the challenges in data collection, there are few studies examining how individuals' routine mobility patterns change when they experience influenza-like symptoms (ILS). In the present study, we aimed to assess the association between changes in routine mobility and ILS using mobile phone-based GPS traces and self-reported surveys from 1, 155 participants over the 2016–2017 influenza season. We used a set of mobility metrics to capture individuals' routine mobility patterns and matched their weekly ILS survey responses. For a statistical analysis, we used a time-stratified case-crossover analysis and conducted a stratified analysis to examine if such associations are moderated by demographic and socioeconomic factors, such as age, gender, occupational status, neighborhood poverty and education levels, and work type. We found that statistically significant associations existed between reduced routine mobility patterns and the experience of ILS. Results also indicated that the association between reduced mobility and ILS was significant only for female and for participants with high socioeconomic status. Our findings offered an improved understanding of ILS-associated mobility changes at the individual level and suggest the potential of individual mobility data for influenza surveillance. Highlights: We assessed the association between changes in routine mobility and influenza illness. Reduced routine mobility appeared to indicate the onset of influenza illness. The associations were significantly moderated by individual's gender and socioeconomic status. People having influenza-like symptoms do not necessarily seek for medical care. Individual movement data may complement hospital-based influenza surveillance.