The effects of influenza-like symptoms on human mobility patterns in Buffalo metropolitan area, New York, the 2016--2017 influenza season

Authors: Youngseob Eum*, University At Buffalo, Eun-Hye Yoo, University at Buffalo
Topics: Geography and Urban Health, Geographic Information Science and Systems, Medical and Health Geography
Keywords: Mobility patterns, Influenza-like symptoms, Smartphone GPS
Session Type: Paper
Day: 4/4/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Truman, Marriott, Mezzanine Level
Presentation File: No File Uploaded

Although human behavioral response to disease symptoms has implications for modeling spread of infectious disease and public health policy, empirical studies are rare. Influenza is one of the most common diseases in everyday life, causing a significant health burden across the population. This study examined how mobility patterns of individuals change when having symptoms of influenza-like illness such as fever and nausea. We used smartphone-based GPS locations and self-reported symptoms surveys, collected from 1,247 participants in Buffalo metropolitan area, New York, during the entire 2016--2017 influenza season. We identified their time-activity patterns of each individual by applying a density-based spatial clustering algorithm to the GPS data, and quantified individual mobility with a set of metrics from the perspective of activity space. We conducted a case-crossover analysis to estimate the extent of which the change of mobility is associated with influenza-like symptoms while controlling for confounding factors effectively. Results indicated that individuals spent significantly more time at home when having influenza-like symptoms, whereas spending less at pastime locations including residential and commercial areas. Furthermore, the total number of activity places, geographical extent of mobility, and the total travel distance between activity places were negatively associated with influenza-like symptoms. Our findings provide an empirical evidence on the impact of disease symptoms to reduced human mobility, and suggest that ubiquitous smartphone-based GPS data may be useful for public health surveillance by monitoring the significant mobility characteristics of individuals.

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