J Med Internet Res. 2021 Dec 21. doi: 10.2196/24787. Online ahead of print.
ABSTRACT
BACKGROUND: Innovative surveillance methods are needed to assess adherence to COVID-19 social distancing and stay-at-home order/self-quarantine recommendations, especially methods that can provide near real-time and/or highly geographically targeted data. Use of location-based social media image data is one possible approach that could be explored to address this problem.
OBJECTIVE: We sought to evaluate whether publicly-available near real-time social media images might be used to monitor COVID-19 health policy adherence.
METHODS: We collected a sample of 43,487 Instagram images in New York from February 7 to April 11, 2020 from the following location hashtags: #Centralpark (N = 20,937); #Brooklyn Bridge (N = 14,875); and #Timesquare (N = 7,675). After manually reviewing images for accuracy, we counted and recorded the frequency of valid daily posts at each of these hashtag locations over time, as well as rated and counted whether the individuals in the pictures at these location hashtags were social distancing (i.e., whether the individuals in the images appeared to be distanced from others versus next to or touching each other). We analyzed the number of images posted over time and the correlation between trends among hashtag locations.
RESULTS: We found a statistically significant decline in the number of posts over time across all regions, with an approximate decline of 17% across each site (p< .001). We found a positive correlation between hashtags (#Centralpark,#Brooklynbridge; r=.40), (#BrooklynBridge,#Timesquare; r=.41), (#Timesquare,#Centralpark; r=.33; p< .001 for all correlations). The logistic regression analysis showed a mild statistically significant increase in the proportion of posts over time with people appearing to be social distancing at Times Square (p<.05) and Brooklyn Bridge (p < .05), but not for Central Park.
CONCLUSIONS: Results suggest the potential of using location-based social media image data as a method for surveillance of COVID-19 health policy adherence. Future studies should further explore the implementation and ethical issues associated with this approach.
PMID:34995205 | DOI:10.2196/24787
