Introduction This article proposes a novel method for matching places based on visual similarity, using high-resolution satellite imagery and machine learning. This approach strengthens comparisons when the built environment is a potential confounder, as in many injury research studies.
Methods As an example, I apply this method to study the spatial influence of alcohol outlets (AOs) on firearm violence in Philadelphia, Pennsylvania, specifically beer stores and bar/restaurants. Using a case–control framework, city blocks with shootings in 2017–2018 were matched with similar-looking blocks with no shootings, based on analysis with a pretrained convolutional neural network and t-distributed stochastic neighbour embedding. Logistic regression was used to estimate the OR of a shooting on the same block as an AO and within one-block and two-block distances, conditional on additional factors such as land use, demographic composition and illegal drug activity.
Results The case–control matches were similar in visual appearance, on human inspection, and were well balanced on covariate measures. The fully adjusted model estimated an increased shootings risk for locations with beer stores within one block, OR=1.5, 95% CI 1.1 to 2.1, p=0.02, and locations with bar/restaurants on the same block, OR=1.6, 95% CI 1.1 to 2.4, p=0.02.
Conclusion These findings align with previous study findings while addressing the concern that AOs might systematically be located in certain kinds of environments, providing stronger evidence of a causal effect on nearby firearm violence. Matching on visual similarity can improve observational injury studies involving place-based risks.
- Case-Control Study
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Contributors JJ conceived the project, conducted the analyses and drafted the manuscript.
Funding This work has been supported by the Firearm-safety Among Children and Teens Consortium (NICHD 1R24HD087149-01A1).
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval This article does not contain any studies with human participants or animals. The Harvard T.H. Chan School of Public Health institutional review board waived review of this study as non-human subjects research.
Provenance and peer review Not commissioned; externally peer reviewed.
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