https://www.sciencedaily.com/releases/2022/06/220629161103.htm

While meaningful legislation requires an understanding of how access to firearms is associated with different outcomes of harm, this knowledge also calls for accurate, highly-resolved data on firearm possession, data that is presently unavailable due to a lack of a comprehensive national firearm ownership registry.

Newly published research from data scientist and firearm proliferation researcher Maurizio Porfiri, Institute Professor at the NYU Tandon School of Engineering, and co-authors Roni Barak Ventura, a post-doctoral researcher at Porfiri's Dynamical Systems Lab, and Manuel Ruiz Marin of the Universidad Politécnica de Cartagena, Spain describe a spatio-temporal model to predict trends in firearm prevalence on a state-by-state level by fusing data from two available proxies -- background checks per capita and suicides committed with a firearm in a given state. The study "A spatiotemporal model of firearm ownership in the United States," in the Cell Press journal Patterns, details how by calibrating their results with yearly survey data, the team determined that the two proxies can be simultaneously considered to draw precise information regarding firearm ownership.