Diana Silver

The COVID‐19 pandemic exposed the vulnerabilities of carceral systems as high‐risk environments for disease transmission. In response, jurisdictions across the United States implemented mass decarceration policies aimed at reducing jail populations. This paper investigates such interventions and their optimal planning, leveraging system‐theoretic insights. First, we empirically demonstrate the influence of jail population changes on COVID‐19 infections by applying convergent cross mapping, transfer entropy, and linear regression to real‐world data. We find that the jail population dynamics were associated with the evolution of the pandemic. Building on this empirical finding, we present a compartmental epidemiological model that captures the coupled dynamics of disease spread in jails and their surrounding communities, with fluxes modeled as time‐dependent control inputs. Using optimal control theory, we derive an optimal design for these fluxes to balance public health and public safety. Our findings provide both empirical and model‐informed evidence that mass decarceration was not only a reactive policy choice but also a justifiable intervention for pandemic mitigation. We emphasize that our optimization is carried out within the space of admission and release policies and does not rank decarceration against other public‐health measures.

Introduction: Public opinion on firearm legislation varies, though there is broader agreement on restricting guns in alcohol-serving venues. Methods: This study used a discrete choice experiment with 306 US adults in June 2025 to examine preferences for firearm restrictions across different conditions. Scenarios varied by who would be restricted (felons, currently intoxicated individuals, or those with prior alcohol-related offenses), venue size (small, medium, or large), and annual enforcement costs ranging from $0 to $300. Results: Results show that when no enforcement costs are included, a majority of the respondent sample weighted to voting-eligible Americans (56%-74%, depending on the restricted group and venue size) supports firearm restrictions, with support exceeding 65% for restrictions in large venues. However, introducing a $100 annual cost reduces support: significant majority support remains only for restricting combinations of felons, intoxicated people, or those with alcohol-related convictions and only in large venues. Support patterns differ by demographics: women show the strongest support regardless of political affiliation, Democratic men show moderate support, while Republican men and Independents are least supportive. Gun ownership did not independently affect preferences. Conclusions: While support for firearm restrictions in alcohol-serving venues is widespread, even modest implementation costs significantly reduce public backing.

Background: Ghost guns are untraceable firearms assembled from online parts kits without background checks or waiting periods. Police nationally recovered 17 times more ghost guns in 2023 than 2017, yet the relationship between ghost gun recovery and firearm mortality is understudied. We investigated whether ghost gun recovery rates are significantly associated with subsequent firearm mortality rates across California’s 58 counties from 2014 to 2023. Methods: We obtained yearly county-level data on ghost guns recovered in California from The Trace’s Gun Violence Data Hub, which aggregated data from the California Department of Justice’s October 2024 report California’s Fight Against the Ghost Gun Crisis: Progress and New Challenges. County-level firearm death counts (total, suicide, homicide) were pulled from the Centers for Disease Control and Prevention’s Restricted-Use Vital Statistics Data. Covariates included (1) urbanicity measured using the Rural-Urban Continuum Codes from the U.S. Department of Agriculture and (2) economic/racial segregation assessed by the Index of Concentration at the Extremes for income and race/ethnicity. We employed a hierarchical Bayesian approach to quantify the associations between ghost gun recoveries per capita and total firearm death rates in the following year. Exploratory analyses examined whether urbanicity and economic/racial segregation were significantly related to ghost gun recovery rates from 2014 to 2023. Results: Controlling for urbanicity and economic/racial segregation, spatiotemporal models indicated that for every 20 ghost guns recovered per 100,000 population, there was an associated 5% increase in total firearm death rate (IRR: 1.05, 95% CrI: 1.02-1.08) and a 5% increase in firearm suicide rate (IRR: 1.05, 95% CrI: 1.02-1.09) in the following year. Ghost gun recovery rates were 298% higher in urban versus rural counties (IRR: 3.98, 95% CrI: 2.37-6.94) and increased 113% per 0.25-unit increase in economic/racial segregation score (IRR: 2.13, 95% CrI: 1.11-4.19). Conclusions: This study provides the first empirical evidence examining the relationship between ghost gun recovery rates and subsequent increases in firearm mortality, particularly firearm suicides, across California counties from 2014 to 2023. Practitioners concentrating on suicide prevention efforts should be advised about the threat that ghost guns may present.

Background: Social vulnerability may play a role in social media-involved crime, but few studies have investigated this issue. We investigated associations between social vulnerability and social media-involved violent crimes. Methods: We analyzed 22,801 violent crimes occurring between 2018 and 2023 in Prince George’s County, Maryland. Social media involvement was obtained from crime reports at the Prince George’s County Police Department. Social media application types included social networking, advertising/selling, ridesharing, dating, image/video hosting, mobile payment, instant messaging/Voice over Internet Protocol, and other. We used the Centers for Disease Control and Prevention’s Social Vulnerability Index to assess socioeconomic status (SES), household characteristics, racial and ethnic minority status, housing type and transportation, and overall vulnerability. Modified Poisson models estimated adjusted prevalence ratios (aPRs) among the overall sample and stratified by crime type (assault and homicide, robbery, and sexual offense). Covariates included year and crime type. Results: Relative to high tertile areas, we observed a higher prevalence of social media-involved violent crimes in areas with low SES vulnerability (aPR: 1.82, 95% CI: 1.37-2.43), low housing type and transportation vulnerability (aPR: 1.53, 95% CI: 1.17-2.02), and low overall vulnerability (aPR: 1.63, 95% CI: 1.23-2.17). Low SES vulnerability areas were significantly associated with higher prevalences of social media-involved assaults and homicides (aPR: 1.64, 95% CI: 1.02-2.62), robberies (aPR: 2.00, 95% CI: 1.28-3.12), and sexual offenses (aPR: 2.07, 95% CI: 1.02-4.19) compared to high SES vulnerability areas. Low housing type and transportation vulnerability (vs. high) was significantly associated with a higher prevalence of social media-involved robberies (aPR: 1.54, 95% CI:1.01-2.37). Modified Poisson models also indicated that low overall vulnerability areas had higher prevalences of social media-involved robberies (aPR: 1.71, 95% CI: 1.10-2.67) and sexual offenses (aPR: 2.14, 95% CI: 1.05-4.39) than high overall vulnerability areas. Conclusions: We quantified the prevalence of social media-involved violent crimes across social vulnerability levels. These insights underscore the need for collecting incident-based social media involvement in crime reports among law enforcement agencies across the United States and internationally. Comprehensive data collection at the national and international levels provides the capacity to elucidate the relationships between neighborhoods, social media, and population health.