Department of Criminal Justice, Temple University, Philadelphia, Pennsylvania, United States of America.
PLoS One. 2022 Feb 23;17(2):e0263777. doi: 10.1371/journal.pone.0263777. eCollection 2022.
This study examines changes in gun violence at the census tract level in Philadelphia, PA before and after the onset of the COVID-19 pandemic. Piecewise generalized linear mixed effects models are used to test the relative impacts of social-structural and demographic factors, police activity, the presence of and proximity to drug markets, and physical incivilities on shooting changes between 2017 and June, 2021. Model results revealed that neighborhood structural characteristics like concentrated disadvantage and racial makeup, as well as proximity to drug markets and police activity were associated with higher shooting rates. Neighborhood drug market activity and police activity significantly predicted changes in shooting rates over time after the onset of COVID-19. This work demonstrates the importance of understanding whether there are unique factors that impact the susceptibility to exogenous shocks like the COVID-19 pandemic. The increasing risk of being in a neighborhood with an active drug market during the pandemic suggests efforts related to disrupting drug organizations, or otherwise curbing violence stemming from drug markets, may go a long way towards quelling citywide increases in gun violence.
本研究考察了 COVID-19 大流行前后宾夕法尼亚州费城普查区层面枪支暴力的变化。分段广义线性混合效应模型用于检验社会结构和人口因素、警察活动、毒品市场的存在和临近程度、以及不文明行为对 2017 年至 2021 年 6 月之间枪击变化的相对影响。模型结果表明，邻里结构特征如集中贫困和种族构成，以及靠近毒品市场和警察活动与更高的枪击率有关。邻里毒品市场活动和警察活动在 COVID-19 大流行后显著预测了枪击率随时间的变化。这项工作表明，了解是否存在独特的因素会影响易感性，如 COVID-19 大流行等外生冲击，这一点很重要。在大流行期间，处于活跃毒品市场的社区面临的风险增加，这表明打击毒品组织或遏制源自毒品市场的暴力行为的努力，可能会在很大程度上遏制全市范围内枪支暴力的增加。
