Eric Reinhart (
Daniel L. Chen is a director of research at the Centre National de la Recherche Scientifique (CNRS), in Paris, France; a professor at the Toulouse School of Economics and Université de Toulouse Faculty of Law, in Toulouse, France; and lead principal investigator of the DE JURE (Data and Evidence for Justice Reform) Program at the World Bank in Washington, D.C.
Health Aff (Millwood). 2020 Aug;39(8):1412-1418. doi: 10.1377/hlthaff.2020.00652. Epub 2020 Jun 4.
Jails and prisons are major sites of novel coronavirus (SARS-CoV-2) infection. Many jurisdictions in the United States have therefore accelerated the release of low-risk offenders. Early release, however, does not address how arrest and pretrial detention practices may be contributing to disease spread. Using data from Cook County Jail-one of the largest known nodes of SARS-CoV-2 spread in the United States-in Chicago, Illinois, we analyzed the relationship between jailing practices and community infections at the ZIP code level. We found that jail-community cycling was a significant predictor of cases of coronavirus disease 2019 (COVID-19), accounting for 55 percent of the variance in case rates across ZIP codes in Chicago and 37 percent of the variance in all of Illinois. Jail-community cycling far exceeds race, poverty, public transit use, and population density as a predictor of variance. The data suggest that cycling people through Cook County Jail alone is associated with 15.7 percent of all documented COVID-19 cases in Illinois and 15.9 percent of all documented cases in Chicago as of April 19, 2020. Our findings support arguments for reduced reliance on incarceration and for related justice reforms both as emergency measures during the present pandemic and as sustained structural changes vital for future pandemic preparedness and public health.
监狱是新型冠状病毒(SARS-CoV-2)感染的主要场所。因此,美国许多司法管辖区已加速释放低风险罪犯。然而,提前释放并不能解决逮捕和审前拘留做法如何助长疾病传播的问题。我们使用来自伊利诺伊州芝加哥市库克县监狱的数据(这是美国已知的 SARS-CoV-2 传播的最大节点之一),在邮政编码级别上分析了监禁做法与社区感染之间的关系。我们发现,监狱-社区循环是冠状病毒病 2019(COVID-19)病例的重要预测因素,占芝加哥所有邮政编码病例率差异的 55%,占伊利诺伊州所有邮政编码病例率差异的 37%。与种族、贫困、公共交通使用和人口密度相比,监狱-社区循环是一个更好的预测因素。数据表明,截至 2020 年 4 月 19 日,仅通过库克县监狱循环人员就与伊利诺伊州记录的所有 COVID-19 病例的 15.7%和芝加哥记录的所有病例的 15.9%有关。我们的研究结果支持减少监禁的依赖,并支持相关司法改革,这既是当前大流行期间的紧急措施,也是未来大流行防范和公共卫生的重要结构性变化。