Identifying and evaluating prevention strategies for COVID-19 in correctional facilities

识别和评估惩教设施中的 COVID-19 预防策略

• 批准号: 10723881
• 负责人: Margaret Lind
• 金额: $ 12.68万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-04 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10723881
• 关键词: 2019-nCoV; Active Learning; Advisory Committees; Affect; Award; COVID-19; COVID-19 mortality; COVID-19 prevention; COVID-19 risk; COVID-19 test; COVID-19 vaccination; Calibration; Communicable Diseases; Communities; Complex; Connecticut; Contracts; Coupled; Data; Development; Disease; Effectiveness; Epidemiologist; Epidemiology; Evaluation; Funding; Future; Goals; Government; Growth; Hazard Models; Herd Immunity; Hospitalization; Household; Individual; Infection; Infection Control; Intervention; Jail; Knowledge; Left; Mass Screening; Measurable; Measures; Mentors; Methodology; Methods; Modeling; Modification; Nature; Output; Persons; Phase; Policies; Policy Maker; Population; Predisposition; Prevention Measures; Prevention strategy; Prisons; Protocols documentation; Public Health Schools; Research; Respiratory Tract Infections; Risk; Risk Reduction; Role; SARS-CoV-2 infection; SARS-CoV-2 transmission; Scientist; Social Distance; Social Network; Structure; Testing; Time; Training; Training Programs; United States; Vaccinated; Vaccination; Vaccinee; Vaccines; Validation; Variant; Viral; Vulnerable Populations; adaptive intervention; burden of illness; career; combat; community burden; community-level factor; discrete time; disease transmission; disorder control; effectiveness evaluation; effectiveness testing; evidence base; experience; feasibility testing; flexibility; hazard; health disparity; high risk; improved; infection risk; marginalized population; microbial disease; model development; models and simulation; novel; prevent outbreaks; prevention effectiveness; programs; simulation; skills; symptomatic COVID-19; transmission process; treatment effect; unvaccinated

PROJECT SUMMARY Respiratory infections, including SARS-CoV-2, disproportionately affect residents of correctional facilities (jails and prisons). While the Federal Bureau of Prisons and state Departments of Correction (DOCs) implemented numerous prevention strategies including social distancing protocols, vaccination campaigns, and testing programs to mitigate transmission and reduce the disease burden, overarching guidance on COVID-19 prevention within correctional facilities is limited. As a result, DOCs must develop and modify their policies based on existing evidence regarding the effectiveness of COVID-19 prevention strategies within correctional facilities. Unfortunately, the existing evidence base is limited. Specifically, the effectiveness of prevention strategies has principally been estimated in isolation (not in combination with other strategies) and while holding the variant constant. Because of this, DOCs are left with little evidence on how to implement and adapt prevention strategies in combination and under the ever-changing COVID-19 landscape. With the goal of expanding the evidence base for infectious disease prevention strategies within correctional facilities, we will estimate the effects of testing and vaccination on the burden of COVID-19 in both jails and prisons. To do so, we will develop an individual level discrete time hazard (transmission) model of SARS-CoV-2 and test the feasibility and reliability of a cutting-edge statistical causal inference approach as an alternative to transmission modeling (Aims 1 & 2). To examine the effects of testing and vaccination in combination and to identify scenarios when strategies require modification to contain spread and reduce disease burden, we will simulate waves of SARS-CoV-2 in the community and identify the strategy combinations required to prevent outbreaks within facilities using our transmission models (Aim 3). The proposed simulation approach will allow for the simulation of SARS-CoV-2 transmission and disease under known and future, theoretical scenarios. The execution of the proposed aims will strengthen the evidence available to DOCs and other policymakers and could make possible the estimation of indirect treatment effects under a causal framework within complex, nested social networks. In addition, their execution, coupled with the proposed training program comprising coursework, structured mentoring, and experiential learning, will allow Dr. Lind (the candidate) to enrich her knowledge of infectious disease transmission modeling, causal inference methods for treatment effect estimation in the presence of interference, and health disparities and infection control within a highly marginalized population, residents of correctional facilities. The candidate has established an expert mentoring and advisory team led by Dr. Albert Ko at the Epidemiology of Microbial Diseases Department at the Yale School of Public Health to enable this training, guide Dr. Lind's transition to independence during the R00 award phase and support her growth as an independently funded infectious disease epidemiologist.

项目总结 呼吸道感染，包括SARS-CoV-2，对教养所(监狱)居民的影响不成比例 和监狱)。同时，联邦监狱局和州惩教部门(DOCS)实施了 多种预防策略，包括社会距离协议、疫苗接种运动和检测 缓解传播和减轻疾病负担的计划，新冠肺炎的总体指导 惩教机构内的预防是有限的。因此，文档必须根据以下条件开发和修改其策略 关于惩教机构内新冠肺炎预防战略有效性的现有证据。 不幸的是，现有的证据基础是有限的。具体地说，预防战略的有效性有 主要是在孤立(不与其他策略组合)和持有变种的情况下进行估计 常量。正因为如此，医生在如何实施和调整预防策略方面几乎没有证据 结合在一起，并在不断变化的新冠肺炎格局下。目的是扩大证据 在惩教机构内的传染病预防战略基地，我们将评估 对监狱和监狱中新冠肺炎的负担进行检测和接种。要做到这一点，我们将开发一个 SARS-CoV-2个体水平离散时间危险(传播)模型及其可行性和可靠性检验 采用尖端的统计因果推断方法作为传输建模的替代方法(目标1和2)。 检查检测和疫苗接种的组合效果，并在战略需要时确定情景 为了遏制传播和减轻疾病负担，我们将在 社区并确定预防设施内疫情所需的策略组合 传播模型(目标3)。所提出的模拟方法可用于SARS-CoV-2的模拟 已知和未来理论情景下的传播和疾病。拟议目标的执行情况 将加强医生和其他政策制定者可用的证据，并可能使估计成为可能 在复杂、嵌套的社会网络中，在因果框架下评估间接治疗效果。此外，他们的 执行，再加上拟议的培训计划，包括课程作业、结构化指导和 体验式学习将使林德博士(候选人)丰富她对传染病的知识。 在存在干扰的情况下用于治疗效果估计的传输建模、因果推断方法， 以及高度边缘化人群中的健康差距和感染控制，惩教所居民 设施。候选人已经建立了一个专家指导和咨询团队，由阿尔伯特·科博士在 耶鲁大学公共卫生学院微生物病流行病学系启用此培训，指导 林德博士在R00颁奖阶段向独立的过渡，并支持她作为一个独立的 资助传染病流行病学家。

项目成果

Evidence of leaky protection following COVID-19 vaccination and SARS-CoV-2 infection in an incarcerated population.

• DOI: 10.1038/s41467-023-40750-8
• 发表时间: 2023-08-19
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Lind, Margaret L.;Dorion, Murilo;Houde, Amy J.;Lansing, Mary;Lapidus, Sarah;Thomas, Russell;Yildirim, Inci;Omer, Saad B.;Schulz, Wade L.;Andrews, Jason R.;Hitchings, Matt D. T.;Kennedy, Byron S.;Richeson, Robert P.;Cummings, Derek A. T.;Ko, Albert I.
• 通讯作者: Ko, Albert I.