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

基本信息

  • 批准号:
    10723881
  • 负责人:
  • 金额:
    $ 12.68万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 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

项目摘要

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.
项目摘要 包括SARS-CoV-2在内的呼吸道感染对教养所(监狱)居民的影响不成比例 监狱)。虽然联邦监狱管理局和州惩教部(DOC)实施了 许多预防策略,包括社交距离协议、疫苗接种运动和检测 减缓传播和减少疾病负担的计划,对COVID-19的总体指导 惩教设施内的预防工作有限。因此,DOC必须根据 有关惩教设施内COVID-19预防策略有效性的现有证据。 遗憾的是,现有的证据基础有限。具体而言,预防战略的有效性 主要是单独估计(不与其他策略结合),同时保持变量 常数正因为如此,DOC在如何实施和调整预防战略方面几乎没有证据 在不断变化的COVID-19形势下,为了扩大证据 作为惩教设施内传染病预防策略的基础,我们将评估 检测和疫苗接种对监狱和监狱中COVID-19负担的影响。为此,我们将开发一个 建立了SARS-CoV-2个体水平离散时间风险(传播)模型,并验证了模型的可行性和可靠性 一个先进的统计因果推理方法作为替代传输建模(目标1和2)。 检查检测和疫苗接种相结合的效果,并确定战略需要时的情景 修改,以遏制传播和减少疾病负担,我们将模拟波SARS-CoV-2在 社区,并确定所需的战略组合,以防止在设施内使用我们的 传输模型(目标3)。所提出的模拟方法将允许模拟SARS-CoV-2 在已知和未来的理论情景下传播和疾病。实现拟议目标 将加强DOC和其他决策者可获得的证据,并使估计成为可能 在复杂的、嵌套的社交网络中的因果框架下,间接的治疗效果。另外他们 执行,再加上拟议的培训计划,包括课程,结构化的指导, 体验式学习,将使林德博士(候选人),以丰富她的传染病知识 传输建模,在存在干扰的情况下用于治疗效果估计的因果推理方法, 在高度边缘化的人口中, 设施候选人已成立了一个专家指导和咨询团队,由Albert Ko博士领导, 微生物疾病流行病学系在耶鲁大学公共卫生学院,使这一培训,指导 博士林德的过渡到独立在R00奖阶段,并支持她的成长为一个独立的 传染病流行病学家

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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:
  • 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.
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Margaret Lind其他文献

Margaret Lind的其他文献

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{{ truncateString('Margaret Lind', 18)}}的其他基金

Using Big Data to Understand Sepsis in an Immunocompromised Population
使用大数据了解免疫功能低下人群的脓毒症
  • 批准号:
    10064529
  • 财政年份:
    2020
  • 资助金额:
    $ 12.68万
  • 项目类别:

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