Community network driven COVID-19 testing of vulnerable populations in the Central US

社区网络驱动的美国中部弱势群体 COVID-19 测试

基本信息

  • 批准号:
    10274013
  • 负责人:
  • 金额:
    $ 123.03万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-07-15 至 2024-03-31
  • 项目状态:
    已结题

项目摘要

This C3 project, Community network-driven COVID-19 testing of vulnerable populations in the Central US, will implement and evaluate a COVID-19 testing approach that combines an evidence-based Social Network Testing Strategy (SNS) with community developed COVID-19 public health messages (SNS+). C3 will engage two disenfranchised populations across rural and urban sites in states across the Central US (TX, LA, AR, IN, IL). C3 leverages NIDA's Justice Community Opioid Innovation Network (JCOIN), the PIs' extensive community located COVID-19 testing programs, and a network of established community partnerships. The collaborative community-academic partnerships, research and engagement infrastructure, and team's leadership across JCOIN will ensure that C3 can rapidly recruit, enroll and test most disenfranchised community members, (n=2400) and through this process, accelerate any forthcoming COVID-19 public health prevention interventions. C3 focuses on two communities most impacted by COVID-19: 1) Criminal justice involved (CJI) - non-incarcerated people with previous history of arrest/jail/prison, probation/parole and drug- court attendance; and 2) Low-income Latinx - community members at 250% or below Federal Poverty Level. Both of these diverse populations, and the overlap between them, have some of the highest rates of COVID-19 infection and death in the United States. Messaging that affirms individual agency and corrects misinformation, combined with accessible and acceptable testing, is required to accelerate COVID-19 prevention for these populations. We use contextually adapted and theory-driven messages – misinformation correction and self- affirmation – to increase awareness, self-efficacy and community engagement in our adapted testing strategy – the Social Network testing Strategy (SNS). SNS is an evidence-based testing intervention that has been widely used in multiple settings with marginalized individuals (ie substance-users) who facilitate the recruitment of their social contacts into testing services. SNS combined with theory-driven, contextually appropriate COVID- 19 messaging (SNS+) will address challenges to current COVID-19 testing strategies which are limited by misinformation, stigma, distrust, and limited affirmation of ability to prevent COVID-19. C3 in partnership with community will: Develop COVID-19 messages that emphasize self-affirmation and misinformation correction for implementation in SNS; Test the efficacy (number of network members COVID-19 tested) of a combined SNS-messaging (SNS+) intervention versus standard SNS using adaptive randomization; and Evaluate C3 implementation strategies and key implementation outcomes (ie cost) using the RE-AIM framework. The disenfranchised populations to be engaged in C3 reflect those most impacted by COVID-19 and least able to adopt COVID-19 prevention practices. C3 is “shovel-ready” for implementation in the short timeframe of the RADx-UP mechanism, with significant institutional commitments and community support, to ensure the procedures and interventions are tailored, feasible, acceptable and effective for at-risk communities.
这个 C3 项目是社区网络驱动的中部地区弱势群体的 COVID-19 测试 美国将实施和评估一种新冠病毒 (COVID-19) 测试方法,该方法结合了基于证据的社会 网络测试策略 (SNS) 与社区制定的 COVID-19 公共卫生消息 (SNS+)。 C3将 让美国中部各州(德克萨斯州、洛杉矶、 阿肯色州、印第安纳州、伊利诺伊州)。 C3 利用 NIDA 的司法社区阿片类药物创新网络 (JCOIN)、PI 广泛的 位于社区的 COVID-19 检测项目以及已建立的社区合作伙伴网络。这 社区学术合作伙伴关系、研究和参与基础设施以及团队的 JCOIN 的领导力将确保 C3 能够快速招募、注册和测试大多数被剥夺权利的人 社区成员 (n=2400),并通过这一过程,加速任何即将到来的 COVID-19 公共卫生 预防干预措施。 C3 重点关注受 COVID-19 影响最严重的两个社区:1) 刑事司法 涉案人员 (CJI) - 有逮捕/入狱/监禁、缓刑/假释和吸毒历史的非监禁人员 - 出庭; 2) 低收入拉丁裔 - 联邦贫困线 250% 或以下的社区成员。 这两个不同的人群以及它们之间的重叠部分都是 COVID-19 发病率最高的人群 美国的感染和死亡。确认个人机构并纠正错误信息的消息, 需要结合可及且可接受的测试来加速对这些人的 COVID-19 预防 人口。我们使用根据情境调整和理论驱动的信息——错误信息纠正和自我纠正 肯定——提高我们调整后的测试策略的意识、自我效能和社区参与度—— 社交网络测试策略(SNS)。 SNS 是一种基于证据的测试干预措施,已被广泛应用 在多种环境中与边缘化个人(即物质使用者)一起使用,以促进招募 他们的社会联系进入了测试服务。 SNS 与理论驱动、适合情境的新冠肺炎 (COVID-19) 相结合 19 消息传递 (SNS+) 将解决当前 COVID-19 测试策略的挑战,这些策略受到以下因素的限制: 错误信息、污名、不信任以及对预防 COVID-19 能力的有限肯定。 C3 与合作伙伴 社区将: 制定强调自我肯定和错误信息纠正的 COVID-19 信息 用于在 SNS 中实施;测试组合的功效(测试的 COVID-19 网络成员数量) SNS 消息传递 (SNS+) 干预与使用自适应随机化的标准 SNS 的比较;并评估C3 使用 RE-AIM 框架的实施策略和关键实施成果(即成本)。这 参与 C3 的被剥夺权利的人群反映了受 COVID-19 影响最严重且最无力参与的人群 采取 COVID-19 预防措施。 C3 已“准备好”在短时间内实施 RADx-UP 机制,具有重大的机构承诺和社区支持,以确保 程序和干预措施是针对高危社区量身定制的、可行的、可接受的和有效的。

项目成果

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HAROLD Alexander POLLACK其他文献

HAROLD Alexander POLLACK的其他文献

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{{ truncateString('HAROLD Alexander POLLACK', 18)}}的其他基金

Alternate Emergency Over Dose Response in Chicago
芝加哥的替代紧急剂量反应
  • 批准号:
    10618266
  • 财政年份:
    2022
  • 资助金额:
    $ 123.03万
  • 项目类别:
Alternate Emergency Over Dose Response in Chicago
芝加哥的替代紧急剂量反应
  • 批准号:
    10425012
  • 财政年份:
    2022
  • 资助金额:
    $ 123.03万
  • 项目类别:
Predictive Analytics Applied to Integrated Administrative Emergency Response Datasets in Chicago - Resubmission 01
预测分析应用于芝加哥综合行政应急响应数据集 - 重新提交 01
  • 批准号:
    10200643
  • 财政年份:
    2019
  • 资助金额:
    $ 123.03万
  • 项目类别:
Reducing Opioid Mortality in Illinois (ROMI)
降低伊利诺伊州阿片类药物死亡率 (ROMI)
  • 批准号:
    10671066
  • 财政年份:
    2019
  • 资助金额:
    $ 123.03万
  • 项目类别:
Reducing Opioid Mortality in Illinois (ROMI)
降低伊利诺伊州阿片类药物死亡率 (ROMI)
  • 批准号:
    10402783
  • 财政年份:
    2019
  • 资助金额:
    $ 123.03万
  • 项目类别:
Predictive Analytics Applied to Integrated Administrative Emergency Response Datasets in Chicago - Resubmission 01
预测分析应用于芝加哥综合行政应急响应数据集 - 重新提交 01
  • 批准号:
    9981836
  • 财政年份:
    2019
  • 资助金额:
    $ 123.03万
  • 项目类别:
Reducing Opioid Mortality in Illinois (ROMI)
降低伊利诺伊州阿片类药物死亡率 (ROMI)
  • 批准号:
    9978033
  • 财政年份:
    2019
  • 资助金额:
    $ 123.03万
  • 项目类别:
Project 2: BAM
项目2:营商事工
  • 批准号:
    8741896
  • 财政年份:
    2014
  • 资助金额:
    $ 123.03万
  • 项目类别:
Project 2: BAM
项目2:BAM
  • 批准号:
    9099542
  • 财政年份:
  • 资助金额:
    $ 123.03万
  • 项目类别:
Project 2: BAM
项目2:BAM
  • 批准号:
    8895087
  • 财政年份:
  • 资助金额:
    $ 123.03万
  • 项目类别:

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新手如何编写代码:发现最佳实践以及如何采用它们
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