A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities

项目概要/摘要 纽约市（NYC）是SARS-CoV 2/COVID-19大流行的全球震中，有223，000例病例 超过两万五千人死亡纽约市病例和死亡人数的社区水平差异可以解释为 社会经济和种族/民族特征，其中拉丁裔和黑人纽约人和那些生活在高 贫困社区检测呈阳性的可能性是其他社区的1.5倍，因此死亡的可能性是其他社区的两倍多。 COVID-19莫特黑文社区位于南布朗克斯-最贫穷的国会议员之一 在美国大陆的地区。莫特港是高度多样化（73%是拉丁裔和24%是黑人）， 而且新冠肺炎死亡率高于整个纽约市--震中中的震中。然而， 尽管莫特港显然是COVID相关预防、检测、疫苗接种的优先社区， 治疗措施，到目前为止，只有不到2%的居民接受了测试。 COVID-19的二次发病率在家庭中最高，介于12 - 38%之间。这导致我们 提议对莫特港的公共住房家庭进行COVID-19检测和缓解干预，这些家庭是 其特点是拥挤，代际共同居住，低工资的高比例“必不可少的 即使在封锁期间也要离开家去工作的工人。我们将评估 创新的护士-社区卫生工作者（CHW）-家庭伙伴关系干预措施，旨在促进 COVID-19检测的接受情况、COVID-19控制措施的采用情况和家庭互助能力 水平我们的干预措施改编自护士-家庭伙伴关系模式，已被证明是 在改善高度贫困、种族歧视和仇外心理国家的孕产妇和儿童健康成果方面， 种族多样的社区。社区卫生工作者将为家庭提供文化上适当的支持， 耻辱，医疗不信任和其他参与医疗保健的常见障碍。 我们提出了一个2臂随机对照试验，其中270个家庭（810个人）将 随机分配（2：1）到将接受护士-CHW-家庭的实验组 伙伴关系干预和提供家庭检测和流感疫苗接种，或照常治疗 对照组指免费测试和流感疫苗接种地点在步行距离内。参与人 将在基线时和每月进行一次评估，持续12个月。 这项研究的结果将为当前和未来的公共卫生举措提供证据基础 与其他高风险环境中的COVID-19缓解相关。可持续性将通过建立当地 参与者、CHW和CAB成员的能力和专业知识，并与他们合作， 社区应对COVID-19的最佳实践。如果它被证明是有效的，我们的干预措施可以有针对性地 在其他脆弱和不利环境中增加检测和其他COVID-19控制措施。

PROJECT SUMMARY/ABSTRACT New York City (NYC) is a global epicenter of the SARS-CoV2/COVID-19 pandemic, with 223,000 cases and more than 25,000 deaths. Neighborhood-level disparities in cases and deaths in NYC can be explained by socioeconomic and racial/ethnic characteristics, where Latinx and Black New Yorkers and those living in high poverty neighborhoods are 1.5 times more likely to test positive and more than twice as likely to die as a result of COVID-19. The community of Mott Haven is located in the South Bronx – one of the poorest congressional districts within the continental United States. Mott Haven is highly diverse (73% are Latinx and 24% are Black), and the COVID-19 mortality rate is higher than NYC as a whole – an epicenter within an epicenter. Yet, although Mott Haven is clearly a priority community for COVID-related prevention, detection, vaccination, and treatment initiatives, so far fewer than 2% of residents have been tested. COVID-19 secondary attack rates are highest in households, varying between 12 – 38%. This led us to propose a COVID-19 testing and mitigation intervention in public housing households in Mott Haven, which are characterized by crowding, intergenerational co-residence, and a high proportion of low wage “essential workers” who leave the home for work even during lockdown periods. We will evaluate the effectiveness of an innovative Nurse-Community Health Worker (CHW)-Family Partnership intervention designed to promote COVID-19 testing uptake, adoption of COVID-19 control measures, and mutual aid capacity at the household level. Our intervention is adapted from the Nurse-Family Partnership model, which has been shown to be effective and cost-effective in improving maternal and child health outcomes in high-poverty, racially- and ethnically-diverse communities. CHWs will provide culturally-appropriate support to families, addressing stigma, medical mistrust, and other common barriers to engagement in healthcare. We propose a 2-arm randomized controlled trial, in which 270 households (810 individuals) will be randomly assigned (2:1) to either the experimental group of families who will receive the Nurse-CHW-Family Partnership intervention and the offer of in-home testing and influenza vaccination, or the treatment-as-usual control group referred to free testing and flu vaccination located within walking distance. Participants in both arms will be assessed at baseline and monthly for 12 months. Findings from this study will provide an evidence-base to inform current and future public health initiatives related to COVID-19 mitigation in other high-risk settings. Sustainability will be addressed by building local capacity and expertise among participants, CHWs and CAB members, and partnering with them to develop the community’s best practices for COVID-19. Should it prove to be effective, our intervention can be tailored to increase testing and other COVID-19 control measures in other settings of vulnerability and disadvantage.