Leveraging artificial intelligence and social innovation to reduce disparities in COVID-19 testing among African Americans

摘要 大流行疲劳--一种以遵循推荐的保护行为而失去动力为特征的现象 随着时间的推移而出现，并受到一个人的情感、经历和感知的影响--威胁着我们的能力 以结束新冠肺炎大流行。疫苗诱导的免疫力减弱，突破性感染，新的变种，以及 不确定性都加剧了大流行的疲劳感。这些持续不断的挑战突显了维持 新冠肺炎缓解战略，包括新冠肺炎检测，从长远来看，以实现疫情控制。 虽然大流行疲劳是对一场旷日持久的公共卫生危机的预期和自然反应，但它损害了 我们保障服务不足、医疗和/或社会弱势群体成员安全的能力，包括 非裔美国人。鉴于彻底根除或消除这种疾病是不可行的，科学家和公共卫生 官员们正专注于让新冠肺炎成为地方病的控制措施。为了达到地方病的地位，我们必须 在脆弱人群中识别和解决新冠肺炎检测的障碍，包括大流行疲劳。 此外，我们必须推进传播科学干预，使我们能够确定 针对新冠肺炎感知风险的消息展示可以被用来增加动力 新冠肺炎测试行为，并采用有效的沟通策略来缓解暴露的影响 关于测试接受和吸收的错误信息。以能力为导向的机会激励--行为 和少数民族健康和健康差距研究框架，这项研究将利用参与性研究 来自社区参与的持续新冠肺炎缓解的方法、人工智能和基础设施 研究：1)主持设计马拉松，开发深度学习计算机动画，能够传达 年在非裔美国人中测试和促进新冠肺炎在社区环境中的重要性 北卡罗来纳州。2)确定深度学习计算机动画干预(与对照)是否改善新冠肺炎 使用1：1随机实验测试摄取。研究结果将确定有效的新冠肺炎测试 针对有可能推广到其他关键人群的非裔美国人的宣传信息。

Abstract Pandemic fatigue—a phenomenon characterized by a demotivation to follow recommended protective behaviors that emerges over time and is affected by one’s emotions, experiences and perceptions—threatens our ability to end the COVID-19 pandemic. Waning vaccine-induced immunity, breakthrough infections, new variants, and uncertainty all contribute to pandemic fatigue. These ongoing challenges highlight the importance of sustaining COVID-19 mitigation strategies, including COVID-19 testing, over the long run to achieve pandemic control. While pandemic fatigue is an expected and natural response to a prolonged public health crisis, it compromises our ability to keep members of underserved and medically and/or socially vulnerable populations safe, including African Americans. Given that complete eradication or elimination are not feasible, scientists and public health officials are focused on control measures to make COVID-19 endemic. To achieve endemic status, we must identify and address barriers to COVID-19 testing within vulnerable populations, including pandemic fatigue. Moreover, we must advance communication science interventions that enable us to determine how variations in the presentation of messages targeting perceived risk for COVID-19 can be leveraged to increase motivation for COVID-19 testing behaviors, and employ effective communication strategies to mitigate the impact of exposure to misinformation on testing acceptance and uptake. Guided by the Capability Opportunity Motivation—Behavior and Minority Health and Health Disparities Research Frameworks, this study will leverage participatory research methods, artificial intelligence, and infrastructure from ongoing community-engaged COVID-19 mitigation research to: 1) Host a design-a-thon to develop deep learning computer animations capable of conveying the importance of COVID-19 testing and promoting its uptake in community settings among African Americans in NC. 2) Determine whether a deep learning computer animation intervention (vs a control) improves COVID-19 testing uptake using a 1:1 randomized experiment. Study results will identify effective COVID-19 testing promotion messages for African Americans with the potential for generalization to other key populations.