Mass gatherings as natural experiments: travel pulses reveal determinants of SARS-CoV-2 epidemic synchrony and predictability in U.S. states and counties

大规模集会作为自然实验：旅行脉搏揭示了美国各州和县 SARS-CoV-2 流行病同步性和可预测性的决定因素

• 批准号: 10632138
• 负责人: Pejman Rohani
• 金额: $ 19.02万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10632138
• 关键词: 2019-nCoV; Affect; Age; Attention; Biological Models; COVID-19; COVID-19 pandemic; Case Study; Communities; Complex; Contact Tracing; County; Data; Data Analytics; Demography; Disease; Ecology; Economics; Epidemic; Epidemiology; Evaluation; Event; Florida; Geography; Goals; Health Personnel; Health Resources; Human; Immune; Immunity; Incidence; Individual; Infection; Intervention; Location; Maps; Modeling; Motorcycles; Natural experiment; New York; Physiologic pulse; Policies; Politics; Public Health; Recording of previous events; Regional Disease; Research; Research Personnel; Risk; Rural; Series; Socioeconomic Factors; Statistical Models; Structure; System; Testing; Time; Time trend; Titrations; Travel; Urbanicity; Vaccination; Vaccines; Variant; Work; current pandemic; dynamic system; epidemic preparedness; epidemic response; future epidemic; geographic difference; hospital bed; improved; novel; response; rural counties; skills; social; socioeconomics; suburb; transmission process; trend

Project Summary Variation in epidemic timing and intensity among U.S. communities has exacerbated shortages of vital pub- lic health resources, from testing and contact tracing to hospital beds and health care workers. Understanding when and why communities are most vulnerable to epidemic disease remains a critical unmet need in this and future epidemics. Our study will leverage a set of five mass gatherings (e.g., the Sturgis Motorcycle Ral- lies in 2020 and 2021) to assess the variable impact of travel pulses across a spectrum of U.S. communities. Our study is organized around two principle aims: Aim 1. To quantify how disease incidence in U.S. counties responds to travel pulses from focal mass gatherings in 2020 and then identify predictors of differing responses. To achieve this, we will use statistical models to quantify counties' differing response to travelers as a function of urbanicity, geographic isolation, age structure, and economic status. Aim 2. To quantify how disease predictability and connec- tivity vary among U.S. counties across 2020 and 2021. We will construct and parameterize mechanistic models of county-level transmission, and then assess model forecasting skill over short-term time horizons. This research will provide much-needed national and state summaries detailing which forces most strongly affect disease connectivity and predictability. Our work will provide detailed evaluations of individual counties, including publicly accessible interactive maps illustrating the relative effects of geography, demography, infection history, and vaccination. These products will help stakeholders identify at-risk communities and tailor control efforts to local conditions, and will highlight regions where increased surveillance is warranted.

项目摘要 美国社区之间流行时间和强度的变化加剧了重要酒吧的短缺， 从检测和接触者追踪到医院病床和卫生保健工作者。理解 社区何时以及为何最容易受到流行病的影响仍然是这方面一个关键的未得到满足的需求。 未来的流行病。我们的研究将利用一组五个大规模集会（例如，斯特吉斯摩托车拉力赛 在于2020年和2021年），以评估旅行脉冲在美国社区范围内的可变影响。我们 研究围绕两个主要目标：目标1。为了量化美国各县的疾病发病率如何应对 从2020年的焦点质量聚集中传播脉冲，然后确定不同反应的预测因素。为了实现这一点， 我们将使用统计模型来量化各县对旅行者的不同反应作为城市化的函数， 地理隔离、年龄结构和经济地位。目标2.为了量化疾病的可预测性和连接性- 在2020年和2021年，美国各县的活力各不相同。我们将构建和参数化的机械模型， 县一级的传输，然后评估短期时间范围内的模型预测技能。本研究 将提供急需的国家和州摘要，详细说明哪些力量对疾病影响最大 连通性和可预测性。我们的工作将提供个别县的详细评估，包括 可公开访问的交互式地图，说明地理，人口统计，感染史， 和疫苗接种。这些产品将帮助利益攸关方识别风险社区，并调整控制工作， 并将突出需要加强监测的地区。