RFA-DP-23-001, Simulation Model of Interventions Linking Evidence to SDOH (SMILES)

项目摘要/摘要 支持疾病控制和预防中心(CDC)以及各州和社区确定 可缩小慢性病发病率不断扩大的差距的计划、政策或实践(PPP) 和死亡率，我们将开发一个模型来探索社会决定因素对 健康(SDOH)因素对未来5到30年慢性病发病率、死亡率和差异的影响。 我们将使用系统科学的方法创建一个数学模拟模型，该模型集成了风险和 心脏病、中风、糖尿病、慢性肾脏病、癌症和阿尔茨海默病发病率的SDOH因素， 说明SDOH与慢性病之间的相互联系和反馈循环。模型 将纳入以证据为基础的战略，以解决以下五个优先领域中每一个领域的SDOH因素 疾控中心国家慢性病预防和健康促进中心：建筑环境， 社区-临床联系、食品和营养安全、无烟政策和社会联系。通过 生成代表SDOH相关特征的合成种群(例如，种族/民族、性别、 年龄、收入、教育程度和城乡状况)和慢性病危险因素 或州人口，该模型将为美国的每个县和州产生有效的结果。 该模型还将根据国家监控数据进行校准。我们将开发一种多用户、基于Web的 该模型的公共使用版本，用于在CDC的网络平台上运行。疾控中心和公共卫生合作伙伴团体 可以使用该模型运行场景，以探索哪些PPP组合会产生最大影响 关于减少慢性病的差异和结果，以及购买力平价在成本和成本方面的比较- 有效性。该模型的结果将为未来与SDOH相关的公共卫生实践提供参考。此外， 公开提供的模式将允许社区成员和公共卫生利益团体创建 并探讨各种购买力平价对健康结果和差距的影响，从而令人鼓舞 使用基于社区的参与性进程和围绕解决方案的决策来解决 并减少慢性病风险因素、发病率和死亡率方面的差异。

PROJECT SUMMARY/ABSTRACT To support the Centers for Disease Control and Prevention (CDC) and states and communities in identifying programs, policies, or practices (PPP) that can reduce the ever-widening gaps in chronic disease incidence and mortality in the United States, we will develop a model to explore the impacts of social determinants of health (SDOH) factors on chronic disease incidence, mortality, and disparities over the next 5 to 30 years. We will use a systems science approach to create a mathematical simulation model that integrates risk and SDOH factors for the incidence of heart disease, stroke, diabetes, CKD, cancer, and Alzheimer’s disease, accounting for the interconnectedness and feedback loops between SDOH and chronic disease. The model will incorporate evidence-based strategies for addressing SDOH factors in each of the five priority areas for CDC’s National Center for Chronic Disease Prevention and Health Promotion: the built environment, community-clinical linkages, food and nutrition security, tobacco-free policy, and social connectedness. By generating synthetic populations to represent the SDOH-related characteristics (e.g., race/ethnicity, sex, age, income, education, and urban vs. rural status) and chronic disease risk factors of the selected county or state population, the model will produce valid results for each county and state in the United States. The model will also be calibrated to national surveillance data. We will develop a multi-user, web-based, public-use version of the model to operate on CDC’s web platforms. CDC and public health partner groups can run scenarios using the model to explore which combinations of PPPs would have the greatest impact on reducing chronic disease disparities and outcomes and how PPPs compare in terms of costs and cost- effectiveness. Results from the model will inform future public health practices related to SDOH. Moreover, the publicly available model will allow community members and public health interest groups to create scenarios and explore the impacts of various PPPs on health outcomes and disparities, thus encouraging the use of community-based participatory processes and decision-making around solutions to address SDOH and reduce disparities in chronic disease risk factors, incidence, and mortality.