Integrating epidemiologic and environmental approaches to understand and predict Coccidioides exposure and coccidioidomycosis emergence

整合流行病学和环境方法来了解和预测球孢子菌暴露和球孢子菌病的出现

• 批准号: 10532733
• 负责人: Justin V Remais
• 金额: $ 74.14万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-09 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10532733
• 关键词: Address; Air; Area; California; Cessation of life; Charge; Chronic; Climate; Climatology; Coccidioides; Coccidioides immitis; Coccidioides posadasii; Coccidioidomycosis; Crossover Design; Data; Data Collection; Development; Disease; Disease Outbreaks; Dose; Droughts; Dust; Economic Burden; Economics; Elderly; Environment; Environmental Risk Factor; Environmental Wind; Epidemic; Epidemiology; Event; Exposure to; Future; Goals; Heterogeneity; High temperature of physical object; Hospitalization; Human; Incidence; Individual; Infection; Infection prevention; Influenza; Inhalation; Knowledge; Laboratories; Lung infections; Measures; Meningitis; Methods; Modeling; Monitor; Pathogen detection; Pattern; Performance; Persons; Population; Population Analysis; Proliferating; Public Health; Rain; Records; Reproduction spores; Research; Resolution; Retrospective cohort; Risk; Risk Factors; Sampling; Seasons; Social Conditions; Soil; Source; Subgroup; Symptoms; Testing; Time; Variant; Vulnerable Populations; burden of illness; density; design; environmental intervention; experience; fungus; high risk; infection rate; infection risk; novel; pathogen; pathogen exposure; predictive modeling; prospective; remote sensing; response; sociodemographics; spatiotemporal; statistical and machine learning; temporal measurement; timeline; transmission process

Project Summary Coccidioidomycosis is an infection caused by inhalation of spores from the soil-dwelling fungi Coccidioides immitis or C. posadasii, and can lead to chronic lung infection, meningitis, or death. Southwestern states are currently experiencing among the highest incidence rates of coccidioidomycosis ever recorded. The disease has levied a substantial human and economic burden throughout the southwest, totaling an estimated $2.2 billion in charges in California alone for coccidioidomycosis-associated hospitalizations from 2000-2011. Critical gaps in understanding have hindered the public health response, including how dust, pathogen, and individual risk factors interact to determine disease incidence, as well as how environmental factors influence the distribution of the pathogen and dust. To address these gaps, this project investigates the impacts of dust exposure, environmental variability, and sociodemographic change on Coccidioides spp. proliferation, dispersion, and coccidioidomycosis infection rates in California. The research focuses on three main aims: 1) investigate the influence of climate variation and dust exposure on the spatiotemporal distribution of cocci incidence using >65,000 geolocated surveillance records from 2000 to 2018 and a case-crossover design; 2) identify environmental sources of C. immitis at high spatial and temporal resolution in disturbed and undisturbed soil, and determine how wind, rainfall, soil disturbance and other factors influence spore dispersion through longitudinal sampling of C. immitis in air and soil; and 3) predict changes in pathogen density over space and time and estimate the exposure-response relationship between pathogen density and risk of infection using a case-crossover approach with prospective surveillance for incident cases. In pursuit of these aims, the research will combine georeferenced coccidioidomycosis case data across California since 2000 at an unprecedented spatial resolution with fine-scale dust concentration estimates and environmental data from a combination of remote sensing, modeling and ground monitors. We will use novel field and laboratory methods to conduct longitudinal sampling of C. immitis in air and soil, determining how microenvironmental conditions and cyclical patterns of rainfall and drought determine pathogen source dynamics, and identifying conditions that support pathogen dispersion through the air. Through these activities, we will identify the specific dust conditions that pose the greatest risk for infection, estimate pathogen exposure and the dose- response relationship, and evaluate heterogeneity in this relationship across risk groups and regions. The results will elucidate drivers of the current epidemic, enhance understanding of the distribution and dispersion of Coccidioides spp. in the environment, and identify high risk regions and subpopulations. The knowledge gained will support decision-makers in targeting, designing and implementing protective measures for vulnerable populations.

项目摘要 球孢子菌病是一种因吸入土壤真菌球孢子菌的孢子而引起的感染。 肺炎或波斯达氏弧菌，并可导致慢性肺部感染、脑膜炎或死亡。西南部各州 目前球孢子菌病的发病率是有记录以来最高的之一。这种病 在整个西南地区造成了巨大的人力和经济负担，估计总额为2.2美元 从2000-2011年间，仅在加利福尼亚州，与球孢子菌病相关的住院费用就高达10亿美元。 认识上的严重差距阻碍了公共卫生反应，包括粉尘、病原体和 个体风险因素相互作用决定疾病发生率，以及环境因素如何影响 病原体和粉尘的分布。为了解决这些差距，这个项目调查了尘埃的影响 球藻暴露、环境变异性和社会人口学变化。扩散， 扩散，和球孢子菌病在加利福尼亚州的感染率。本文的研究主要集中在三个方面：1) 调查气候变化和沙尘暴露对球菌时空分布的影响 使用2000年至2018年65,000个地理位置监测记录和病例交叉设计的发病率；2) 在高时空分辨率下识别受干扰的线虫的环境来源 原状土壤，并确定风、降雨、土壤扰动和其他因素如何影响孢子散布 通过对空气和土壤中的线虫进行纵向采样；以及3)预测病原体密度的变化 空间和时间，并估计病原体密度和风险之间的暴露-反应关系 采用病例交叉方法进行感染，并对事件病例进行前瞻性监测。为了追求这些 旨在，这项研究将结合加州自2000年以来的地理参考球孢子菌病病例数据， 史无前例的空间分辨率与细尺度尘埃浓度估计和环境数据来自 遥感、建模和地面监测的结合。我们将使用新的领域和实验室 方法对空气和土壤中的隐翅虫进行纵向采样，确定微环境 降雨和干旱的条件和循环模式决定了病原源的动态，并确定了 支持病原体在空气中传播的条件。通过这些活动，我们将确定 对感染构成最大风险的特定粉尘条件，估计病原体暴露和剂量- 应对关系，并评估这种关系在风险群体和地区中的异质性。这个 结果将阐明当前疫情的驱动因素，加强对疫情分布和扩散的了解 球藻(Coccidioidesspp.)并确定高危区域和亚人群。《知识》 GAIN将支持决策者有针对性地、设计和实施保护措施 弱势群体。