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: 10307540
• 负责人: Justin V Remais
• 金额: $ 74.71万
• 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/10307540
• 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; Lead; Lung infections; Measures; Meningitis; Meteorology; Methods; Modeling; Monitor; Pathogen detection; Pattern; Performance; Periodicity; Persons; Population; Population Analysis; Public Health; Rain; Records; Reproduction spores; Research; Resolution; Retrospective cohort; Risk; Risk Factors; Sampling; Social Conditions; Soil; Source; Subgroup; Symptoms; Testing; Time; TimeLine; 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; risk prediction; sociodemographics; spatiotemporal; statistical and machine learning; temporal measurement; 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 球霉菌病是一种感染，是由吸入土壤栖息真菌孢子的孢子引起的感染 侵入性或C. posadasii，可导致慢性肺部感染，脑膜炎或死亡。西南州是 目前，有史以来记录的球菌病的发病率最高。疾病 整个西南部都承担了巨大的人力和经济负担，总计估计2.2美元 仅在加利福尼亚州就有数十亿美元的指控，从2000 - 2011年开始，仅在2000 - 2011年间与住院相关。 理解中的关键差距阻碍了公共卫生的反应，包括灰尘，病原体和 个人风险因素相互作用以确定疾病发生率，以及环境因素如何影响 病原体和灰尘的分布。为了解决这些差距，该项目调查了灰尘的影响 球虫下菌的暴露，环境变异性和社会人口统计学变化。增殖， 加利福尼亚州的分散体和球虫病的感染率。该研究重点是三个主要目的：1） 研究气候变化和灰尘暴露对球菌时空分布的影响 从2000年到2018年使用> 65,000个地理监视记录的发病率和案例交叉设计； 2） 确定在受干扰和时空的高空间和时间分辨率下的环境疾病来源 不受干扰的土壤，并确定风，降雨，土壤干扰和其他因素如何影响孢子分散 通过对空气和土壤中的炎性炎的纵向采样； 3）预测病原体密度的变化 空间和时间，并估计病原体密度与风险之间的暴露响应关系 使用案例交叉方法进行感染，并针对事件病例进行预期监视。追求这些 目的，这项研究将结合自2000年以来加利福尼亚州的地球性球菌病病例数据 前所未有的空间分辨率，并具有精细的灰尘浓度估计和环境数据 遥感，建模和地面监视器的组合。我们将使用新颖的领域和实验室 在空气和土壤中进行炎症炎的纵向采样的方法，确定微环境如何 降雨和干旱的条件和周期性模式决定了病原体源动力学，并确定 支持通过空气传播病原体分散的条件。通过这些活动，我们将确定 特定的灰尘条件构成最大感染风险，估计病原体暴露和剂量 响应关系，并评估风险群体和地区之间这种关系中的异质性。这 结果将阐明当前流行病的驱动因素，增强对分布和分散的理解 球虫剂属。在环境中，确定高风险区域和亚群。知识 获得的将支持决策者针对，设计和实施保护措施 脆弱的人群。