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 球孢子菌病是一种感染所造成的吸入孢子从土壤居住的真菌球孢子 immitis或C. posadasii，并可能导致慢性肺部感染，脑膜炎或死亡。西南部各州是 目前正在经历有史以来最高的球孢子菌病发病率。疾病 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。 仅在加州，2000-2011年，就有10亿美元的费用用于球孢子菌病相关的住院治疗。 认识上的重大差距阻碍了公共卫生反应，包括灰尘、病原体和 个体风险因素相互作用决定疾病发病率，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， 暴露、环境变异性和社会人口学变化对球孢子菌属的影响扩散， 分散和球孢子菌感染率在加州。本研究主要有三个目的：（1） 探讨气候变化和粉尘暴露对球菌时空分布的影响 使用2000年至2018年超过65，000份地理定位监测记录和病例交叉设计的发病率; 2） 确定C.高空间和时间分辨率， 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分散 通过纵向取样，空气和土壤中的病原体密度变化; 3）预测 空间和时间，并估计病原体密度与风险之间的因果关系， 使用病例交叉方法，对事件病例进行前瞻性监测。为了实现这些 目的是，该研究将联合收割机自2000年以来加州州的地理参考球孢子菌病病例数据， 一个前所未有的空间分辨率与细尺度粉尘浓度估计和环境数据， 遥感、建模和地面监测相结合。我们将使用新的领域和实验室 方法采用纵向抽样的方法对C.在空气和土壤中，确定微环境如何 降雨和干旱的条件和周期性模式决定病原体源动态， 支持病原体通过空气传播的条件。通过这些活动，我们将确定 造成最大感染风险的特定粉尘条件，估计病原体暴露和剂量- 反应关系，并评估这种关系在不同风险群体和地区的异质性。的 结果将阐明当前流行病的驱动因素，加强对分布和分散的理解， 球孢子菌属并确定高风险区域和亚群。知识 将支持决策者针对、设计和实施保护措施， 弱势群体。