# Integrating Epidemiologic and Environmental Approaches to Understand and Predict Coccidioides Exposure and Coccidioidomycosis Emergence

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA BERKELEY · 2020 · $28,430

## Abstract

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 p...

## Key facts

- **NIH application ID:** 10116673
- **Project number:** 3R01AI148336-01S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Justin V Remais
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $28,430
- **Award type:** 3
- **Project period:** 2019-12-09 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10116673

## Citation

> US National Institutes of Health, RePORTER application 10116673, Integrating Epidemiologic and Environmental Approaches to Understand and Predict Coccidioides Exposure and Coccidioidomycosis Emergence (3R01AI148336-01S1). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10116673. Licensed CC0.

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