{"doi":"10.1289/ehp13875","title":"Estimating the Exposure–Response Relationship between Fine Mineral Dust Concentration and Coccidioidomycosis Incidence Using Speciated Particulate Matter Data: A Longitudinal Surveillance Study","abstract":"BACKGROUND: spp. spores, is an emerging infectious disease that is increasing in incidence throughout the southwestern US. The pathogen is soil-dwelling, and spore dispersal and human exposure are thought to co-occur with airborne mineral dust exposures, yet fundamental exposure-response relationships have not been conclusively estimated. OBJECTIVES: We estimated associations between fine mineral dust concentration and coccidioidomycosis incidence in California from 2000 to 2017 at the census tract level, spatiotemporal heterogeneity in exposure-response, and effect modification by antecedent climate conditions. METHODS: We acquired monthly census tract-level coccidioidomycosis incidence data and modeled fine mineral dust concentrations from 2000 to 2017. We fitted zero-inflated distributed-lag nonlinear models to estimate overall exposure-lag-response relationships and identified factors contributing to heterogeneity in exposure-responses. Using a random-effects meta-analysis approach, we estimated county-specific and pooled exposure-responses for cumulative exposures. RESULTS: (95% CI: 1.04, 1.12)] months before estimated disease onset, with the highest exposures being particularly associated. The cumulative exposure-response relationship varied significantly by county [lowest IRR, western Tulare: 1.05 (95% CI: 0.54, 2.07); highest IRR, San Luis Obispo: 3.01 (95% CI: 2.05, 4.42)]. Season of exposure and prior wet winter were modest effect modifiers. DISCUSSION: Lagged exposures to fine mineral dust were strongly associated with coccidioidomycosis incidence in the endemic regions of California from 2000 to 2017. https://doi.org/10.1289/EHP13875.","journal":"Environmental Health Perspectives","year":2025,"id":515508,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9614,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":851407,"name":"Nicole Keeney","orcid":"0000-0002-8128-2235","position":1,"is_corresponding":false},{"id":348483,"name":"Jennifer R. 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Vugia","orcid":"0000-0003-2595-7354","position":11,"is_corresponding":false},{"id":328311,"name":"Seema Jain","orcid":"0000-0002-6342-8288","position":12,"is_corresponding":false},{"id":86223,"name":"John R. Balmes","orcid":"0000-0002-2246-7002","position":13,"is_corresponding":false},{"id":612113,"name":"John W. Taylor","orcid":"0000-0002-5794-7700","position":14,"is_corresponding":false},{"id":314216,"name":"Justin V. Remais","orcid":"0000-0002-0223-4615","position":15,"is_corresponding":false},{"id":491844,"name":"Matthew J. Strickland","orcid":"0000-0003-3027-5470","position":16,"is_corresponding":false},{"id":844956,"name":"Amanda Weaver","orcid":null,"position":0,"is_corresponding":true}],"reference_count":67,"raw_metadata":null,"created_at":"2026-07-19T02:48:39.436300Z","pmid":"39804964","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}