DOI 10.1080/09603123.2025.2566245
Mapping the environmental risk of coccidioidomycosis in Sonora, Mexico: a Bayesian spatiotemporal perspective (2010-2022).
Аннотация
Coccidioidomycosis, a fungal disease caused by Coccidioides spp. is endemic in arid regions of the Americas. Although northern Mexico shows increasing incidence, its environmental determinants remain understudied. This research examines the association between coccidioidomycosis and environmental factors in Sonora, Mexico, from 2010 to 2022. We integrated municipal-level hospital discharge data with mean annual temperature, total annual precipitation, wind speed and direction, soil moisture, vegetation index and land use (human settlements and agriculture). Using a Bayesian hierarchical spatiotemporal model with a second-order random walk structure, we estimated posterior relative risk. Results indicate that higher mean annual temperature, total annual precipitation, and wind patterns were associated with increased hospitalization rates, whereas greater vegetation cover and soil moisture were associated with reduced rates. Spatial heterogeneity in posterior relative risk was substantial, with hotspots detected in municipalities such Hermosillo, Cajeme and Caborca showing marked increases. These results contribute to a better understanding of the dynamic environmental factors influencing coccidioidomycosis acquisition, which can inform more effective public health strategies. However, to improve future risk prediction and disease prevention, it will be necessary to also consider immunological, genetic, and lifestyle factors among populations living in endemic areas.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.