Prolonged coccidioidomycosis transmission seasons in a warming California: a Markov state transition model of shifting disease dynamics.

Abstract

Coccidioidomycosis, an emerging fungal disease in the southwestern United States, exhibits pronounced seasonal transmission, yet the influence of current and future climate on the timing and duration of transmission seasons remains poorly understood. We developed a distributed-lag Markov state transition model to estimate the effects of temperature and precipitation on the timing of transmission season onset and end, analysing reported coccidioidomycosis cases (<i>n</i> = 72 125) in California from 2000 to 2023. Using G-computation substitution estimators, we examined how hypothetical changes in seasonal meteorology impact transmission season timing. Transitions from cooler, wetter conditions to hotter, drier conditions were found to significantly accelerate season onset. Dry conditions (10th percentile of precipitation) in the spring shifted season onset an average of 2.8 weeks (95% CI: 0.43-3.58) earlier compared with wet conditions (90th percentile of precipitation). Conversely, transitions back to cooler, wetter conditions hastened season end, with dry autumn conditions extending the season by an average of 0.69 weeks (95% CI: 0.37-1.41) compared with wet conditions. When dry conditions occurred in the spring and autumn, the transmission season extended by 3.70 weeks (95% CI: 1.23-4.22). With prolonged dry seasons expected in California with climate change, our findings suggest this shift will extend the period of elevated coccidioidomycosis risk.