Rising levels of airborne fungal spores could provide early warning for spikes in flu and COVID-19 cases, according to new research presented at the American Society for Microbiology’s ASM Microbe 2025 meeting in Los Angeles.
The study, conducted in Puerto Rico, suggests that tracking these environmental signals may offer a powerful, underused tool for predicting seasonal waves of respiratory illness.
From the Ground to the Air to the Clinic
The research team, led by Dr. Félix E. Rivera-Mariani of Lynn University and the RIPLRT Institute, explored how natural environmental factors—specifically airborne fungal spores and pollen—might influence the timing and scale of viral respiratory outbreaks. While spores and pollen are known to aggravate asthma and allergies, their relationship to viral illnesses has been less clear.
Puerto Rico offered an ideal testing ground. Its year-round fungal and pollen activity, combined with active monitoring stations in San Juan and Caguas, provided a dense data environment. The team analyzed daily environmental readings and viral case counts from 2022 to 2024, using statistical and machine learning models to test whether airborne exposures could predict infection spikes.
What They Found—and What It Might Mean
The results were striking. Fungal spores—not pollen—were strongly correlated with rising flu and COVID-19 cases, often within a matter of days. This “lag effect” allowed the researchers to forecast spikes with notable accuracy, especially during the fall season.
- Airborne fungal spores predicted viral surges within the same or following week
- Pollen showed no consistent predictive value for flu or COVID-19
- Predictive accuracy peaked during autumn months in both regions studied
“Our findings suggest that monitoring airborne fungal spore levels could help predict short-term outbreaks of flu and COVID-19,” said Rivera-Mariani. “That gives public health systems an early warning signal that could be especially valuable for vulnerable populations.”
Beyond Human Transmission
By pointing to environmental drivers, this study expands the understanding of what causes outbreaks to swell. It challenges the notion that human-to-human transmission alone governs respiratory virus trends and raises the possibility of broader environmental contributions. This insight could shape how health systems time their alerts and interventions.
One important detail that wasn’t emphasized in the press release: the machine learning models consistently performed better when fungal data was included than when only traditional epidemiological factors were considered. That suggests fungal surveillance could add measurable value to forecasting tools.
Looking Ahead
The researchers now plan to explore whether fungal exposure correlates with more severe health outcomes, such as hospitalizations or deaths, and to test whether similar environmental patterns occur in other regions. Rivera-Mariani also hopes to work with health agencies to integrate fungal monitoring into public health alert systems.
“These findings may help inform environmental risk alerts, particularly for the elderly or those with asthma and allergic rhinitis,” Rivera-Mariani noted.
While more research is needed, this work offers a compelling case for watching the air—not just the people—when trying to stay ahead of the next viral wave.
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