More than 25% of US adults suffer with seasonal allergies, yet the specific patters are still relatively poorly understood and a recent PNAS Nexus study is investigating these trends.
Seasonal allergies most commonly, things like itchy skin, runny noses, watery eyes, and asthma impact the U.S. economy far more than you'd think with the estimated annual cost coming to $10 billion.
While most cases don’t necessitate hospital visits, assessing their true prevalence remains challenging.
Current methods for gauging seasonal allergies often depend on self-reported symptoms or assumptions linking allergy rates to aeroallergen levels. However, this data is limited and generally focuses on pollen alone.
Internet-based tracking tools, including platforms like Twitter, Google, and Facebook, are now being used to monitor disease trends. The early efforts being things like "Google Flu Trends", but this has so far failed to predict influenza spread and serious cases accurately.
That said with advent of AI and better parsing of big data, such tools continue to evolve and show potential for public health tracking.
How Did The Study Work?
The study developed an internet-based method to track seasonal allergies across the U.S. The researchers employed AI and machine learning to analyze allergy-related Google searches and Twitter posts, hypothesizing that allergy symptoms would prompt increased online activity.
They then compared these online results to emergency department visits in densely populated California counties.
So, Did It Work?
The early results has shown that online data can work quite well as a proxy for aeroallergen exposure.
Allergy-related searches and Twitter posts did in fact correlate with ED visit data. Of course this is an early model and isn't cut and dry, but could be used to help hospitals predict their needs going forward.
National-Level Modeling
Using that California data, researchers mapped allergy-related online activity across 144 U.S. counties, analyzing daily fluctuations over eight years.
Seasonal allergy patterns varied regionally most peaked in spring as you'd expect, but there were some unique seasonal trends were noted in Texas and Florida, where additional peaks occurred in winter and summer.
While this is all relatively new and shouldn't be used as a complete guide it could well be used to help with healthcare management in the near future.
Reference: Stallard-Olivera, E., Fierer, N. (2024). Internet-based surveillance to track trends in seasonal allergies across the United States. PNAS Nexus. https://doi.org/10.1093/pnasnexus/pgae430.