Could the Omicron variant of COVID-19 be masking itself as a common cold virus?
Source – CDC Public Health Image library ID 11162. Author – James Gathany. Public Domain
Influenza A virus, or IAV is a pathogen with strains that cause seasonal flu in humans; it can also infect birds and some mammals.
The 2025-26 flu season has been one of the most severe in recent years, with hospitalisation rates reaching their second-highest level in 15 years of CDC tracking. Researchers at the University of Arizona have been able to spot the surge early, weeks before federal lab data confirmed it. The researchers achieved this with a digital platform that collects flu symptoms directly from people across the country, built on AI.
The digital platform Global Flu View brings together self-reported flu symptom data from partner programs in eleven different countries. The project began as a means to compare a handful of national surveillance systems. Now it has grown into a shared digital infrastructure, with a common map, standardized data and AI-driven forecasts that project flu activity weeks ahead. The platform is part of the Global Health Institute in the College of Public Health.
Global Flu View is one of the very few functional digital epidemiology tools available worldwide – a field that uses non-traditional data sources such as self-reported health surveys to track and predict disease patterns.
Symptoms of human seasonal flu usually include fever, cough, sore throat, muscle aches and, in severe cases, breathing problems and pneumonia that may be fatal.
“We wanted to see if connecting self-reporting systems into a single platform could help answer our fundamental questions – where flu starts and how it spreads globally. That was the genesis of this platform,” explains Mark Smolinski, who helped create Global Flu View.
From Flu Near You to Global Flu View
Global Flu View grew out of an earlier project called Flu Near You. Smolinski built Flu Near You in 2011 in partnership with HealthMap, a disease surveillance project at Harvard, to track self-reported flu symptoms across the United States.
“We knew that any pandemic threat would most likely be a respiratory disease, because what’s what allows it to spread globally. So, we built a tool around that.” Smolinski adds.
From the start, the team designed Flu Near You to be compatible with similar systems running in Australia and Europe. As more countries launched their own similar systems, the teams behind them began collaborating. It became clear that combining their data into a single platform could reveal patterns that no single system could see on its own.
Beyond the map
The platform also creates opportunities for the next generation of public health researchers. Global Flu View’s Spark program, offers students at the College of Public Health the chance to work directly with the platform on projects ranging from AI-driven forecasting to expanding surveillance into new regions.
Filling a gap in traditional surveillance
What makes this data valuable to medics is what it captures that the traditional approach cannot. Official flu tracking relies on people visiting a doctor and getting a lab test. But an estimated 80% of people who get the flu never see a doctor, which means the official numbers only reflect a fraction of actual cases.
The goal is not to replace the official systems, but to fill the gap between when people get sick and when they show up in the data.