From Reactionary to Anticipatory Integrated Action: Novel Environmental Health Surveillance for Mass Gatherings

Advances in AI-driven analytics, human-in-the loop techniques, and wastewater monitoring provide the foundation needed to shift from reactive to anticipatory actions for mass gatherings. Traditional surveillance systems focus on clinical and lab-based notification pathways, which often result in tardy actions being implemented. Thus, traditional surveillance is becoming outdated. Mass gatherings pose heightened public health risks and hazards, including trauma; injury and substance misuse; deliberate poisoning; and infectious diseases such as food and waterborne illnesses, sexually transmitted infections, and respiratory diseases. There is also a heightened concern due to reduced vaccination coverage. As a result, future international events such as the Olympic Games likely will have an influx of people from regions with active outbreaks, amplifying public health threats. This reality, combined with an increased frequency of terrorism and other mass casualty incidents, highlights the need for anticipatory action. We propose a novel framework that we call the Environmental Health Surveillance and AI for Event Protection (E-SAFE) model. This model leverages and integrates environmental health measures with recent advances in AI, data availability, predictive analytics, and a multilayer defense to anticipate disease outbreaks and other risks earlier and faster. Applying these tools for the 2028 Los Angeles Olympic Games and other mass gatherings could maximize health system readiness and create a scalable and transferable legacy for environmental health surveillance.