The COVID-19 Safe Return Simulator combined proven epidemiological modeling methodologies with some of today’s most sophisticated forecasting techniques to predict when communities were projected to be low-risk at a county-by-county level. To address unique agency needs, the model can also be enhanced with real-time data such as population movements between counties and states, social media data reflecting updated public sentiment about health measures, hospitalization information, testing and contact tracing capacity, and personal protective equipment availability.
By powerfully clarifying the full picture of the pandemic’s effects, this project marked a significant step forward in the design, testing, and improvement of sophisticated, AI-enabled strategies for public health surveillance overall.
Extending the focus beyond the initial COVID-19 pandemic, federal health agencies can use this kind of advanced analytical approach for a range of public health applications. Examples include:
- Tracking and assessing outbreaks of COVID-19 variants and of other viruses such as Ebola, Zika, and monkeypox within neighborhoods and throughout the nation as a whole
- Analyzing opioid abuse in defined locales using overdose data from emergency rooms and modeling the effectiveness of different mitigation strategies
- Mapping levels of access to healthcare in multiple communities to better understand and address health inequities
- Mining huge data sets to identify ways to manage Americans’ risks for chronic conditions such as cancer and diabetes and to evaluate the most effective treatments
In each case, virtual laboratories that incorporate AI for accelerated data collection and analysis allow decision makers to use any number of variables to quickly establish many different models. These “digital experiments” move public health surveillance well beyond the realm of cohort studies and other traditional methods to redefine the speed, accuracy, and life-saving potential of public health initiatives, now and in the future. Learn more about how AI is transforming the federal health environment.