With eight Public Health Emergencies of International Concern declared in the last 15 years, timely and effective public health decision-making can save lives and limit disease spread. However, as we all experienced with COVID-19, decision-makers must use predictive models to make challenging choices with significant societal trade-offs. This work is not easy, particularly in the face of incomplete data and rampant misinformation.
A recently published blog shares insights from a diverse group of innovators who were selected as winners of the inaugural Trinity Challenge on pandemic preparedness. Collectively they are working to use data and analytics to better predict, detect and respond to pandemic threats. Jhpiego has been providing support to the cohort since 2022, and facilitated an in-person conversation earlier this year.
The Trinity Challenge winners explored some of the factors that enable and impede the use of data models for informed decision-making during health emergencies. Drawing upon their diverse perspectives as academics, nonprofits and for-profits working in different regions around the world, they highlighted the critical—and oft neglected—role of frontline health workers in generating the data that underpins all models, the importance of centering the needs and priorities of decision-makers, and the power of storytelling for translating complex data insights into practical action.