Improving outbreak predictions for infections like COVID-19 and schistosomiasis
Refining Predictive Models for Neglected and Emerging Infectious Diseases
This project improves computer models that forecast outbreaks of infections such as COVID-19 and schistosomiasis to help public health teams and people at risk.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Georgia NIH-funded |
| Lab location | 1 site (Athens, United States) |
| Project ID | NIH-11170547 on NIH RePORTER |
What this research studies
Researchers will combine data from surveillance systems, GPS, climate records, and wearable devices to strengthen outbreak forecasting. They will develop statistical methods to fill in missing information and allow models to update as new data arrive. The team will test these methods using past data from diseases like schistosomiasis, COVID-19, and seasonal influenza. The goal is to make local forecasts faster and more accurate so responses can be targeted sooner.
Who could benefit from this research
Good fit: People living in areas affected by diseases such as COVID-19, schistosomiasis, or seasonal flu who contribute health, location, or wearable data to surveillance systems would be the most relevant participants.
Not a fit: Patients with health issues unrelated to the infectious diseases studied or people who do not live in monitored areas or cannot share data (e.g., wearables/GPS) may not see direct benefit.
Why it matters
Potential benefit: More accurate and timely outbreak forecasts could help public health officials target interventions earlier and reduce infections in affected communities.
How similar studies have performed: Related forecasting models have supported responses to COVID-19 and seasonal flu, but handling missing and continuously incoming data is a newer and less-tested focus.
Where this research is happening
Athens, United States
- University of Georgia — Athens, United States (Active)
Researchers
- Principal investigator: Shen, Ye — University of Georgia
- Study coordinator: Shen, Ye
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.