Improving predictions of COVID-19 and other infectious disease outbreaks
Quantifying Error Growth to Improve Infectious Disease Forecast Accuracy
This project tests methods to make predictions about COVID-19 and other outbreaks more accurate so hospitals and communities can plan better.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Columbia University Health Sciences NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project ID | NIH-10836422 on NIH RePORTER |
What this research studies
From a patient's perspective, researchers are borrowing techniques from weather forecasting to learn how errors grow in infectious disease models. They will analyze past outbreak data for illnesses like COVID-19, influenza, dengue, and Ebola to identify when and why forecasts go wrong. The team will use computer simulations and statistical tools rather than enrolling patients for treatment. If the methods succeed, public health officials and hospitals could receive more reliable forecasts to guide staffing, supplies, and timing of interventions.
Who could benefit from this research
Good fit: This project does not enroll patients; it relies on existing public health surveillance and outbreak data rather than recruiting individuals.
Not a fit: People seeking new treatments or immediate personal clinical benefits would not directly benefit from this modeling-focused research.
Why it matters
Potential benefit: If successful, this work could provide clearer early warnings of patient surges so hospitals and public health systems can avoid shortages and improve care.
How similar studies have performed: Related forecasting systems have produced useful predictions for influenza and COVID-19, but improving and controlling forecast error growth is a newer focus.
Where this research is happening
New York, United States
- Columbia University Health Sciences — New York, United States (Active)
Researchers
- Principal investigator: Shaman, Jeffrey L — Columbia University Health Sciences
- Study coordinator: Shaman, Jeffrey L
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.