Olivia Feldman
University of Tennessee-Knoxville, TN·Mathematics & Statistics·Early-career
During outbreaks like COVID-19, mathematical models help decide which control measures to use. But a model is only as good as the data that feeds it.
- Fields
Mathematics & Statistics
Public Health & Epidemiology
Ecology & Evolution
- Topics
mathematical biology
mathematical epidemiology
epidemiological models
- Grants
- 1 known grant, through Feb 2027
What they work on
- Develop improved, tractable likelihood models that capture the correlated, complex structure of epidemic data, for more accurate uncertainty estimates in mechanistic disease models.
- Use control theory to derive data sampling strategies that jointly minimize a practical-identifiability metric, how well parameters can be estimated, and the cost of collecting data.
- Test the sampling methods on synthetic data, then apply them to COVID-19, Zika and Ebola outbreaks to find which data would have been enough to reduce parameter uncertainty.
- Build inquiry-based modules teaching undergraduates mathematical modeling, coding and visualization using the project's epidemiological models.
More about the research
If the data collected do not match what the model needs, predictions can be badly uncertain, and policy choices can go wrong. This project asks a practical question: given limited public-health resources, what is the cheapest way to collect data that still lets a model give reliable answers?
Why it matters
Public-health agencies have limited money for testing and surveillance. Knowing which data to collect, and how often, could make outbreak models more trustworthy and help officials pick effective control strategies for future pandemics. The same methods could help ecologists and physiologists design experiments that match their models.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Amy Wesolowski
Johns Hopkins University, MD·Public Health & Epidemiology
Collect and standardize many human mobility datasets gathered by different methods, and statistically describe how movement varies at individual, household, community and larger scales.
Lauren Gardner
Johns Hopkins University, MD·Public Health & Epidemiology
Develop an integrated mathematical framework that couples mechanistic models of infectious disease transmission with economic models of individual decision-making, so that behavior responds to the epidemic state and to policies.
Patrick Stephens
Oklahoma State University, OK·Ecology & Evolution
Identify environmental factors (weather, air quality) and socioeconomic factors (physician numbers, vaccine willingness) that explain why Oklahoma counties and metro areas had more or fewer COVID-19 cases than their population size predicted.
The school
University of Tennessee-Knoxville: 16 labs on PI Pages, $387M a year on research, 426 research doctorates a year.
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