Patrick Stephens
Oklahoma State University, OK·Ecology & Evolution
Large disease outbreaks are becoming more frequent worldwide. Yet it is still unclear why some places are hit much harder than others.
- Fields
Ecology & Evolution
Public Health & Epidemiology
Mathematics & Statistics
- Topics
disease ecology
infectious disease dynamics
mathematical epidemiology
- Grants
- 2 known grants, through May 2027
What they work on
- 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.
- Modify SIR-like disease models to include human behavior, and compare models built on existing socioeconomic data with models using new statewide survey data on prevention attitudes.
- Build datasets, mechanistic models, and statistical tools that describe and predict spillover of Ebola and other filoviruses from animals to humans at ecological boundaries in Africa.
- Test whether Schmalhausen's law, which predicts outbreaks at species range edges or during unusual weather, applies to directly transmitted pathogens such as filoviruses.
More about the research
This work combines ecology, mathematical modeling, and social science to explain where and why outbreaks happen. It looks at environmental, socioeconomic, and behavioral factors. One project examines COVID-19 across Oklahoma. A second asks how Ebola and related viruses jump from animals to people in Africa.
Why it matters
Zoonotic diseases such as Ebola and Marburg cause large outbreaks, and the drivers of COVID-19 differed sharply from place to place. Databases of conditions linked to past outbreaks, risk maps for disease emergence, and models that include human behavior could help public health decision makers anticipate outbreaks. These tools could also help them target prevention in Africa and in US regions similar to Oklahoma.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Sagan Friant
Pennsylvania State University, PA·Public Health & Epidemiology
Measure how human land use shapes the population dynamics, movement and Lassa virus infection of rodent reservoirs, sampling field sites that span broad-scale drivers of Lassa fever risk.
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.
Fuqing Wu
University of Texas Health Science Center at Houston, TX·Public Health & Epidemiology
Build models that connect how virus levels change inside one infected person with how the virus passes between people, so that SARS-CoV-2 levels in wastewater can be read as measures of community transmission.
The school
Oklahoma State University: 15 labs on PI Pages, $254M a year on research, 238 research doctorates a year.
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