Leah JohnsonView profile
Associate Professor
Leah Johnson is an Associate Professor in the Department of Statistics at Virginia Polytechnic Institute and State University (Virginia Tech), within the College of Science. Her research focuses on the intersection of statistics, biology, and mathematics, particularly in understanding how individual variability in populations influences broader ecological and epidemiological patterns. Education: Ph.D. in Applied Mathematics and Statistics and Physics, University of California Santa Cruz (2006), Dissertation: Mathematical Modeling of Cholera M.S. in Physics, University of California Santa Cruz (2003) B.S. with Honors in Physics, The College of William and Mary (2001) Research Interests: Dr. Johnson’s work centers on infectious disease epidemiology, vector-borne disease dynamics, and the impact of climate change. She employs Bayesian statistical methods and mechanistic models to study how environmental drivers, population structure, and individual behaviors shape disease transmission and persistence. Key areas include malaria, dengue, and amphibian pathogens. Recent Article Trends: Her publications emphasize the role of temperature and humidity in vector performance, the development of databases for vector traits, and ecological forecasting under climate change. Studies highlight the importance of integrating empirical data with theoretical models to address public health challenges. Awards and Honors: Early Career Fellow, Mathematical Biosciences Institute (2013) Finalist, Kings College Junior Research Fellowship (2008) College Research Associate, University of Cambridge (2006–2009) Grants and Funding: Principal Investigator: Vector Behavior in Transmission Ecology (VectorBiTE) (NIH-NSF-USDA, 2015–2020) Co-PI: Effects of Temperature on Vector-Borne Disease Transmission (NSF-NIH-USDA, 2015–2020) Labs and Teams: She leads the QED Lab, which explores quantitative methods for ecological and epidemiological systems. The lab collaborates on global initiatives like the VectorByte platform for vector trait data and climate-driven disease forecasting.









