Leah Johnson

Professor

Education

Ph.D. (Applied Mathematics and Statistics; Physics) June 2006, University of California Santa Cruz, Dissertation title: Mathematical Modeling of Cholera: from Bacterial Life Histories to Human Epidemics
M.S. (Physics) September 2003, University of California Santa Cruz
B.S. with Honors (Physics) June 2001, The College of William and Mary, Williamsburg, VA

Awards and Honors

Early Career Fellow, Mathematical Biosciences Institute, The Ohio State University (Fall 2013)
Finalist, Kings College Junior Research Fellowship, University of Cambridge (2008)
College Research Associate, Jesus College, University of Cambridge (2006-09)
President's Dissertation Year Fellow, UCSC (2005-06)
GAANN Fellow (Graduate Assistance in Areas of NationalNeed), UCSC (2002-05)
Regents Fellowship, UCSC (2001)

Current Grants

As Principal Investigator:

Collaborative Research: CIBR: VectorByte: A Global Informatics Platform for studying the Ecology of Vector-Borne Diseases. NSF DBI #2016264.

As Co-Principal Investigator:

Effects of temperature on vector-borne disease transmission: integrating theory with empirical data. NSF-NIH-USDA Ecology of Infectious Diseases. Award Number 1518681; PI: Mordecai, E. (Stanford). Project Period: 07/2015--06/2020

STAT 3615: Biological Statistics 1
STAT 4214/5214G: Methods of Regression
CMDA/STAT 4664: Computationally Intensive Stochastic Modeling

Methods for statistical -- particularly Bayesian -- inference and validation for mechanistic mathematical models of biological systems
Impacts of environmental drivers, population structure, and individual level dynamics and heterogeneity on the spread and control of infectious diseases, including vector-borne disease.
Understanding how individual behaviors or life history strategies evolve in response to external pressures and stimuli, such as anthropogenic factors or climate change, and how these individual traits impact population dynamics and persistence.

Leah R. Johnson - Google Scholar

Selected Recent Publications

S. Sorek, J. W. Smith Jr., P. J. Huxley, et al. “bayesTPC: Bayesian inference for thermal performance curves in R”. In: Methods in Ecology and Evolution 16.4 (2025), pp. 687-697. DOI: https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.70004
S. Pawar, P. J. Huxley, T. R. Smallwood, et al. “Variation in temperature of peak trait performance constrains adaptation of arthropod populations to climatic warming”. In: Nature Ecology and Evolution (2024), pp. 1-11. DOI: 10.1038/s41559-023-02301-8.
O. C. Villena, A. Arab, C. A. Lippi, et al. “Influence of environmental, geographic, socio-demographic, and epidemiological factors on presence of malaria at the community level in two continents.” In: Sci Rep (14 2024), p. 16734. DOI: 10.1038/s41598-024-67452-5.
J. J. Brown, M. Pascual, M. C. Wimberly, et al. “Humidity-The overlooked variable in the thermal biology of mosquito-borne disease”. In: Ecology Letters (2023). DOI: 10.1111/ele.14228.
J. W. Smith, R. Q. Thomas, and L. R. Johnson. “Parameterizing Lognormal state space models using moment matching”. In: Environmental and Ecological Statistics 30.3 (2023), pp. 385-419.
B. Zhang, R. B. Gramacy, L. R. Johnson, et al. “Batch-sequential design and heteroskedastic surrogate modeling for delta smelt conservation”. In: The Annals of Applied Statistics 16.2 (2022), pp. 816-842.
L. J. Cator, L. R. Johnson, E. A. Mordecai, et al. “The role of vector trait variation in vector-borne disease dynamics”. In: Frontiers in Ecology and Evolution 8 (2020), p. 189.
P. H. Boersch-Supan and L. R. Johnson. “Two case studies detailing Bayesian parameter inference for dynamic energy budget models”. In: Journal of Sea Research 143 (2019), pp. 57-69.
S. J. Ryan, C. J. Carlson, E. A. Mordecai, et al. “Global expansion and redistribution of Aedes-borne virus transmission risk with climate change”. In: PLoS Neglected Tropical Diseases 13.3 (2019), p. e0007213.