Mathematical modeling in epidemiology, ecology, and evolutionary biology, using the tools of differential equations and dynamical systems, stochastic processes, and statistical methods.

Current projects include modeling the seasonal epidemics and pandemics of influenza; the spread of HIV among injection drug users and sex workers; plague in 14-16 centuries in London; network epidemic models; statistical methods on disease parameter estimation.

• Ma, J., Worden, L. Levin, S.A., 2007, “Evolutionary Branching of Single Traits”, chapter in book “From Energetics to Ecosystems: The Dynamics and Structure of Ecological Systems”, 191-212, Springer Heidelberg. (link)

• Yuan, S., van den Driessche, P., Willeboordse, F. H., Shuai, Z. Ma, J., 2015. Disease invasion risk in a growing population, published online in Journal of Mathematical Biology (link).
• Li, M., Ma, J., P. van den Driessche, 2014. Model for Disease Dynamics of a Waterborne Pathogen on a Random Network, Journal of Mathematical Biology, published online before print. (link)
• Li, M., Illner, R., Edwards, R. Ma, J., 2014. Marketing new products: Bass models on random graphs. Communications in Mathematical Sciences, 13:497-509. (link)
• Ma, J., Dushoff, J., Bolker, B. M., and Earn, D. J. D., 2014. Estimating Initial Epidemic Growth Rates Bulletin of Mathematical Biology, 76:245-260, link.
• He, D., Dushoff, J., Day, T., Ma, J., and Earn, D. J. D., 2013. Inferring the causes of the three waves of the 1918 influenza pandemic in England and Wales. Proc. R. Soc. B, 280:20131345 (link).
• Ma, J., van den Driessche, P., Willeboordse, F. H., 2013. The importance of contact network topology for the success of vaccination strategies. Jour. Theor. Biol., 325:12-21. (link).
• Koch, D. Illner, R., Ma, J., 2013. “Edge Removal in Random Contact Networks and the Basic Reproduction Number”, Journal of Mathematical Biology, published online before print, doi: 10.1007/s00285-012-0545-6. (link).
• Ma, J., van den Driessche, P., Willebroodse, F., 2012, “Effective degree household network disease models”, Journal of Mathematical Biology, published online before print, doi: 10.1007/s00285-011-0502-9.(link)
• Ma, J., Dushoff, J., Earn, D.J.D., 2011, Age-specific mortality risk from pandemic influenza, Journal of Theoretical Biology, 288:29-34. (link)
• Tuite, A.R., Tien, J. Eisenberg, M., Earn, D.J.D., Ma, J., and Fisman, D.N., “Cholera epidemic in Haiti, 2011 – Using a transmission model to explain spatial spread of disease and identify optimal control interventions”, Annals of Internal Medicine, 154:593-601. (link)
• He, D., Dushoff, J., Day, T., Ma, J., and Earn, D.J.D., 2011, “Mechanistic modeling of the three waves of the 1918 influenza pandemic”, Theoretical Ecology, 4:283-288. (link)
• Goldstein, E., Dushoff, J., Ma, J., et al., 2009, “Reconstructing influenza incidence by deconvolution of daily mortality time series”, PNAS, published online before print, doi: 10.1073/pnas/092958. (link)
• Lindquist, J., Ma, J., van den Driessche, P., Willboordse, F., 2011, “Effective degree network disease models”, Journal of Mathematical Biology, 62(2), 142-164. (link)
• Lindquist, J., Ma, J., van den Driessche, P., Willboordse, F., 2009, “Network evolution by different rewiring schemes”, Physica D, 238(4), 370-278. (link)
• Ma, J., van den Driessche, P., 2008, “Case fatality proportion”, Bulletin of Mathematical Biology, 70(1), 118-133. (link)
• Ma, J., Levin, S.A., 2006, “The evolution of resource adaptation: how generalist and specialist consumers evolve”, Bulletin of Mathematical Biology, 68(5), 1111-1123. (link)
• Ma, J., Earn, D.J.D., 2006, “Generality of the final size formula for an epidemic of a newly invading infectious disease”, Bulletin of Mathematical Biology, 68(3), 679-702. (link)
• Ma, J., Ma, Z., 2006, “Epidemic threshold conditions for seasonally-forced SEIR models“, Mathematical Biosciences and Engineering, 3(1), 161-172. (link)