Modeling Infectious Disease

We use a combination of mathematical analysis and computer simulation to examine the evolution and co-evolution of hosts and parasites. Themes include:

The Evolution of pathogens (virulence)

Spatial Structure: There is always some form of spatial or social structure within populations: individuals interact with some individuals more often than others. We use a combination of computer simulation and pair approximation to examine the implication of local interactions to the evolution of parasites. 

Boots, M., & Sasaki, A. (1999). “Small worlds” and the evolution of virulence: infection occurs locally and at a distance. Proceedings of the Royal Society of London. Series B, Biological Sciences, 266(1432), 1933–1938 https://doi.org/10.1098/rspb.1999.0869

Boots, M., & Sasaki, A. (2002). Parasite-driven extinction in spatially explicit host-parasite systems. American Naturalist, 159(6), 706–713 https://doi.org/10.1086/339996

Boots M., P. J. Hudson & A. Sasaki (2004). Large shifts in pathogen virulence relate to host population structure.  Science 303, 842-844.

Kamo M., A. Sasaki & M. Boots (2007). The role of trade-off shapes in the evolution of parasites in spatial host populations: an approximate analytical approach. Journal of Theoretical Biology 244, 588-596.

Bartlett L. J. & M. Boots (2021). The central role of host reproduction in determining the evolution of virulence in spatially structured populations. Journal of Theoretical Biology 523, 110717.

O’Neill, X., A.R. White, G.R. Northrup, C.M. Saad-Roy, P.S. White & M. Boots (2025). Superspreading and the evolution of virulence. PloS Computational Biology. 21 (10), e1013517.

The evolution of emerging disease & zoonoses: We are interested in evolution under non equilibrium situations including disease emergence and zoonotic diseases in humans. 

Sasaki A., S. Lion & M. Boots (2022). Antigenic escape selects for the evolution of higher pathogen transmission and virulence. Nature Ecology and Evolution 6, 51-62.

Lion S., M. Boots & A. Sasaki (2023). Extending eco-evolutionary theory with oligomorphic dynamics. Ecology Letters,  https://doi.org/10.1111/ele.14183

The evolution of host defense to pathogens

We’re interested in the role of eco-evolutionary feedbacks on the evolution of host defense to pathogens.  Selected papers

Boots, M., & Haraguchi, Y. (1999). The Evolution of Costly Resistance in Host‐Parasite Systems. The American Naturalist, 153(4), 359–370 https://doi.org/10.1086/303181

Best, A., White, A., & Boots, M. (2008). Maintenance of host variation in tolerance to pathogens and parasites. Proceedings of the National Academy of Sciences of the United States of America, 105(52), 20786–20791 https://doi.org/10.1073/pnas.0809558105

The generation of diversity in hosts and parasites

Understanding the drivers of host and parasite diversity is a key challenge in the lab.

• Boots M, A.White, A. Best & R. Bowers (2014). How specificity and epidemiology drive the coevolution of static trait diversity in hosts and parasites. Evolution, 68, 1594-1606.
• Boots M, A. White, A. Best & R. Bowers (2012). Diversity in host resistance: The importance of who infects whom. Ecology Letters 15, 1104-1111.

Coevolutionary Dynamics

How important is coevolution as opposed to evolution to the outcome?

• Best, A., A. White & M. Boots (2009). The implications of co-evolutionary dynamics to host-parasite interactions. The American Naturalist 173, 779-791.
• Best A, A. White & M. Boots (2014). The co-evolutionary implications of host tolerance. Evolution, 68, 1426-1435.
• Ashby B & M. Boots (2015). The coevolution of parasite virulence and host mating strategies. Proceedings of the National Academy of Sciences 112(43) 13290-13295
• Best, A., S.Guth, & M. Boots (2025). The coevolution of parasite virulence, and host investment in constitutive and induced defense.  Journal of Evolutionary Biology, 38 (4), 481-491.  https://doi.org/10.1093/jeb/voaf014.

Human Infectious Disease

We use epidemiological and evolutionary models to address questions in human vector-borne disease.

Dengue

Numerous studies have shown that the majority of DENV infections are inapparent and that the ratio of inapparent to symptomatic infections (I/S) fluctuates substantially year-to-year.  However, the mechanisms explaining these large fluctuations are not well understood. We used a mechanistic model to test the hypothesis that in dengue-endemic areas, frequent boosting (i.e., exposures to DENV that do not lead to extensive viremia and result in a <4-fold rise in antibody titers) of the immune response can be protective against symptomatic disease and this can explain fluctuating I/S ratios.

• Alexander L. W., R. Ben-Shachar, L. C. Katzelnick, G. Kuan, A. Balmaseda, E. Harris & M. Boots (2021). Boosting can explain patterns of fluctuations of ratios of inapparent to symptomatic dengue virus infections. Proceedings of the National Academy of Sciences 118(14) e2013941118.

The four serotypes of dengue show a characteristic out of phase pattern in Bangkok, while the phylogenetic analysis of the data shows evidence of an immune interaction between the serotypes. We used models to show that partial cross-immunity was sufficient to cause the out of phase dynamics providing evidence for cross-immunity between dengue serotypes.

• Adams, B., E. C. Holmes, C. Zhang, M. P. Mammen Jr, S. Nimmannitya, S. Kalayanarooj and M. Boots (2006). Cross-protective immunity can account for the alternating epidemic pattern of dengue virus serotypes circulating in Bangkok. Proceedings of the National Academy of Science. 103, 14234-14239.

We had previously shown that the large difference between the dengue serotypes could be explained by antibody-dependent enhancement on death.

• Kawaguchi, I., A. Sasaki & M. Boots (2003). Antibody-dependent enhancement explains coexistence in dengue serotypes. Proceedings of the Royal Society, Series B 270, 2241-2247.

Further models look at the role of mosquito transmission of dengue.