Population Dynamics of Infectious Disease ~
Infectious Disease Modeling

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The Grenfell Lab studies the spatio-temporal dynamics of infectious disease. Apart from its public health importance, measles provides an ideal paradigm for understanding nonlinear population interactions.  Our lab has made significant developments in epidemic modeling methodology, time series methods and analysis of large spatio-temporal data sets. In collaboration with others, we have used the resulting methods to quantify the dynamics of measles epidemics, in a range of settings and the impact of vaccination strategies against measles and other childhood infections. Our analyses reveal a wide spectrum of dynamic behavior in large populations, spanning limit cycles in pre-vaccination UK to chaotic dynamics in more seasonally-driven contexts.

We use gravity models, adapted from transportation theory, to capture and explain key features of measles metapopulation dynamics in developed countries (ie. England and Wales). Recent development includes refinement of these gravity models to better understand the relative importance of core-satellite dynamics and local metapopulations to the persistence of measles. A big recent thrust of the group has been generalizing these results to explore comparative dynamics of a range of pathogens, including influenza, rotavirus, RSV, Norovirus, HIV, HCV and veterinary morbilliviruses

We also look at the dynamics of viral evolution – phylodynamics. In particular we are interested in the question of how pathogen phylogenies are affected by host immunity, transmission bottlenecks and epidemic dynamics at scales from individual host to population? Grenfell and colleagues coined the term phylodynamics, describing the feedback between epidemiological and evolutionary dynamics of pathogens, in a paper on immune escape in influenza (add reference). We are currently exploring how the impact of vaccination impacts the phylodynamics of a range of infections.

Our recent work includes:

  • Linking within-host, individual level and population dynamics of measles and other infections
  • Exploring epidemiological and evolutionary implications of novel broad spectrum influenza vaccines
  • Population dynamics and control of rotavirus
  • Synthesizing epidemic dynamics of immunizing infections with the spatiotemporal economic dynamics of vaccination and the impact of vaccine hesitancy
  • The dynamics and control of HIV, typhoid and hand foot and mouth disease (HFMD)