Models for the evolution of virulence traditionally assume a trade-off between inverse disease-induced mortality rate and infectivity, resulting in intermediate virulence. The underlying intuition is that faster growing agent populations do both more damage and produce more infective particles. This intuition implicitly assumes a well-mixed host body. In reality both damag...
In models of disease transmission on contact networks, the probability of exposure is determined by the connectivity (degree) of the individual (node). Thus, the most highly connected individuals in a contact network have both a higher probability of spreading infection through the population and a higher rate of exposure (susceptibility) through social contacts. As an epi...
Mathematical and computational models are increasingly used in support decisions in public health, however the perception of their reliability and the criteria for their uses is contrasted among domain experts. We consider the Global Epidemic and Mobility model that generates stochastic realizations of epidemic evolution worldwide from which we can gather information such ...
Virulence evolution has a long history, including the now-classic paper of Gandon et al. 2001 on the impact of malaria vaccination on the virulence of the parasite. Gandon et al. found that a vaccine with the action of reducing the pathogen growth rate in the host selects for more virulent pathogens, while an infection-blocking vaccine selects for less virulent pathogens. ...
In the talk we present a simple extension of the configuration model to weighted networks, and state some asymptotic properties of the network model. The weights may be used for some stochastic process taking place on the network; for example an epidemic where the probability of transmission between two individuals depends on the weight of the connected edge (the weight fo...
We consider a SIR epidemic model propagating on a random network generated by a configuration model, where the degree distribution of the vertices is given and where the edges are randomly matched. The evolution of the epidemics is summed up into three measure-valued equations that describe the degrees of the susceptible individuals and the number of edges from an infectio...
Parasite evolution is increasingly being recognized as one of the most important challenges in applied evolutionary biology. Understanding how parasites maximize fitness whilst facing the diverse challenges of living in cells, hosts, and vectors, is central to disease control and offers a novel testing ground for evolutionary theory. Along with Sam Brown, I recently hosted...
Tuberculosis is one of the major global diseases in terms of both prevalance and mortality. In recent decades, strains of the disease have evolved that are resistant to several, or all, of the drugs used to treat the disease. Drug resistance is conferred by rare mutations, raising the question of how multiple mutations might have arisen in a single strain. Motivated by thi...
The basic reproduction number R0 is one of the most important quantities in epidemiology. However, for epidemic models with explicit social structure involving small mixing units such as households, its definition is not straightforward and a wealth of other threshold parameters has appeared in the literature. In this talk I use branching processes to define R0, apply this...
Multi-drug resistant pathogens such as MRSA and VRE give rise to substantial morbidity and mortality, and impose a huge economic burden on healthcare systems. In this talk we describe a framework for analysing patient-level data from hosptials on such pathogens, employing stochastic transmission models and using Markov chain Monte Carlo methods witin a Bayesian statistical...
HIV has been introduced in Cuban in 1986. From the beginning of the epidemics, contact-tracing is used, in the purpose of detecting more HIV-positive individuals and of controlling the spread of the disease. The data generated from this contact-tracing program provide some partial information on the social networks underlying the propagation of HIV. In this talk, we presen...
We consider an stochastic, individual-based model of an evolving population with logistic density-dependence, where individuals are characterized by a quantitative phenotypic trait. Under appropriate parameters scalings of rare mutations and large populations, we obtain a stochastic jump process on the mutation time-scale, where evolution proceeds through successive invasi...
Our understanding of the ecological and evolutionary conditions that permit the establishment and persistence of different bacterial species in host-associated microbial communities is incomplete. Recent work done to characterize human vaginal bacterial communities by experimental and analytical approaches has shown that idiosyncratic changes in species composition and wid...