Final Report Summary - MOBVIR (Host mobility and pathogen virulence in host-pathogen interactions: ecology and evolution)
In our project, we developed mathematical models to generate predictions on the evolution of host-pathogen interactions. Specfically, we showed that when infection patterns generated by host mobility or pathogen dispersal change, natural selection can favour more aggressive or milder pathogens depending on the epidemiological characteristics of the disease. The classical expectation has been that long-range dispersal should lead to increased virulence in infectious diseases, raising concerns that infectious diseases may evolve to be more severe in a globalized world. Our work shows that host long-lived immunity is critical to the evolution of higher virulence when infection becomes more global and that virulence can be maximal for intermediate mixing (a pattern which closely resembles the interaction network of modern societies or trading routes) in host populations with substantial demographic turnover. Although our results are derived from simplified epidemiological models, they rely on a general mathematical approach that has been developed during this project and could be applied to more complex epidemiological scenarios. The main message is that taking into account the epidemiological characteristics of the disease are crucial for predictions on the interplay between virulence evolution and changes in host and pathogen mobility. Recent experimental results have also made it possible to test the predictions of our model using experimental interactions between bacteria and viruses in the lab, which is a focus of future research.
At a more fundamental level, our work has clarified the driving forces of pathogen evolution in populations with different levels of mixing. We have shown that the evolutionary outcome depends on the balance between the genetic and epidemiological structures of the population. In particular, pathogen virulence is predicted to increase when parasitic strains in interacting hosts are less related (which will typically be the case if mobility is high); but only if epidemiological structuring is strong enough. This helps clarify an ongoing controversy about the role of genetic relatedness between individuals in the evolution of traits and shows that insights obtained from more fundamental research fields, such as social evolution theory, are helpful when trying to understand what drives the evolution of infectious diseases.
As exemplified by the Swine Flu outbreak in 2009, the consequences of long-range mobility in modern human societies is a topic of growing concern in the general public. The research carried out during this project can lead to a better understanding of the ecological and social factors that may contribute to increase the severity or emergence of infectious diseases. In the long run, we hope this could help devise better recommendation that can be used by policy makers for the management of infectious diseases.
At a more fundamental level, our work has clarified the driving forces of pathogen evolution in populations with different levels of mixing. We have shown that the evolutionary outcome depends on the balance between the genetic and epidemiological structures of the population. In particular, pathogen virulence is predicted to increase when parasitic strains in interacting hosts are less related (which will typically be the case if mobility is high); but only if epidemiological structuring is strong enough. This helps clarify an ongoing controversy about the role of genetic relatedness between individuals in the evolution of traits and shows that insights obtained from more fundamental research fields, such as social evolution theory, are helpful when trying to understand what drives the evolution of infectious diseases.
As exemplified by the Swine Flu outbreak in 2009, the consequences of long-range mobility in modern human societies is a topic of growing concern in the general public. The research carried out during this project can lead to a better understanding of the ecological and social factors that may contribute to increase the severity or emergence of infectious diseases. In the long run, we hope this could help devise better recommendation that can be used by policy makers for the management of infectious diseases.