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The same social networks can promote spread of viruses, but suppress their evolution

Posted January 26, 2015

Deeper understanding of social dynamics of disease transmission is a beautiful example of interdisciplinary work between social scientists and epidemiologists. However, interplay between population structure and evolution of viruses is yet to be determined.

Image credit: CIMMYT via Flickr, CC BY-NC-SA 2.0.

Image credit: CIMMYT via Flickr, CC BY-NC-SA 2.0.

”We show that heterogeneity in contact structure, which facilitates the spread of a single disease, surprisingly renders a resident strain more resilient to invasion by new variants. Our results suggest that many host contact structures suppress invasion of new strains and may slow disease adaptation,” the authors of the article published on the Nature Communicatios say.

It is well-known that real-world social networks often are scale-free. One of the characteristics of these networks is presence o so called hubs, members who have considerably more contacts than others. In other words, these networks are heterogeneous. In case of epidemics, these individuals can function as superspreaders and dramatically foster  dissemination of illnesses.

Biologists at the Harvard University and ETH Zürich have number of reasons think that network structure can exert important influence not only on the diffusion, but also on the evolution of viruses. ”First, population structure can either amplify or suppress selection in simple population-genetic models. Second, models that have looked at the successive spread of two strains on a heterogeneous contact network have shown that the spread of the first strain modifies the network in a manner that may affect the spread of the second strain. Third, local contact heterogeneity arising from spatial structure has been shown to affect the evolution of pathogen virulence both in theoretical and experimental investigations,” world famous scholar Martin A. Nowak says.

Researchers conducted computer simulations which allow to model evolutionary dynamics on several real-world and theoretical networks. They have obtained surprising results. Although network heterogeneity increases speed of virus transmision, it hinders evolution of the disease. This occurs, because fixation of a new strain of a illness is slowed down in such networks. Central individuals are usually infected by the older strain and thus not susceptible to the new version.

”Lower fixation probability results in slower adaptation when mutations are rare. Hence, heterogeneous contact structure acts to suppress selection for infectious diseases, despite facilitating initial spread,” the biologists explain.

Article: Gabriel E. Leventhal, Alison L. Hill, Martin A. Nowak & Sebastian Bonhoeffer, 2014, source link.

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