In the SIMS model, star-like mutational clusters cause oscillatory seasonal outbreaks while lattice-like networks give stable endemic states, and simulated strain emergence order correlates with H3N2 sampling times.
How host mobility patterns shape antigenic escape during viral-immune co-evolution
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abstract
Viruses like influenza have long coevolved with host immune systems, gradually shaping the evolutionary trajectory of these pathogens. Host immune systems develop immunity against circulating strains, which in turn avoid extinction by exploiting antigenic escape mutations that render new strains immune from existing antibodies in the host population. Infected hosts are also mobile, which can spread the virus to regions without developed host immunity, offering additional reservoirs for viral growth. While the effects of migration on long term stability have been investigated, we know little about how antigenic escape coupled with migration changes the survival and spread of emerging viruses. By considering the two processes on equal footing, we show that on short timescales an intermediate host mobility rate increases the survival probability of the virus through antigenic escape. We show that more strongly connected migratory networks decrease the survival probability of the virus. Using data from high traffic airports we argue that current human migration rates are beneficial for viral survival.
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Genotype networks drive oscillating endemicity and epidemic trajectories in viral evolution
In the SIMS model, star-like mutational clusters cause oscillatory seasonal outbreaks while lattice-like networks give stable endemic states, and simulated strain emergence order correlates with H3N2 sampling times.