Cliff OM, McLean N, Sintchenko V, Fair KM, Sorrell TC, Kauffman S, & Prokopenko, M.
PLoS Comput Biol 16(10): e1008401
We study emergence and evolution of foodborne pathogens, and provide a new method for public health surveillance dealing with genetically diverse and spatiotemporally distributed epidemic scenarios. The proposed method interprets the surveillance data through genotype networks, and discovers how the most dominant strains of infection emerge and adapt. The approach allows us to correlate the strength of epidemics with genetic features of observed pathogens. This could open a way to predict and contain epidemics closer to their source, enabling more timely and precise allocations of public health resources, as well as efficient interventions during epidemics. This should make a significant economic and social impact, improving health of the population, while also safeguarding national and international supply chains.