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• W2000940858 abstract "Most studies on susceptible-infected-susceptible epidemics in networks implicitly assume Markovian behavior: the time to infect a direct neighbor is exponentially distributed. Much effort so far has been devoted to characterize and precisely compute the epidemic threshold in susceptible-infected-susceptible Markovian epidemics on networks. Here, we report the rather dramatic effect of a nonexponential infection time (while still assuming an exponential curing time) on the epidemic threshold by considering Weibullean infection times with the same mean, but different power exponent $ensuremath{alpha}$. For three basic classes of graphs, the Erdifmmode mbox{H{o}}else H{o}fi{}s-R'enyi random graph, scale-free graphs and lattices, the average steady-state fraction of infected nodes is simulated from which the epidemic threshold is deduced. For all graph classes, the epidemic threshold significantly increases with the power exponents $ensuremath{alpha}$. Hence, real epidemics that violate the exponential or Markovian assumption can behave seriously differently than anticipated based on Markov theory." @default.
• W2000940858 created "2016-06-24" @default.
• W2000940858 creator A5027156094 @default.
• W2000940858 creator A5033227174 @default.
• W2000940858 date "2013-03-05" @default.
• W2000940858 modified "2023-10-05" @default.
• W2000940858 title "Non-Markovian Infection Spread Dramatically Alters the Susceptible-Infected-Susceptible Epidemic Threshold in Networks" @default.
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• W2000940858 doi "https://doi.org/10.1103/physrevlett.110.108701" @default.
• W2000940858 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23521310" @default.
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