Limited data on infectious disease distribution exposes ambiguity in epidemic modeling choices
Laura Di Domenico,
Eugenio Valdano,
Vittoria Colizza
Abstract:Traditional disease transmission models assume that the infectious period is exponentially distributed with a recovery rate fixed in time and across individuals. This assumption provides analytical and computational advantages, however, it is often unrealistic when compared to empirical data. Current efforts in modeling nonexponentially distributed infectious periods are either limited to special cases or lead to unsolvable models. Also, the link between empirical data (the infectious period distribution) and … Show more
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