title: Simulation of a viral epidemic by means of a neural network.
abstract: The neurons of the network used for the simulation of a viral epidemic correspond to the individuals of the community. The activation state of the neurons reflects the contagious state of the diseased persons. Variable thresholds are introduced for the differentiation of the neuronal non-activation states (susceptible or immune subjects). The thresholds are calculated depending on the cumulated values over time of the neural activation states. The network functions synchronously. In order to follow up the state of the neural network, recurrence relations were introduced. They were applied in two epidemiological situations which differ from each other by the spreading intensity of the virus over time, reflected by the particular values ascribed to the elements of the neural connection matrix.
authors.affiliation: Stefan S. Nicolau Institute of Virology, Bucharest, Romania.
authors.forename: A
authors.initials: A
authors.lastname: Cristea
authors.forename: C N
authors.initials: CN
authors.lastname: Zaharia
mesh_terms: D002648:Child; D003198:Computer Simulation; D004196:Disease Outbreaks; D006801:Humans; D016571:Neural Networks, Computer; D014777:Virus Diseases / Q000453:epidemiology*