title: Parameter identification in epidemic models.
abstract: Starting from a recent paper of Pollicott, Wang and Weiss we try to obtain improved representation formulas for the estimation of the time-dependent transmission rate of an epidemic in terms of either incidence or prevalence data. Although the formulas are (trivially) mathematically equivalent to previous formulas, the new representations need no additional estimates and they should be more stable numerically. We review the discrete time and the stochastic continuous time approach. We replace the assumption that recovery follows an exponential distribution and get estimates for the transmission rate for constant duration of the infectious phase.
authors.affiliation: School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85287, USA. hadeler@uni-tuebingen.de
authors.forename: K P
authors.initials: KP
authors.lastname: Hadeler
mesh_terms: D000465:Algorithms; D003141:Communicable Diseases / Q000453:epidemiology* / Q000635:transmission*; D003710:Demography; D006801:Humans; D015994:Incidence; D016013:Likelihood Functions; D008954:Models, Biological; D015995:Prevalence; D013269:Stochastic Processes; D013997:Time Factors