A Reed-Frost model taking into account uncertainties in the diagnostic of the infection.
In this paper, we model the epidemic course of a pathogen infection within a semi-closed group which generates clinical signals which do not necessarily permit its ready and certain identification. Typical examples of such a pathogen are influenza-type viruses. We allow for time-varying infectivity levels among individuals, and model the probability of infection per contact as a function of the clinical signals. In order to accomplish this, we introduce a modified chain-binomial Reed-Frost model. We obtain an expression for the basic reproduction ratio and determine conditions which guarantee that the epidemic does not survive in the long-term. These conditions being functions of the signal's distribution, they can be used to design and evaluate interventions, such as treatment protocols.
De Menezes
Renée X
RX
Department of Medical Statistics, Leiden University Medical Centre, Postbus 9604, 2300 RC Leiden, The Netherlands. r.x.menezes@lumc.nl
Ortega
Neli R S
NR
Massad
Eduardo
E
D004196:Disease Outbreaks; D006801:Humans; D007239:Infections / Q000175:diagnosis* / Q000453:epidemiology*; D007251:Influenza, Human / Q000175:diagnosis / Q000453:epidemiology; D008954:Models, Biological; D015233:Models, Statistical; D009975:Orthomyxoviridae / Q000254:growth & development