Bayesian model assessment for stochastic epidemic models
Alharthi, Muteb (2016) Bayesian model assessment for stochastic epidemic models. PhD thesis, University of Nottingham.
Acrucial practical advantage of infectious diseases modelling as a public health tool lies in its application to evaluate various disease-control policies. However, such evaluation is of limited use, unless a sufficiently accurate epidemic model is applied. If the model provides an adequate fit, it is possible to interpret parameter estimates, compare disease epidemics and implement control procedures. Methods to assess and compare stochastic epidemic models in a Bayesian framework are not well-established, particularly in epidemic settings with missing data.
Actions (Archive Staff Only)