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Modern data and computational resources, coupled with algorithmic and theoretical advances to exploit these, allow disease dynamic models to be parameterised with increasing detail and accuracy. While this enhances models' usefulness in prediction and policy, major challenges remain. In particular, lack of identifiability of a model's parameters may limit the usefulness of the model. While lack of parameter identifiability may be resolved through incorporation into an inference procedure of prior knowledge, formulating such knowledge is often difficult. Furthermore, there are practical challenges associated with acquiring data of sufficient quantity and quality. Here, we discuss recent progress on these issues.

An efficient method for Bayesian model selection is presented for a broad class of continuous-time Markov chain models and is subsequently applied to two important problems in epidemiology. The first problem is to identify the shape of the infectious period distribution; the second problem is to determine whether individuals display symptoms before, at the same time, or after they become infectious. In both cases we show that the correct model can be identified, in the majority of cases, from symptom onset data generated from multiple outbreaks in small populations. The method works by evaluating the likelihood using a particle filter that incorporates a novel importance sampling algorithm designed for partially-observed continuous-time Markov chains. This is combined with another importance sampling method to unbiasedly estimate the model evidence. These come with estimates of precision, which allow for stopping criterion to be employed. Our method is general and can be applied to a wide range of model selection problems in biological and epidemiological systems with intractable likelihood functions.

Salicylate therapy has been in use for over half a century for the treatment of acute rheumatic fever, and opinions have varied among clinicians as to the mode of action and the value of the salicyl compounds. Although most authorities have agreed that these drugs exert definite antipyretic and analgesic actions, few have maintained that salicylates actually modify the course of the disease. Tremendous interest has been aroused, therefore, by Coburn's recent report1that massive doses of sodium salicylate produce a prompt subsidence of rheumatic inflammation if a level of blood salicyl (measured as salicylic acid) above 350 micrograms per cubic centimeter is maintained. To maintain such a level, Coburn advocated the daily administration of from 10 to 20 Gm. of the drug. This amount exceeds the toxic and even the fatal dose as given in some textbooks of pharmacology.2 Numerous reports of salicylate poisoning in children have