Modelling the epidemiology of infectious diseases for decision analysis: a primer

Abstract

The number of economic evaluations related to infectious disease topics has increased over the last 2 decades. However, many such evaluations rely on models that do not take into account unique features of infectious diseases that can affect the estimated value of interventions against them. These include their transmissibility from infected to susceptible individuals, the possibility of acquiring natural immunity following recovery from infection and the uncertainties that arise as a result of their complex natural history and epidemiology. Modellers conducting economic evaluations of infectious disease interventions need to know the main features of different types of infectious disease models, the situations in which they should be applied and the effects of model choices on the cost effectiveness of interventions.

Fig. 1

Number of articles found on model-based economic evaluations that are infection and non-infection related, according to year of publication. Percentages on top of each bar show the proportion of articles that are infection related. See Appendix 1 for search terms used.

Fig. 2

Dynamic and static model predictions about changes to varicella incidence following the introduction of an infant immunization programme. Initially, following vaccination, there is a honeymoon period where incidence drops rapidly, but accumulation of susceptible individuals eventually causes a sharp temporary increase in incidence (post-honeymoon epidemic) before infection reaches a new equilibrium (post-vaccination equilibrium). Assumptions: infant vaccination with 80% coverage and a perfect vaccine (100% protection for life).

Fig. 3

Flow diagram showing how the choice of a static model, static model with approximation for herd immunity or dynamic model could be made based on answers to seven key questions.

Fig. 4

Timeline for the natural history of (a) infection and (b) disease, together with (c) corresponding model structures. In (c), direct lines indicate movement between health states, while dotted lines indicate that the rate at which susceptible individuals are infected is influenced by the proportion of the population that is infectious. SEIR = susceptible-exposed-infectious-recovered; SIR = susceptible-infectious-recovered; SIRS = susceptible-infectious-recovered-susceptible; SIS = susceptible-infectious-susceptible.