| Summary: | The development of models and surveillance systems to give early warning of a new or re-emerging disease is an important first step in devising control strategies to protect the public health. In this chapter, we discuss and illustrate modelling and surveillance approaches to (re-)emerging disease detection before considering in Chapter 11 what control strategies might be used to mitigate new threats. We begin by reviewing in Section 10.2.1 the generic SIR (susceptible ⇒ infected ⇒ removed) mass action models commonly used to model the spread of infectious diseases in human and many animal populations, before moving on to present a robust spatial derivative, the so-called swash–backwash model (Section 10.2.2). This model is applied in Section 10.3 to data from France, Iceland, and a small English town, Cirencester, to show, for the cyclically reemerging disease of influenza, how the model readily separates pandemic years from the normal run of influenza seasons. While it is encouraging that the model can spot pandemic years in the train of annual epidemics, influenza is an odd disease in that pandemics occur when a new strain of the causative A virus emerges to afflict the human population. To test the model further, we apply it in Section 10.4 to a set of 14 measles waves for Iceland, 1916–75, waves caused by an unchanging virus in a changing population. Our discussion of the swash–backwash model is concluded in Section 10.5, where it is shown how it can be used as part of a real-time surveillance-based earlywarning system for new disease threats. Any modelling approach to identifying newly emergent or re-emerging diseases can only be as good as the data which are supplied to the models. Accordingly, in Section 10.6, advances in surveillance methodology are outlined which have been facilitated by developments in communications technology, especially the Internet. The chapter is concluded in Section 10.7.
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