For a number of infections, previous exposure to different strains of the infection can be an important determinant of eventual outcome of infection, whether as a result of a degree cross-immunity between closely related strains which might therefore mitigate the seriousness of disease (e.g., influenza) or, as appears to be the case for dengue virus, a degree of ''antigenic enhancement'' resulting in increased morbidity (e.g., dengue hemorrhagic shock syndrome). Transmission dynamics models are eminently suitable for the investigation of the epidemiology arising from such phenomena, and there are a number of examples in the literature (e.g., Koella and Antia, 2003; Turner and Garnett, 2002), although as the possible number of co-circulating strains of an infection increases, the complexity of such models increases greatly and the difficulty in providing satisfactory estimates for the increasing number of parameters greatly increases. Another aspect of strain variation which can usefully be tackled using these types of models relates to the evolution of resistance to control measures in some strains but not in others. Here modeling can provide insights in a number of ways, such as how long it might take for the less controlled or uncontrolled strain to predominate or how best control measures might be designed to counter the danger of emergence of new strains (Wilson et al., 2000).
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