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• W1973784405 abstract "In the last three decades, the appreciation of the role of infections in cancer aetiology has greatly expanded. Among the 13 million new cancer cases that occurred worldwide in 2008, around 2 million (16%) were attributable to infections. Concurrently, the approach to prevention of infection-related cancers is shifting from cancer control to infection control, for example, vaccination and the detection of infected individuals. In support of this change, the use of infection transmission models has entered the field of infection-related cancer epidemiology. These models are useful to understand the infection transmission processes, to estimate the key parameters that govern the spread of infection, and to project the potential impact of different preventive measures. However, the concepts, terminology, and methods used to study infection transmission are not yet well known in the domain of cancer epidemiology. This review aims to concisely illustrate the main principles of transmission dynamics, the basic structure of infection transmission models, and their use in combination with empirical data. We also briefly summarise models of carcinogenesis and discuss their specificities and possible integration with models of infection natural history." @default.
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• W1973784405 date "2013-12-03" @default.
• W1973784405 modified "2023-10-16" @default.
• W1973784405 title "Infection transmission and chronic disease models in the study of infection-associated cancers" @default.
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• W1973784405 doi "https://doi.org/10.1038/bjc.2013.740" @default.
• W1973784405 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3887312" @default.
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