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Epidemiology: Modeling of Natural History

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Hepatitis C: Epidemiology, Prevention and Elimination

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Abstract

Models have been widely employed, in particular in infectious diseases, to provide a simplified representation of complex phenomena. They consist of three important ingredients: disease stages, allowed transitions between stages, and corresponding stage-specific transition probabilities. This chapter reviews the approaches that have been used to model the natural history of chronic hepatitis C (CHC). A commonly used approach is to consider disease progression through successive fibrosis stages to cirrhosis, and other serious sequelae, assuming stage-specific fibrosis progression rates. The Markov maximum likelihood method allows to estimate progression rates between successive fibrosis stages even when only data on a single biopsy and known duration of infection are available. Models are important at an individual level, as they produce individualized information on the risk of disease progression and also at population level as they allow to project future liver disease burden in a given population.

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Authors and Affiliations

  1. Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece

    Vana Sypsa

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  1. Vana Sypsa
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Correspondence to Vana Sypsa .

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Editors and Affiliations

  1. Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens Medical School, Athens, Greece

    Angelos Hatzakis

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Sypsa, V. (2021). Epidemiology: Modeling of Natural History. In: Hatzakis, A. (eds) Hepatitis C: Epidemiology, Prevention and Elimination . Springer, Cham. https://doi.org/10.1007/978-3-030-64649-3_8

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