Akushevich, I.; Yashkin, A.; Kravchenko, J.; Fang, F.; Arbeev, K.; Sloan, F.; Yashin, A. I. A forecasting model of disease prevalence based on the McKendrick-von Foerster equation. (English) Zbl 1425.92123 Math. Biosci. 311, 31-38 (2019). Summary: A new model for disease prevalence based on the analytical solutions of McKendrick-von Foerster’s partial differential equations is developed. Derivation of the model and methods to cross check obtained results are explicitly demonstrated. Obtained equations describe the time evolution of the healthy and unhealthy age-structured sub-populations and age patterns of disease prevalence. The projection of disease prevalence into the future requires estimates of time trends of age-specific disease incidence, relative survival functions, and prevalence at the initial age and year available in the data. The computational scheme for parameter estimations using Medicare data, analytical properties of the model, application for diabetes prevalence, and relationship with partitioning models are described and discussed. The model allows natural generalization for the case of several diseases as well as for modeling time trends in cause-specific mortality rates. Cited in 1 Document MSC: 92C60 Medical epidemiology 92D30 Epidemiology 35Q92 PDEs in connection with biology, chemistry and other natural sciences Keywords:prevalence; projections; Lee-Carter; time series; forecasting; medicare; partitioning; type II diabetes PDFBibTeX XMLCite \textit{I. Akushevich} et al., Math. Biosci. 311, 31--38 (2019; Zbl 1425.92123) Full Text: DOI Link References: [1] U.S. Census Bureau. National Population Projections: Methodology and Assumptions (2014), Population Projections Program, Population Division: Population Projections Program, Population Division U.S. Census Bureau, Washington, D.C. 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