ArticleMathematical biosciences2019
A forecasting model of disease prevalence based on the McKendrick-von Foerster equation.
Article in Mathematical biosciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Forecasting prevalence and mortality of Alzheimer's disease using the partitioning models.Experimental gerontology · 2023Article
- Geographic disparities in mortality from Alzheimer's disease and related dementias.Journal of the American Geriatrics Society · 2021Article
- Partitioning of time trends in prevalence and mortality of bladder cancer in the United States.Annals of epidemiology · 2020Article
- Partitioning of time trends in prevalence and mortality of lung cancer.Statistics in medicine · 2019Article
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7 authors.
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Abstract
A new model for disease prevalence based on the analytical solutions of McKendric-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.
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