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BMC Medical Research Methodology
Published in: BMC Medical Research Methodology 1/2019

Open Access 01-12-2019 | Hypertension | Research Article

Analysing detection of chronic diseases with prolonged sub-clinical periods: modelling and application to hypertension in the U.S.

Authors: Ralph Brinks, Sophie Kaufmann, Annika Hoyer, Edward W Gregg, Jürgen Saal

Published in: BMC Medical Research Methodology | Issue 1/2019

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Abstract

Background

We recently introduced a system of partial differential equations (PDEs) to model the prevalence of chronic diseases with a possibly prolonged state of asymptomatic, undiagnosed disease preceding a diagnosis. Common examples for such diseases include coronary heart disease, type 2 diabetes or cancer. Widespread application of the new method depends upon mathematical treatment of the system of PDEs.

Methods

In this article, we study the existence and the uniqueness of the solution of the system of PDEs. To demonstrate the usefulness and importance of the system, we model the age-specific prevalence of hypertension in the US 1999–2010.

Results

The examinations of mathematical properties provide a way to solve the systems of PDEs by the method of characteristics. In the application to hypertension, we obtain a good agreement between modeled and surveyed age-specific prevalences.

Conclusions

The described system of PDEs provides a practical way to examine the epidemiology of chronic diseases with a state of undiagnosed disease preceding a diagnosis.
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Metadata
Title
Analysing detection of chronic diseases with prolonged sub-clinical periods: modelling and application to hypertension in the U.S.
Authors
Ralph Brinks
Sophie Kaufmann
Annika Hoyer
Edward W Gregg
Jürgen Saal
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2019
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-019-0845-2

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