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Change rates and prevalence of a dichotomous variable: simulations and applications.

Brinks R, Landwehr S - PLoS ONE (2015)

Bottom Line: The transitions between the states are described by change rates, which depend on calendar time and on age.We develop a partial differential equation (PDE) that simplifies the use of the three-state model.In two further applications, the PDE may provide insights into smoking behaviour of males in Germany and the knowledge about the ovulatory cycle in Egyptian women.

View Article: PubMed Central - PubMed

Affiliation: Institute for Biometry and Epidemiology, German Diabetes Center, Duesseldorf, Germany.

ABSTRACT
A common modelling approach in public health and epidemiology divides the population under study into compartments containing persons that share the same status. Here we consider a three-state model with the compartments: A, B and Dead. States A and B may be the states of any dichotomous variable, for example, Healthy and Ill, respectively. The transitions between the states are described by change rates, which depend on calendar time and on age. So far, a rigorous mathematical calculation of the prevalence of property B has been difficult, which has limited the use of the model in epidemiology and public health. We develop a partial differential equation (PDE) that simplifies the use of the three-state model. To demonstrate the validity of the PDE, it is applied to two simulation studies, one about a hypothetical chronic disease and one about dementia in Germany. In two further applications, the PDE may provide insights into smoking behaviour of males in Germany and the knowledge about the ovulatory cycle in Egyptian women.

No MeSH data available.


Related in: MedlinePlus

Prevalence of dementia.Age-specific prevalence of dementia in the simulated data (crosses, with 95% confidence bounds) and published values (diamonds, [12]).
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pone.0118955.g003: Prevalence of dementia.Age-specific prevalence of dementia in the simulated data (crosses, with 95% confidence bounds) and published values (diamonds, [12]).

Mentions: For each of the 457,000 persons, we have simulated the date of birth, the age of a possible diagnosis and the age of death. To cross-check these results of the simulation, we compare the age-specific prevalence of dementia in the year 2000 with published values for 2002 [12]. Fig. 3 shows the good agreement between the simulated and the reported prevalence.


Change rates and prevalence of a dichotomous variable: simulations and applications.

Brinks R, Landwehr S - PLoS ONE (2015)

Prevalence of dementia.Age-specific prevalence of dementia in the simulated data (crosses, with 95% confidence bounds) and published values (diamonds, [12]).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4352043&req=5

pone.0118955.g003: Prevalence of dementia.Age-specific prevalence of dementia in the simulated data (crosses, with 95% confidence bounds) and published values (diamonds, [12]).
Mentions: For each of the 457,000 persons, we have simulated the date of birth, the age of a possible diagnosis and the age of death. To cross-check these results of the simulation, we compare the age-specific prevalence of dementia in the year 2000 with published values for 2002 [12]. Fig. 3 shows the good agreement between the simulated and the reported prevalence.

Bottom Line: The transitions between the states are described by change rates, which depend on calendar time and on age.We develop a partial differential equation (PDE) that simplifies the use of the three-state model.In two further applications, the PDE may provide insights into smoking behaviour of males in Germany and the knowledge about the ovulatory cycle in Egyptian women.

View Article: PubMed Central - PubMed

Affiliation: Institute for Biometry and Epidemiology, German Diabetes Center, Duesseldorf, Germany.

ABSTRACT
A common modelling approach in public health and epidemiology divides the population under study into compartments containing persons that share the same status. Here we consider a three-state model with the compartments: A, B and Dead. States A and B may be the states of any dichotomous variable, for example, Healthy and Ill, respectively. The transitions between the states are described by change rates, which depend on calendar time and on age. So far, a rigorous mathematical calculation of the prevalence of property B has been difficult, which has limited the use of the model in epidemiology and public health. We develop a partial differential equation (PDE) that simplifies the use of the three-state model. To demonstrate the validity of the PDE, it is applied to two simulation studies, one about a hypothetical chronic disease and one about dementia in Germany. In two further applications, the PDE may provide insights into smoking behaviour of males in Germany and the knowledge about the ovulatory cycle in Egyptian women.

No MeSH data available.


Related in: MedlinePlus