title: Surveillance of the Incidence of Non-Communicable Diseases (NCDs) with Sparse Resources: A Simulation Study Using Data from a National Diabetes Registry, Denmark, 1995-2004.
abstract: We propose two new methods to estimate secular trends in the incidence of a chronic disease from a series of prevalence studies and mortality data. One method is a direct inversion formula, the second method is a least squares estimation. Both methods are validated in a simulation study based on data from a diabetes register. The results of the validation show that the proposed methods may be useful in epidemiological settings with sparse resources, where running a register or a series of follow-up studies is difficult or impossible.
authors.affiliation: German Diabetes Center, Institute for Biometry and Epidemiology, Duesseldorf, Germany.|University Hospital Duesseldorf, Hiller Research Unit for Rheumatology, Duesseldorf, Germany.
authors.forename: Ralph
authors.initials: R
authors.lastname: Brinks
authors.affiliation: German Diabetes Center, Institute for Biometry and Epidemiology, Duesseldorf, Germany.
authors.forename: Annika
authors.initials: A
authors.lastname: Hoyer
authors.affiliation: University Hospital Duesseldorf, Department for Statistics in Medicine, Duesseldorf, Germany.
authors.forename: Sandra
authors.initials: S
authors.lastname: Landwehr
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000453:epidemiology; D003198:Computer Simulation; D003718:Denmark / Q000453:epidemiology; D003920:Diabetes Mellitus / Q000453:epidemiology*; D006295:Health Resources; D006801:Humans; D015994:Incidence; D016018:Least-Squares Analysis; D008875:Middle Aged; D008962:Models, Theoretical; D011159:Population Surveillance; D015995:Prevalence; D012042:Registries; D015203:Reproducibility of Results