Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model

Xue Feng Hu,Hing Man Chan,Kue Young

doi:10.1186/s12874-016-0288-y

Xue Feng Hu, Hing Man Chan + Show 1 more

Open Access

https://doi.org/10.1186/s12874-016-0288-y

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Abstract

BackgroundDisease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and expensive; the latter is not available in most developing countries. Alternatively, mathematical models could be used to estimate disease incidence from prevalence.MethodsWe proposed and validated a method to estimate the age-standardized incidence of cardiovascular disease (CVD), with prevalence data from successive surveys and mortality data from empirical studies. Hallett’s method designed for estimating HIV infections in Africa was modified to estimate the incidence of myocardial infarction (MI) in the U.S. population and incidence of heart disease in the Canadian population.ResultsModel-derived estimates were in close agreement with observed incidence from cohort studies and population surveillance systems. This method correctly captured the trend in incidence given sufficient waves of cross-sectional surveys. The estimated MI declining rate in the U.S. population was in accordance with the literature. This method was superior to closed cohort, in terms of the estimating trend of population cardiovascular disease incidence.ConclusionIt is possible to estimate CVD incidence accurately at the population level from cross-sectional prevalence data. This method has the potential to be used for age- and sex- specific incidence estimates, or to be expanded to other chronic conditions.

Highlights

Disease incidence and prevalence are both core indicators of population health
Hospitalized myocardial infarction (MI) incidence data were based on 26 States which participated in the Centers for Disease Control and Prevention (CDC) environmental public health tracking program [16]
Linear regression showed that the MI incidence decreased by approximately 32 (1/100,000) each year since 2000

Summary

Introduction

Disease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and expensive; the latter is not available in most developing countries. The most direct approach to estimating cardiovascular disease incidence is through longitudinal observational studies. Such studies are time-consuming, expensive, and are disease specific. Electronic health record systems and disease registry systems provide new sources of incidence estimates, but these are not available in most of the developing countries. Incidence could be estimated by mathematical models, with prevalence data at multiple time points, population demographic change, and mortality as fundamental input. The assumptions in this model were based on the HIV epidemic in Africa, and may not be applicable for cardiovascular diseases in a developed country

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