DRG Epidemiology's coverage of CHF comprises epidemiological estimates of key patient populations across 45 countries worldwide. We report the diagnosed prevalence of CHF for each country, as well as annualized case counts projected to the national population.

Most patient populations are forecast over a period of 20 years for the major mature pharmaceutical markets and 10 years for the other countries covered in this content.

DRG Epidemiology's CHF forecast will answer the following questions:

  • Of all people diagnosed with CHF, how many in each country across the major mature pharmaceutical markets are drug-treated?
  • How will demographic trends, such as population aging and improving life expectancy, affect the epidemiology of CHF over the forecast period?

All forecast data are available on the DRG Insights Platform in tabular format, with options to download to MS Excel. All populations are accompanied by a comprehensive description of the methods and data sources used, with hyperlinks to external sources. A summary evidence table generated as part of our systematic review of the epidemiological literature is also provided for full transparency into research and methods.

In addition to the total number of cases for each forecast year, DRG Epidemiology also provides at least ten years of forecast data for the following CHF subpopulations:

  • Diagnosed prevalent cases of CHF by comorbid AF.
  • Diagnosed prevalent cases of CHF by comorbid COPD.
  • Diagnosed prevalent cases of CHF by comorbid diabetes.
  • Diagnosed prevalent cases of CHF by comorbid hypertension.
  • Diagnosed prevalent cases of CHF by comorbid CHD.
  • Diagnosed prevalent cases of CHF by comorbid dyslipidemia.
  • Diagnosed prevalent cases of CHF by history of a MI.
  • Diagnosed prevalent cases of CHF by history of strokes.
  • Diagnosed prevalent cases of CHF by comorbid obesity.
  • Diagnosed prevalent CHF cases by NYHA-functional classification status.
  • Diagnosed prevalent CHF cases by reduced and mid-range EF.
  • … and more (details available on request).

Note: Coverage may vary by country.

Table of contents

  • Chronic Heart Failure - Epidemiology - Mature Markets Data
    • Introduction
      • Diagnosed Prevalence of Chronic Heart Failure per 1,000 Among People Aged 20+ in 2017 and 2037
      • Relative Sizes of the Factors Contributing to the Trend in Prevalent Cases of Chronic Heart Failure over the Next 20 Years
      • Analysis of Diagnosed Prevalent Cases of Chronic Heart Failure by Ejection Fraction
      • Analysis of the Diagnosed Prevalent Cases of Chronic Heart Failure by Drug-Treated Status
    • Epidemiology Data
    • Methods
      • Diagnosed Prevalent Cases
      • Diagnosed Prevalent Cases by NYHA Classification
      • Diagnosed Prevalent CHF Cases with Atrial Fibrillation
      • Diagnosed Prevalent CHF Cases with Chronic Obstructive Pulmonary Disease
      • Diagnosed Prevalent CHF Cases with Coronary Heart Disease
      • Diagnosed Prevalent CHF Cases with Diabetes
      • Diagnosed Prevalent CHF Cases with Dyslipidemia
      • Diagnosed Prevalent CHF Cases with History of Myocardial Infarction
      • Diagnosed Prevalent CHF Cases with History of Stroke
      • Diagnosed Prevalent CHF Cases with Hypertension
      • Diagnosed Prevalent CHF Cases with Obesity
      • Diagnosed Prevalent Cases of Chronic Heart Failure Classified by Ejection Fraction
      • Percentage Drug-Treated
    • Reference Materials
      • Literature Review
        • Studies Included in the Analysis of Chronic Heart Failure
        • Studies Excluded from the Analysis of Chronic Heart Failure
      • Risk/Protective Factors
        • Risk/Protective Factors for Chronic Heart Failure

Author(s): Sunali D. Goonesekera, S.M.

Sunali Goonesekera, S.M., is a senior epidemiologist at DRG, part of Clarivate. Prior to joining DRG, Ms. Goonesekera conducted epidemiological research on racial/ethnic disparities in metabolic diseases at the New England Research Institute and lead-authored two manuscripts. She has contributed to multiple publications in peer-reviewed journals in epidemiology and the biological sciences. She holds a master’s degree in epidemiology from the Harvard School of Public Health and a B.A. in biology (Honors) from Dartmouth College.


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