DRG Epidemiology’s coverage of hepatitis C virus (HCV) comprises epidemiological estimates of key patient populations in 45 countries worldwide. We report both the incidence and prevalence of HCV for each country, as well as annualized case counts projected to the national population.
DRG Epidemiology’s HCV forecast will answer the following questions:
- Of all people with HCV, how many in each country have been formally diagnosed?
- Of all people diagnosed with HCV, how many in each country are drug-treated?
- How will demographic trends, such as population aging and improving life expectancy, affect the epidemiology of HCV 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, we provide a graph of the patient flow between or within different disease states for the countries considered in this report. These patient-flow diagrams are provided at the regional level but may be requested for any specific country or forecast year.
DRG Epidemiology provides at least ten years of forecast data for the following HCV patient populations:
- Total prevalent cases by viremic status.
- Diagnosed prevalent cases by drug-treated status.
- Total incident and prevalent cases of HCV.
- Total prevalent cases of HCV.
Note: Coverage may vary by country and region.
- Hepatitis C Virus - Epidemiology - Emerging Markets Data
- Key Findings
- Prevalence of Hepatitis C Virus per 1,000 People of All Ages per Year in 2017 and 2027
- Relative Sizes of the Contributing Factors to the Trend in Prevalent Cases of Hepatitis C Virus over the Next Ten Years
- Analysis of the Prevalent Cases of Hepatitis C Virus in 2017 by Genotype
- Analysis of the Prevalent Cases of Hepatitis C Virus in 2017 by Diagnosed and Drug-Treated Status
- Key Findings
- Epidemiology Data
- Total Seroprevalent Cases
- Total Incident Cases
- Total Prevalent Viremic Cases
- HCV Genotype Prevalence
- Cirrhotic Status by Genotype
- Diagnosed Prevalent Cases
- Drug-Treated Prevalent Cases
- Reference Materials
- Literature Review
- Studies Included in the Analysis of HCV
- Studies Excluded from the Analysis of HCV
- Risk/Protective Factors
- Risk/Protective Factors for Hepatitis C Virus
- Literature Review
Author(s): Ruchika Sharma, MPH; Mike Hughes, MSc, PhD
Ruchika Sharma joined Decision Resources Group as Associate Epidemiologist in May 2016. She performs fully documented systematic reviews of both published and grey literature on the epidemiology of assigned diseases and their risk factors to estimate incidence/prevalence over a 10-30 year period. She produces analyses for pharmaceutical drug developers on the descriptive epidemiology of major drug indications in mature and developing markets.
She holds a Master of Public Health degree from School of Public Health, Post-Graduate Institute of Medical Education and Research, and a Bachelor of Dental Surgery from MN DAV Dental College & Hospital.She has previously worked as a dental surgeon and as a Fellow at the National Health Systems Resource Centre, where she supported the preparation of National Health Accounts - Guidelines for India 2016.
Mike joined Decision Resources as an epidemiologist in 2006. He has many years’ experience in the mathematical modeling of healthcare service delivery, cardiovascular and cancer epidemiology, biostatistics, meta-analysis and systematic reviewing.
He has been principal author on many published articles in leading international journals in the areas of risk modeling in intensive care and cardiovascular medicine. He has also been responsible for developing national guidelines on behalf of NICE and the American College of Chest Physicians for the treatment of atrial fibrillation, stroke and hypertension. He is particularly interested in modeling patient flows in cancer and methods for forecasting disease burden in non-communicable epidemiology.
Dr. Hughes received his Ph.D. in risk modeling in intensive care in 2003 from City University, London and is currently enrolled in a Ph.D. program in statistical causation and foundations of probability theory at the University of Nottingham.