DRG Epidemiology’s coverage of Huntington’s disease (HD) comprises epidemiological estimates of key patient populations in seven emerging pharmaceutical markets (Brazil, Russia, India, China, Mexico, Turkey, and South Korea). We report the prevalence of the disease for each country, as well as annualized case counts projected to the national population.
DRG Epidemiology’s HD forecast will answer the following questions:
- How will demographic trends, such as population aging and improving life expectancy, affect the epidemiology of HD 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 provided for full transparency into research and methods.
In addition to the total number of cases for each forecast year, DRG Epidemiology provides at least ten years of forecast data for the following HD subpopulations:
- Diagnosed prevalence of premanifest HD.
- Diagnosed prevalence of manifest HD.
- Diagnosed incident cases of manifest HD.
- Diagnosed population at risk.
- Diagnosed prevalence of manifest HD by disease stage.
Note: Coverage may vary by country.
- Huntington's Disease - Epidemiology - Emerging Markets
- Key Findings
- Diagnosed Prevalent Cases of Manifest Huntington's Disease per 100,000 People of All Ages in 2019 and 2029
- Patient-Flow Diagram for Huntington's Disease in All Countries Under Study in 2019
- Relative Sizes of the Contributing Factors to the Trend in Diagnosed Prevalent Cases of Manifest Huntington's Disease over the Next Ten Years
- Epidemiology Data
- Diagnosed Population at Risk for Huntington's Disease
- Diagnosed Incident Cases of Manifest Huntington's Disease
- Diagnosed Prevalent Cases of Huntington's Disease
- Diagnosed Prevalence of Huntington's Disease by Manifest Status
- Diagnosed Prevalent Cases of Manifest Huntington's Disease by Disease Stage
- Reference Materials
- Literature Review
- Studies Included in the Analysis of Huntington's Disease
- Studies Excluded from the Analysis of Huntington's Disease
- Risk/Protective Factors
- Risk/Protective Factors for Huntington's Disease
- Literature Review
Author(s): Nishant Kumar, MPH; Mike Hughes, MSc, PhD
Nishant is a senior epidemiologist and head of oncology within the epidemiology team at Decision Resources Group. He also covers some CNS diseases, including Alzheimer’s disease and dementia. His key interests are developing interactive patient flows, and modelling disease progression to forecast commercially relevant drug-treatable incident and prevalent populations. Nishant also spends a lot of time collaborating with clients to help answer more specific questions through custom work and consulting projects.
His qualifications include an MSc in Public Health with specialization in epidemiology and statistics from King’s College London, and a BSc in Medical Studies from the University of Birmingham.
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.