DRG Epidemiology's coverage of insomnia comprises epidemiological estimates of key patient populations across the major mature pharmaceutical markets (United States, France, Germany, Italy, Spain, United Kingdom, and Japan). We report the prevalence of insomnia 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 report.
DRG Epidemiology's insomnia forecast will answer the following questions:
- Of all people diagnosed with insomnia, 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 insomnia 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 provides at least ten years of forecast data for the following insomnia subpopulations:
- Total DSM-IV prevalent cases by anxiety and mood disorders comorbidity status.
- Total DSM-V prevalent cases by anxiety and mood disorders comorbidity status.
- Total DSM-IV prevalent cases by obstructive sleep apnea comorbidity status.
- Total DSM-V prevalent cases by obstructive sleep apnea comorbidity status.
- Total DSM-V prevalent cases by drug-treated status.
Note: Coverage may vary by country.
- Insomnia - Epidemiology - Europe
- Key Findings
- Total Prevalence Estimates of Insomnia per 100 People Aged 15+ years in 2018 and 2028
- Relative Sizes of the Contributing Factors to the Trend in Total Prevalent Cases of Insomnia over the Next 10 Years
- Epidemiology Data
- Total DSM-V Prevalent Cases
- Total DSM-IV Prevalent Cases
- Comorbidity Cases
- Reference Materials
- Literature Review
- Studies Included in the Analysis of Insomnia
- Studies Excluded from the Analysis of Insomnia
- Risk/Protective Factors
- Risk/Protective Factors for Insomnia
- Literature Review
Author(s): Swarali Tadwalkar; Mike Hughes, MSc, PhD
Swarali joined Decision Resources Group (DRG) in 2016 and with the Epidemiology team develops epidemiological populations forecasts for different infectious and non-communicable diseases with her particular interests in the oncology space.
Prior to joining DRG, she has been extensively involved in primary and secondary healthcare research. Her experience involves projects in digital health, health policy and management, and health economics and outcomes research (HEOR). She has also coordinated various non-governmental public health projects focusing in hepatitis and human papilloma virus treatment access. Swarali holds a Masters in Public Health (Epidemiology) degree from the University of South Florida, Tampa.
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.