Acute Musculoskeletal Pain – Epidemiology – Epidemiology – Acute Musculoskeletal Pain – Mature markets
Clarivate Epidemiology’s coverage of acute musculoskeletal pain (AMP) comprises epidemiological estimates of key patient populations in the major mature pharmaceutical markets (the United States, France, Germany, Italy, Spain, the United Kingdom, and Japan). We report the prevalence of AMP 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 covered in this report.
Clarivate Epidemiology’s AMP forecast will answer the following question:
- How will demographic trends, such as population aging and improving life expectancy, affect the epidemiology of AMP over the forecast period?
All forecast data are available on the Clarivate 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 total, Clarivate Epidemiology forecasts three patient populations, as follows:
- Total prevalent cases of acute and subacute low back pain (LBP).
- Total prevalent cases of acute and subacute neck pain.
- Total prevalent cases of acute and subacute musculoskeletal pain by site.
Note: Coverage may vary by country.
Table of contents
- Acute Musculoskeletal Pain - Epidemiology - Epidemiology - Acute Musculoskeletal Pain - Mature markets
- Epidemiology Data
- Methods
- Literature review (studies included in/excluded from the analyses of acute musculoskeletal pain)
- Total prevalent cases of acute and subacute low back pain
- Total prevalent cases of acute and subacute neck pain
- Total prevalent cases of acute and subacute musculoskeletal pain by number of sites
- Risk/protective factors applied to disease forecast models
- Reference Materials
