Knowledge of the frequency of disease is an important prerequisite for understanding population health, case finding, commissioning and planning services, and understanding variation in health and care. The most commonly used measure of disease frequency is *prevalence* which is an estimate of the number of cases of a given disease or risk factor in the population at a point in time (*point prevalence*) or over a given time period (*period prevalence*).

PHE working with Imperial College, commissioned a series of updated prevalence estimates for:

  • COPD
  • Coronary heart disease
  • Stroke
  • Peripheral arterial disease
  • Heart failure
  • Hypertension - diagnosed and undiagnosed
  • Depression

We have retained previous similar estimates for reference and comparison.

The data for the updated estimates is available for:

  • Lower tier local authorities
  • General practices

In future iterations of the dataset we hope to provide aggregations to higher level geographies inlcuding CCGs, STP footprints and  upper tier local authorities.

How do these estimates differ from previous versions and how have they been calculated?

There are differences in case definitions, methods, data sources, predictor variables, and age banding for the 2015 estimates which mean they are not strictly comparable with the 2011 modelled estimates.

A summary of key methods and results of the latest prevalence modelling data is available here.

The technical documents describing how the latest modelled estimates were generated are available below:


Other sources of disease prevalence estimates

Estimates from the diabetes prevalence model are available here.


The 2015 GBD visualisation tool now publishes the prevalence estimates used to calculate Disability Adjusted Life Years. In some cases they differ from the measured or estimated values contained in this tool. There are a number of reasons for this:

  • Different data sources
  • Requirement for between country comparablity in estimating disease prevalence
  • Different modelling methodology