Measuring Disease

The most common methods for assessing the amount of disease in a population are look at morbidity (illness) or mortality (death). There are 2 common methods used to measure morbidity; incidence and prevalence.
Incidence
The incidence of a disease is the rate at which new cases occur in a population at risk during a specific period.
If the population is stable, the formula used is:
Incidence = Number of cases / Population at risk x time during which cases were ascertained
If the population changes during the period where new cases are measured, the incidence is calculated using "total person years at risk". This is the sum of the new cases during the period which each person in the population was at risk during the measurement period. The formula is therefore
Incidence = Number of new cases / Total person years at risk
Example: If there were 17 cases of flu in a school of 1000 in a 2 years, this is an incidence of 8.5/1000 per year.

Prevalence
The proportion of a population who have a disease at a point in time is the prevalence of disease. It is often expressed as a percentage. The 'point in time' can be a single examination [point prevalence], but is often a longer time scale in order to give a better estimate of the numbers with the disease [period prevalence].
Prevalence = (cases/population) * 100
Prevalence is used for diseases that are chronic conditions, such as asthma, diabetes, cystic fibrosis.
Example: In a nursing home with 100 residents, 10 people had diabetes in a 12 month period. The prevalence of diabetes in the nursing home was therefore 10%.

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Rates
It is often to look at the incidence and prevalence of diseases in terms of rates. This enables comparisons between different populations.
Crude Rate
A crude rate is a rate that applies to the population as a whole, and that hasn’t been adjusted to account for differences in population structures such as age and sex. It is calculated using this formula:
Crude Rate = Number of Events / Total Number of People in a Population
Example: If a town has a population of 1000, and 25 people die from cancer in one year, the mortality rate is 25/1000/year.
Pros:
• Crude rates are useful for getting an overall picture of the amount of disease in an area
Cons:
• Crude rate often mask the differences in particular age groups or sexes. If there are differences in the crude rate between areas, it could be because one area has a higher proportion of vulnerable people.

For example, if area A has a high proportion of elderly people compared with area B, its crude death overall rate will be higher. This may however mask the fact that the premature death rate is actually higher in area B, which had the lower crude death rate.
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Standardised Rates
In order to overcome the problems of a crude rate masking differences in particular age groups, rates can be standardised. There are two types of standardization; direct and indirect.
Direct Standardisation
Directly standardized rates give an indication of the number of events that would occur in a standard population, if the population had the same age-specific rates of the local area. The standard population that is most commonly used is the European Standard population, however other populations such as the Avon standard population can also be used. The rates are calculated per 100,000 and because rates are applied to the same population, rates across areas can be compared.
Example:
Between 1997-1999, Bristol Unitary Authority has a directly standardized mortality rate for accidents of 16.7/100,000. This means that if the European Standard population experienced the same age-specific patterns in mortality, the death rate would be 16.7 per 100,000
Pros:
• Unlike indirectly standardised rates, which compare the observed number of events to the expected number of events, (see below) they can be used to compare disease rates across areas and time.
• Can be used to asses the relative burden of disease in a population e.g. if there is more heart disease than cancer
• There is a wide variety of comparable figures including data in the Compendium of Clinical Indicators available that have been standardised using the European Standard population.
Cons:
• Requires age specific rates that are not often available at a local level.
• Rates may not be stable for small number of events (approximately = to 70%, and the National Target is 80%.
Cervical Screening Coverage
The coverage of the screening programme is defined as the proportion of women eligible for screening who have had a test with a recorded result at least once in the previous 5 years. Women ineligible for screening, and therefore excluded from both the numerator and denominator of the coverage calculation, are those whose recall has been ceased for clinical reasons (e.g. those who have had a hysterectomy).
The National Minimum Standard for coverage is 80%.
Finished Consultant Episode (FCE)
This is defined as a period of admitted patient care under one consultant within one health care provider. The figures do not represent the number of patients, as a person may have more than one episode of care within the year. (London Health Observatory)
Finished Admission Episode
This is defined as the first period of in-patient care under one consultant within one health care provider. Such episodes are coded 01 in the spell of care (London Health Observatory)
PBS Phase III Diabetes Prevalence model
A spreadsheet model that generates expected total numbers of persons with Type 1 and Type 2 diabetes mellitus (diagnosed plus undiagnosed combined) for 2005. The model applies age/sex/ethnic group-specific estimates of diabetes prevalence rates, derived from epidemiological population studies, to population estimates.
Lower Super Output Areas (LSOAs)
The Index of Multiple Deprivation 2007 (IMD 2007) is based on the small area geography known as Lower Super Output Areas (LSOAs). LSOAs have between 1,000 and 3,000 people living in them with an average population of 1,500 people. In most cases LSOAs are smaller than wards, thus allowing the identification of small pockets of deprivation. There are 34,378 LSOAs in England and Wales and 145 in the London Borough of Waltham Forest.
Middle Super Output Areas (MSOAs)
Middle Super Output Layers (MSOAs) have a minimum population of 5,000, and mean population of 7,200. MSOAs are built from aggregations of LSOAs. There are 7,193 MSOAs in England and Wales and 28 in the London Borough of Waltham Forest