MFPHMI Part I key terms

The number of new cases of a disease arising in a defined population over a specified period, divided by the person-time at risk. It expresses how quickly new cases appear and allows comparison between populations of different sizes and follow-up.

The proportion of a population initially free of disease that develops it during a defined follow-up period. It ranges from zero to one and requires complete follow-up of a closed cohort to be interpretable as a risk.

The proportion of a population that has a disease at a given point in time (point prevalence) or during a period (period prevalence). It reflects both the rate of new cases and how long cases remain in the population.

The summed time each individual in a cohort remains under observation and free of the outcome. It is the denominator for incidence rates and correctly accounts for people entering, leaving, or being censored during follow-up.

The proportion of a defined group who become ill after a common exposure, such as food at a gathering. It is a form of cumulative incidence used in outbreak investigations where the population and exposure window are clearly bounded.

The proportion of people diagnosed with a disease who die from it within a specified period. It measures severity of disease among cases and is not the same as the population mortality rate.

The ratio of observed deaths in a study population to the number expected if that population experienced the age-specific death rates of a reference population, usually expressed as a percentage. It allows fair comparison between populations with different age structures.

A method of adjusting summary rates so that populations with different age distributions can be compared. Direct standardisation applies study rates to a reference age structure; indirect standardisation applies reference rates to the study population.

The ratio of the risk of an outcome in an exposed group to the risk in an unexposed group. A value of one indicates no association; values above one indicate increased risk among the exposed.

The ratio of the odds of exposure among cases to the odds of exposure among controls, or equivalently of outcome odds between exposed and unexposed. It approximates relative risk when the outcome is rare.

The absolute difference in outcome risk between exposed and unexposed groups. It quantifies the excess number of cases attributable to exposure and is directly relevant to estimating public health impact.

The amount of disease incidence in a population that can be attributed to a particular exposure, obtained by subtracting the risk in the unexposed from that in the exposed. It informs the potential benefit of removing the exposure.

The proportion of all cases in a population that would be avoided if a risk factor were eliminated, assuming a causal relationship. It depends on both the strength of association and the prevalence of the exposure.

Distortion of an exposure-outcome association by a third factor that is associated with both and is not on the causal pathway. It can create, exaggerate, or mask a true effect and must be addressed in design or analysis.

Systematic error arising when the groups compared differ in ways related to both exposure and outcome because of how participants were selected or retained. It cannot usually be corrected by increasing sample size.

Systematic error in the measurement or classification of exposure, outcome, or covariates that produces incorrect estimates of association. Recall bias and observer bias are common examples in epidemiological studies.

A situation where the magnitude of an exposure-outcome association differs across levels of a third variable, such as age or sex. Unlike confounding, it is a real biological or social phenomenon to be described, not adjusted away.

An observational design in which a group free of the outcome is classified by exposure and followed forward in time to measure outcome occurrence. It permits direct calculation of incidence and relative risk.

An observational design that samples people with the outcome of interest and comparable people without it, then compares past exposure. It is efficient for rare diseases but yields odds ratios rather than direct risks.

An experimental study in which participants are allocated to interventions by chance, so that known and unknown confounders are balanced between groups. It provides the strongest evidence of causal effect when properly conducted and analysed.

Sensitivity is the proportion of people with disease correctly identified by a test; specificity is the proportion without disease correctly identified. Both are intrinsic test properties independent of disease prevalence.

The probability that a person with a positive test result actually has the disease. It depends on test sensitivity and specificity and on the prevalence of the condition in the tested population.

A range of values, calculated from sample data, that is likely to contain the true population parameter with a stated probability, commonly 95%. Its width reflects precision and depends on variability and sample size.

The probability of observing data at least as extreme as those obtained, assuming the null hypothesis is true. It is not the probability that the null hypothesis is correct and says nothing about effect size.

The probability that a study will detect a true effect of a specified size at a given significance level. Power increases with larger samples, larger effects, and lower variability, and is typically set at 80% or 90%.

Rejecting a true null hypothesis, that is, concluding there is an effect when none exists. Its probability is controlled by the chosen significance level, conventionally 5%.

Failing to reject a false null hypothesis, that is, missing a real effect. Its probability is related inversely to statistical power, so underpowered studies are prone to this error.

The standard deviation of a statistic's sampling distribution, indicating how much an estimate would vary between repeated samples. It is used to construct confidence intervals and shrinks as sample size grows.

Analysis of trial participants according to the group to which they were originally randomised, regardless of adherence. It preserves the benefits of randomisation and gives a conservative estimate of intervention effect.

The number of people who must receive an intervention for one additional person to benefit, calculated as the reciprocal of the absolute risk reduction. It translates trial results into a clinically interpretable measure.

The occurrence of cases of a disease in a community or region in excess of what is normally expected for that place and time. Investigation aims to confirm the diagnosis, identify the source, and control further transmission.

A standardised set of clinical, laboratory, and epidemiological criteria used to classify whether a person counts as a case for surveillance or outbreak investigation. It may be stratified as suspected, probable, or confirmed.

The continuous, systematic collection, analysis, and timely dissemination of health data for planning, implementation, and evaluation of public health practice. It underpins detection of threats and monitoring of trends.

The process of identifying people who may have been exposed to an infectious case, informing them, and supporting isolation or treatment as appropriate. It aims to interrupt onward transmission by finding secondary cases early.

The interval between exposure to an infectious agent and the onset of symptoms. It informs the period of observation for contacts and helps identify the likely time and source of exposure in an outbreak.

The indirect protection of susceptible individuals that arises when a sufficiently high proportion of a population is immune, reducing transmission. The threshold depends on the basic reproduction number and on how the vaccine or infection blocks transmission.

The average number of secondary infections produced by one infectious case in a fully susceptible population. It indicates the transmissibility of an agent and the effort needed to control it.

The reduction in disease risk among vaccinated people compared with unvaccinated people under real-world conditions, expressed as a proportion. It differs from efficacy measured in controlled trials and depends on programme delivery and population factors.

The systematic testing of apparently healthy people to detect unrecognised disease at an early stage, so that earlier intervention can improve outcomes. It requires an accepted test, effective treatment, and adequate follow-up services.

The apparent improvement in survival after screening that arises solely because diagnosis is made earlier, lengthening the time a person is known to have disease without postponing death. It must be excluded when judging screening benefit.

The tendency of screening to detect disproportionately more slowly progressing disease, which has a longer detectable preclinical phase. This makes screened cases appear to survive longer even if screening confers no real benefit.

The principle that where there is plausible evidence of serious or irreversible harm, lack of full scientific certainty should not delay proportionate action to protect health. It guides decision-making under uncertainty in health protection.