Descriptive epidemiology: person, place and time
- Concept
Descriptive epidemiology sorts cases by who, where and when to reveal patterns and suggest causes.
What it is
Descriptive epidemiology organises health data by characteristics of person, place and time and expresses them as rates. It shows which groups, areas and periods carry the most burden, guides services, and generates hypotheses that analytic studies then test. Its own tools are specific rates, spot maps and rate maps, and time series with their trends.
Structure
- Person: age- and sex-specific rates, rates by occupation or by vaccination status.
- Place: spot map by home or workplace, rate map by municipality, urban-rural differences.
- Time: secular trend, seasonality, multi-year cycles and the epidemic curve of an outbreak.
Worked example
- Data (made up): a municipality of 50 000 people, stable population; severe acute respiratory infection (ARI) cases: 1 500, 1 650 and 1 800 in 2023–2025.
- Secular trend: rates of 30, 33 and 36 per 1 000; up 10 % in 2024 (150/1 500) and ≈ 9 % in 2025 (150/1 650).
- Seasonality 2025: April and May add up to 540 cases; 540 / 1 800 = 30 % of the year in 2 of 12 months.
- If cases were even, 2 months would hold 2 / 12 ≈ 16.7 %; 30 / 16.7 ≈ 1.8 times the expected share in those months.
- Person 2025: under-5s, 600 cases in 4 000 children = 150 per 1 000; everyone else, 1 200 in 46 000 ≈ 26.1 per 1 000.
- Rate ratio by age: 150 / 26.1 ≈ 5.75; young children have almost six times the rate of the rest.
- Place: the spot map clusters cases in two neighbourhoods with crowded housing; their rates are computed before concluding.
- Reading: a rising burden, a rainy-season peak and concentration in young children; hypotheses for an analytic study and for planning services.
Time patterns in descriptive epidemiology
| Pattern | Scale | Typical example | What it suggests |
|---|---|---|---|
| Secular trend | Years or decades | Falling infant mortality | Changes in living conditions, services or diagnosis |
| Seasonal | Months within the year | Acute respiratory infection in the rainy season | Climate, vectors, crowding |
| Cyclic | Peaks every few years | Vaccine-preventable diseases with low coverage | Build-up of susceptible people between peaks |
| Outbreak | Days or weeks | Diarrhoea after an event | A common source or person-to-person spread |
Markers
- Person
- Place
- Time
- Spot map
- Secular trend
- Seasonality
In practice
- INS event reports and health situation analyses present data this way: by age, territory and epidemiological week.
- Known seasonality lets services add beds, staff and vaccination before the peak, not during it.
- A sudden change in a trend first raises the question of whether the case definition, the reporting or the diagnostic test changed.
Common pitfalls
- Reading a spot map as a risk map without dividing by each area's population.
- Comparing raw counts between years when the population grew.
- Attributing a secular trend to the disease when a change in coding or in access to diagnosis explains it.
- Comparing crude rates between populations with very different ages without standardising.
Test yourself
Think of the answer, then tap the question to see it.
What is the difference between seasonal and cyclic variation?
Seasonal variation repeats within each year (by month or season); cyclic variation produces peaks every few years, often because susceptible people build up.
Why can a spot map mislead about risk?
Because it shows where the cases are, not each area's population; a crowded area will have more dots even if its rate is the same or lower.
Which person variable influences almost every disease the most?
Age; that is why age-specific rates are computed and rates are standardised before comparing populations.
If cases of an event jump one year, what should be checked before calling it a real increase?
Whether the case definition, reporting, diagnostic test or population changed: any of these changes the count without the disease changing.
Connections
Educational content on epidemiological and statistical methods; the examples use made-up numbers to teach the calculation. Not a clinical or legal guide: current Colombian rules are in the official sources.
Sources: Principles of Epidemiology | Lesson 1 - Section 6 (Centers for Disease Control and Prevention, 2012); The design, applications, strengths and weaknesses of descriptive studies and ecological studies (Health Knowledge (Faculty of Public Health), 2018).
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Representative model, for educational purposes only.