Population projection is an essential tool in demography, urban planning, public health, and economic forecasting, as it estimates future population size and structure. Among the many projection techniques, the Survival Method is one of the most widely used for medium- to long-term projections because it incorporates age- and sex-specific survival rates and accounts for births, deaths, and migration.
The Survival Method is particularly important when a planner needs age-structured projections for policy formulation, resource allocation, and infrastructure planning.
2. Concept of the Survival Method
The Survival Method projects the population by following each cohort (a group of people born in the same year or period) over time and applying survival rates to estimate how many people remain in that cohort in future years.
The method is called “survival” because:
- It uses life tables or survival ratios to determine what proportion of a cohort will survive to the next age group in the next projection period.
- It moves each age cohort forward through time, reducing it according to mortality, and adding new births for the youngest cohort.
3. Data Requirements
To apply the Survival Method, the following data are typically needed:
- Base-Year Population Data
- Classified by age and sex.
- Usually obtained from a census or population register.
- Survival Ratios / Life Tables
- Probability of surviving from one age group to the next over a given time interval.
- Derived from mortality rates, adjusted for the local population.
- Fertility Rates (for projecting new births)
- Age-specific fertility rates (ASFRs) for females in childbearing ages (usually 15–49 years).
- Migration Data
- Estimates of net migration by age and sex, if applicable.
4. Step-by-Step Procedure
Step 1: Prepare Base-Year Age-Sex Population
Organize the population into standard 5-year age groups (0–4, 5–9, 10–14, …, 80+), separated by male and female.
Step 2: Obtain Survival Ratios
- From life tables, determine the proportion of people who survive from one age group to the next over the projection interval (e.g., 5 years).
- Example: If the survival ratio from age 10–14 to age 15–19 is 0.98, it means 98% of those aged 10–14 will survive to the 15–19 group after 5 years.
Step 3: Apply Survival Ratios to Cohorts
- Multiply each cohort by the corresponding survival ratio to get the population in the next age group for the next projection period.
- Example:
Base-year population (age 10–14): 20,000
Survival ratio to age 15–19: 0.98
Projected 15–19 age group (next period) = 20,000 × 0.98 = 19,600.
Step 4: Project the Youngest Age Group (Births)
- Calculate expected births during the projection period using age-specific fertility rates and the projected number of women in childbearing ages.
- Example:
- ASFR for women aged 20–24 = 0.08 (meaning 80 births per 1,000 women over the 5-year period).
- Multiply ASFR by the number of women in that age group.
- Sum births across all childbearing age groups to get total births.
- Apply infant and child survival ratios to estimate how many survive to age 0–4 in the next period.
Step 5: Adjust for Migration (If Applicable)
- Add or subtract net migration by age group before moving to the next projection cycle.
Step 6: Repeat for Each Projection Interval
- Continue moving cohorts forward for each projection period until the desired future year is reached.
5. Example (Simplified)
Base-Year Population (2025) – Males Only:
| Age Group | Population | Survival Ratio | Projected Pop. (2030) |
|---|---|---|---|
| 0–4 | 10,000 | 0.995 | (Births projected) |
| 5–9 | 9,800 | 0.995 | 9,751 |
| 10–14 | 9,500 | 0.990 | 9,405 |
| 15–19 | 9,200 | 0.985 | 9,062 |
| … | … | … | … |
For the 0–4 age group in 2030, births are calculated based on projected women in reproductive ages and then multiplied by infant/child survival ratios.
6. Advantages of the Survival Method
- Age-specific projection: Produces detailed breakdowns by age and sex.
- High accuracy for medium-term projections (10–30 years) when data are good.
- Can incorporate fertility, mortality, and migration separately.
- Useful for planning schools, hospitals, housing, pensions, etc.
7. Limitations
- Requires reliable and detailed data (age-sex population, life tables, fertility rates).
- Less accurate for small populations due to statistical fluctuations.
- Long-term projections (>40 years) may be less reliable because fertility, mortality, and migration trends can change unexpectedly.
- More complex than simple growth rate methods.
8. Applications
- Urban planning – predicting future demand for housing and infrastructure.
- Health planning – estimating needs for hospitals and elderly care.
- Education planning – forecasting school enrollment.
- Labour market forecasting – anticipating changes in the working-age population.
- Social security and pension planning – understanding aging trends.
✅ In short, the Survival Method (Cohort-Survival) is a systematic way to move each age cohort forward in time, adjusting for mortality, fertility, and migration, to produce age-structured, sex-specific population projections. Its strength lies in its demographic realism and policy relevance, making it a standard in official statistical agencies and planning institutions.
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