Related Experiment Video
Updated: Jul 11, 2026

10:00
Measurement of Lifespan in Drosophila melanogaster
Published on: January 7, 2013
Sources of South African mortality data, 1910-1992
1Department of Community Health, University of Cape Town.
Summary
This bibliography details South African mortality statistics from 1910-1992, covering death counts, ages, and causes. It includes information on International Classification of Diseases editions and data sources.
Area of Science:
- Demography
- Public Health
- Medical Statistics
Context:
- Official statistical publications are the primary source of mortality data for the South African population.
- The period covered is from 1910 to 1992.
- This includes data on the number of deaths, ages, and causes of death.
Purpose:
- To provide a complete bibliography of official statistical publications on South African mortality data.
- To detail the International Classification of Diseases (ICD) editions used in these reports.
- To present information on unpublished computer tapes used for data production from 1968 onwards.
Summary:
- The bibliography covers official statistical publications on South African mortality data from 1910-1992.
- It specifies the International Classification of Diseases (ICD) editions and listed causes of death.
- Details on unpublished computer tapes (1968 onwards) used for report generation are also included.
Impact:
- Facilitates historical research into South African mortality trends.
- Aids researchers in understanding data collection and classification methods over time.
- Provides a comprehensive resource for public health and demographic studies.
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
Introduction To Survival Analysis
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time until a...
The primary goal of survival analysis is to estimate survival time—the time until a...
Life Tables
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
Assumptions of Survival Analysis
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
Applications of Life Tables
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
Cancer Survival Analysis
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

