South Africa - ZA021 Excess Mortality: Surveillance Episodes Datasets
Reference ID | ZA021-EXMORTALITY-03 |
Year | 1995 - 2021 |
Country | South Africa |
Producer(s) |
Prof Eric Maimela - DIMAMO Prof Steve Tollman - Agincourt Prof Kathleen Khan - Agincourt Dr Chodziwadziwa Kabudula - Agincourt Dr Beth Tippett-Barr - Nyanja Health Research Institute{B |
Sponsor(s) | Bill & Melinda Gates Foundation, Seattle, WA - BMGF - Current Funder South African Population Research Infrastructure Network, South Africa - SAPRIN - Current Funder Wellcome Trust, UK - Wellcome - Previous Funder |
Metadata | Documentation in PDF |
Created on
Dec 22, 2023
Last modified
Mar 22, 2024
Page views
1952
Overview
Identification
ZA021-EXMORTALITY-03 |
Version
v1: Dataset for public distribution. 2023-06-01
Overview
Following the declaration of COVID-19 as a pandemic by the World Health Organization, there have been high levels of reported deaths, at least in countries with functioning civil registration and vital statistics (CRVS). These largely under-represent the true mortality due to COVID-19. A fundamental question, then, is what is the impact of COVID-19 on mortality and the scale of excess deaths, and the population sub-groups most affected, particularly in low- and middle-income settings? Constructing a true representation of COVID-19 deaths can be useful for social policies and future pandemic preparedness planning. The goal of this initiative is to characterise all-cause mortality rates and trends, by age and sex, across a range of rural and urban sub-Saharan African and South Asian settings under continuous health and demographic surveillance. This a multinational initiative bringing together 17 sites/centres from Africa and South Asia. This dataset represents a snapshot of the continually evolving data in the underlying longitudinal databases maintained by the nodes.
Event history data
Exposure Episodes
Scope
Each record in the dataset represents a period of observation for an individual during which all the recorded characteristics of the individual stay constant. For example, on the birthday of the individual a new episode will start, because the age of the individual has changed. An out-migration will result in a new episode, because the location or residential status has changed. Any change in one of the status values, such as education or marital status, will likewise result in a new episode on the date of the change.Topic | Vocabulary | URI |
---|---|---|
Episodes, Mortality, Migration |
Coverage
The data are collected from the DIMAMO health and socio-demographic surveillance area in rural and peri-urban, South Africa. The HDSS was established in 1995 in the Capricorn District of Limpopo Province, South Africa. The surveillance area comprises 59 villages, classified into rural and semi-rural areas. These areas are inhabited by people of low socioeconomic status with high levels of unemployment, poor educational backgrounds, and a high prevalence of hypertension and other chronic illnesses. Since its establishment, the DIMAMO surveillance area has undergone two major expansions, tremendously increasing the population under surveillance. The expansions were in 2010 and 2018, with populations of approximately 34,000 and 100,000, respectively. The current population is over 100,000 from approximately 21,000 households.
Households resident in dwellings within the study area will be eligible for inclusion in the surveillance. All individuals identified by the household proxy informant as a member of the household will be enumerated. A resident household member is an individual that intends to sleep the majority of time at the dwelling occupied by the household over a four-month period. Households will include resident and non-resident members. An individual is a non-resident member if they have close ties to the household, but do not physically reside with the household most of the time. They can also be called temporary migrants and they are enumerated within the household list. Because household membership is not tied to physical residency, an individual may be a member of more than one household.
Producers and Sponsors
Name | Affiliation |
---|---|
Prof Eric Maimela | DIMAMO |
Prof Steve Tollman | Agincourt |
Prof Kathleen Khan | Agincourt |
Dr Chodziwadziwa Kabudula | Agincourt |
Dr Beth Tippett-Barr | Nyanja Health Research Institute |
Name | Affiliation | Role |
---|---|---|
Kagiso Peace Seakamela | DIMAMO | Conceptualization analysis and drafting of the manuscript and reviewing |
Jean Juste Harrisson Bashingwa | Agincourt | Conceptualization, analysis and drafting of the manuscript, reviewing |
Joseph Tlouyamma | Department of Computer Science, University of Limpopo | Conceptualization analysis and drafting of the manuscript, reviewing |
Cairo Bruce Ntimana | DIMAMO | Conceptualization, analysis and drafting of the manuscript, reviewing |
Modupi Peter Mphekgwana | Research Administration and Development, University of Limpopo | Analysis, drafting of the manuscript and reviewing |
Reneilwe Given Mashaba | DIMAMO | Reviewing |
Katlego Mothapo | DIMAMO | Reviewing |
Chodziwadziwa Whiteson Kabudula | Agincourt | Conceptualization, analysis and drafting of the manuscript, reviewing |
Eric Maimela | DIMAMO | Reviewing |
Name | Abbreviation | Role |
---|---|---|
Bill & Melinda Gates Foundation, Seattle, WA | BMGF | Current Funder |
South African Population Research Infrastructure Network, South Africa | SAPRIN | Current Funder |
Wellcome Trust, UK | Wellcome | Previous Funder |
Name | Affiliation | Role |
---|---|---|
SAMRC/Wits Agincourt Data Team | Agincourt | Data review, and analysis |
South African Population Research Infrastructure Network team | SAPRIN | Data review, analysis, and write-up processes |
DIMAMO leadership and staff | DIMAMO PHRC | Providing data |
Child Health and Mortality Prevention Surveillance Network team | CHMPS | Data review, analysis, and write-up processes |
Nyanja Health Research Institute | NHRI | Data review and Write-up processes |