onr:"swepub:oai:DiVA.org:uu-158318"
Search: onr:"swepub:oai:DiVA.org:uu-158318" > Lessons from Histor...
- 1 of 1
- Previous record
- Next record
- To hitlist
Lessons from History for Designing and Validating Epidemiological Surveillance in Uncounted Populations
-
- Byass, Peter (author)
- Umeå universitet,Epidemiologi och global hälsa,Department of Public Health and Clinical Medicine, Umeå Centre for Global Health Research, Umeå University, Swede
-
- Sankoh, Osman (author)
- INDEPTH Network, Accra, Ghana
-
- Tollman, Stephen M (author)
- Umeå universitet,Epidemiologi och global hälsa,Department of Public Health and Clinical Medicine, Umeå Centre for Global Health Research, Umeå University, Sweden
- show more...
- show less...
- (creator_code:org_t)
- 2011-08-03
- 2011
- English.
- In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:8, s. e22897-
- Journal article (peer-reviewed)
Abstract
Subject headings
Close
- Background: Due to scanty individual health data in low- and middle-income countries (LMICs), health planners often use imperfect data sources. Frequent national-level data are considered essential, even if their depth and quality are questionable. However, quality in-depth data from local sentinel populations may be better than scanty national data, if such local data can be considered as nationally representative. The difficulty is the lack of any theoretical or empirical basis for demonstrating that local data are representative where data on the wider population are unavailable. Thus these issues can only be explored empirically in a complete individual dataset at national and local levels, relating to a LMIC population profile. Methods and Findings: Swedish national data for 1925 were used, characterised by relatively high mortality, a low proportion of older people and substantial mortality due to infectious causes. Demographic and socioeconomic characteristics of Sweden then and LMICs now are very similar. Rates of livebirths, stillbirths, infant and cause-specific mortality were calculated at national and county levels. Results for six million people in 24 counties showed that most counties had overall mortality rates within 10% of the national level. Other rates by county were mostly within 20% of national levels. Maternal mortality represented too rare an event to give stable results at the county level. Conclusions: After excluding obviously outlying counties (capital city, island, remote areas), any one of the remaining 80% closely reflected the national situation in terms of key demographic and mortality parameters, each county representing approximately 5% of the national population. We conclude that this scenario would probably translate directly to about 40 LMICs with populations under 10 million, and to individual states or provinces within about 40 larger LMICs. Unsubstantiated claims that local sub-national population data are "unrepresentative" or "only local" should not therefore predominate over likely representativity.
Keyword
- MEDICINE
- MEDICIN
Publication and Content Type
- ref (subject category)
- art (subject category)
- 1 of 1
- Previous record
- Next record
- To hitlist
Find more in SwePub
- By the author/editor
- Byass, Peter
- Sankoh, Osman
- Tollman, Stephen ...
- Högberg, Ulf, 19 ...
- Wall, Stig
- Articles in the publication
- PLOS ONE
- By the university
- Uppsala University
- Umeå University
Search outside SwePub
- Extend your search to:
- Google Book Search
- Google Scholar
Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.
- Copyright © LIBRIS - National Library Systems
- LIBRIS.kb.se
