Evidence map›Paper›PMID 35377288›Full record

ReviewGlobal health action2021

Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects.

Kobus Herbst, Sanjay Juvekar, Momodou Jasseh, Yemane Berhane, Nguyen Thi Kim Chuc, Janet Seeley, Osman Sankoh, Samuel J Clark, Mark A Collinson

Abstract readReview
In one paragraph

Review in Global health action, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

  1. Trial
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  5. Neuropsychiatry genetics in Africa.Nature communications · 2026
    Review
  6. Article
  7. Review
  8. Article
  9. Article
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  15. Article
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  18. The Value Proposition of Coordinated Population Cohorts Across Africa.Annual review of biomedical data science · 2024
    Review
  19. Strengthening Global Health Research.Global health action · 2023
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Kobus HerbstDSI-MRC South African Population Infrastructure Network, Durban, South Africa.ORCID 0000-0002-5436-9386
Sanjay JuvekarKEM Hospital Research Centre, Vadu Rural Health Program, Pune, India.ORCID 0000-0002-7209-6924
Momodou JassehMedical Research Council Unit, The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia.ORCID 0000-0002-1026-1082
Yemane BerhaneAddis Continental Institute of Public Health, Addis Ababa, Ethiopia.ORCID 0000-0002-2527-1339
Nguyen Thi Kim ChucFamily Medicine Department, Hanoi Medical University, Hanoi, Vietnam.ORCID 0000-0001-6486-7891
Janet SeeleyPopulation Science, Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa.ORCID 0000-0002-0583-5272
Osman SankohStatistics Sierra Leone, Tower Hill, Freetown, Sierra Leone.ORCID 0000-0003-4405-9808
Samuel J ClarkDepartment of Sociology, The Ohio State University, Columbus, Ohio, USA.ORCID 0000-0002-4929-6231
Mark A CollinsonDSI-MRC South African Population Infrastructure Network, Durban, South Africa.ORCID 0000-0002-8205-7099

Funding

Verbal Autopsy: Reimagining Data & Automated Cause Assignment (using ALPHA Network data)R01HD086227 · NICHD · OHIO STATE UNIVERSITY · PI CLARK, SAMUEL J · 2016 to 2021
$2.4M
NICHD NIH HHS R01 HD086227
6 · The paper itself

Abstract

Health and Demographic Surveillance Systems (HDSS) have been developed in several low- and middle-income countries (LMICs) in Africa and Asia. This paper reviews their history, state of the art and future potential and highlights substantial areas of contribution by the late Professor Peter Byass.Historically, HDSS appeared in the second half of the twentieth century, responding to a dearth of accurate population data in poorly resourced settings to contextualise the study of interventions to improve health and well-being. The progress of the development of this network is described starting with Pholela, and progressing through Gwembe, Balabgarh, Niakhar, Matlab, Navrongo, Agincourt, Farafenni, and Butajira, and the emergence of the INDEPTH Network in the early 1990'sThe paper describes the HDSS methodology, data, strengths, and limitations. The strengths are particularly their temporal coverage, detail, dense linkage, and the fact that they exist in chronically under-documented populations in LMICs where HDSS sites operate. The main limitations are generalisability to a national population and a potential Hawthorne effect, whereby the project itself may have changed characteristics of the population.The future will include advances in HDSS data harmonisation, accessibility, and protection. Key applications of the data are to validate and assess bias in other datasets. A strong collaboration between a national HDSS network and the national statistics office is modelled in South Africa and Sierra Leone, and it is possible that other low- to middle-income countries will see the benefit and take this approach.

Indexed as

Developing CountriesPopulation SurveillanceDemographyHumansPovertySouth AfricaDemographyHDSSLongitudinal Population Studies

Identifiers

PMID35377288
PMCPMC8986235

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.