Evidence map›Paper›PMID 33038321›Full record

ReviewThe Lancet. Planetary health2020

People-centred surveillance: a narrative review of community-based surveillance among crisis-affected populations.

Ruwan Ratnayake, Meghan Tammaro, Amanda Tiffany, Anine Kongelf, Jonathan A Polonsky, Amanda McClelland

Open access · goldAbstract readReview
In one paragraph

Review in The Lancet. Planetary health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 5% of its field
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

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Review
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

6 authors at 5 institutions in 4 countries.

Ruwan RatnayakeInternational Rescue Committee, New York, NY, USA; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: ruwan.ratnayake@lshtm.ac.uk.
Meghan TammaroJohns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Amanda TiffanyEpicentre, Geneva, Switzerland.
Anine KongelfNorwegian Red Cross, Oslo, Norway.
Jonathan A PolonskyWorld Health Organization, Geneva, Switzerland; Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Amanda McClellandInternational Federation of Red Cross and Red Crescent Societies, Geneva, Switzerland.
International Federation of Red Cross and Red Crescent Societies · CHInternational Rescue Committee · USJohns Hopkins University · USNorges Røde Kors · NOUniversity of Geneva · CH

Funding

World Health Organization 001
6 · The paper itself

Abstract

Outbreaks of disease in settings affected by crises grow rapidly due to late detection and weakened public health systems. Where surveillance is underfunctioning, community-based surveillance can contribute to rapid outbreak detection and response, a core capacity of the International Health Regulations. We reviewed articles describing the potential for community-based surveillance to detect diseases of epidemic potential, outbreaks, and mortality among populations affected by crises. Surveillance objectives have included the early warning of outbreaks, active case finding during outbreaks, case finding for eradication programmes, and mortality surveillance. Community-based surveillance can provide sensitive and timely detection, identify valid signals for diseases with salient symptoms, and provide continuity in remote areas during cycles of insecurity. Effectiveness appears to be mediated by operational requirements for continuous supervision of large community networks, verification of a large number of signals, and integration of community-based surveillance within the routine investigation and response infrastructure. Similar to all community health systems, community-based surveillance requires simple design, reliable supervision, and early and routine monitoring and evaluation to ensure data validity. Research priorities include the evaluation of syndromic case definitions, electronic data collection for community members, sentinel site designs, and statistical techniques to counterbalance false positive signals.

Indexed as

Public Health SurveillanceVulnerable PopulationsCommunity NetworksDisease NotificationDisease OutbreaksEpidemicsEpidemiological MonitoringHumans

Identifiers

PMID33038321
PMCPMC7542093
OpenAlexW3083715491

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.