Evidence map›Paper›PMID 19025678›Full record

ArticleBMC proceedings2008

Electronic public health surveillance in developing settings: meeting summary.

Jean-Paul Chretien, Sheri Happel Lewis

Abstract read
In one paragraph

Article in BMC proceedings, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Redefining syndromic surveillance.Journal of epidemiology and global health · 2011
    Review
  13. 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

2 authors.

Jean-Paul ChretienDepartment of Defense Global Emerging Infections Surveillance and Response System (DoD-GEIS), Silver Spring, Maryland, USA. JeanPaul.Chretien@us.army.mil
Sheri Happel Lewis

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In some high-income countries, public health surveillance includes systems that use computer and information technology to monitor health data in near-real time, facilitating timely outbreak detection and situational awareness. In September 2007, a meeting convened in Bangkok, Thailand to consider the adaptation of near-real time surveillance methods to developing settings. Thirty-five participants represented Ministries of Health, universities, and militaries in 13 countries, and the World Health Organization (WHO). The keynote presentation by a WHO official underscored the importance of improved national capacity for epidemic surveillance and response under the new International Health Regulations, which entered into force in June 2007. Other speakers presented innovative electronic surveillance systems for outbreak detection and disease reporting in developing countries, and methodologies employed in near-real time surveillance systems in the United States. During facilitated small- and large-group discussion, participants identified key considerations in four areas for adapting near-real time surveillance to developing settings: software, professional networking, training, and data acquisition and processing. This meeting was a first step in extending the benefits of near-real time surveillance to developing settings. Subsequent steps should include identifying funding and partnerships to pilot-test near-real time surveillance methods in developing areas.

Identifiers

PMID19025678
PMCPMC2587694

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.