Evidence map›Paper›PMID 25329886›Full record

ReviewPloS one2014

A review of evaluations of electronic event-based biosurveillance systems.

Kimberly N Gajewski, Amy E Peterson, Rohit A Chitale, Julie A Pavlin, Kevin L Russell, Jean-Paul Chretien

Abstract readReview
In one paragraph

Review in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Epidemic intelligence needs of stakeholders in the Asia-Pacific region.Western Pacific surveillance and response journal : WPSAR
    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

6 authors.

Kimberly N GajewskiResponse Directorate, Federal Emergency Management Agency, Washington, DC, United States of America.
Amy E PetersonDivision of Integrated Biosurveillance, Armed Forces Health Surveillance Center, Silver Spring, MD, United States of America.
Rohit A ChitaleDivision of Integrated Biosurveillance, Armed Forces Health Surveillance Center, Silver Spring, MD, United States of America.
Julie A PavlinHeadquarters, Armed Forces Health Surveillance Center, Silver Spring, MD, United States of America.
Kevin L RussellHeadquarters, Armed Forces Health Surveillance Center, Silver Spring, MD, United States of America.
Jean-Paul ChretienDivision of Integrated Biosurveillance, Armed Forces Health Surveillance Center, Silver Spring, MD, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic event-based biosurveillance systems (EEBS's) that use near real-time information from the internet are an increasingly important source of epidemiologic intelligence. However, there has not been a systematic assessment of EEBS evaluations, which could identify key uncertainties about current systems and guide EEBS development to most effectively exploit web-based information for biosurveillance. To conduct this assessment, we searched PubMed and Google Scholar to identify peer-reviewed evaluations of EEBS's. We included EEBS's that use publicly available internet information sources, cover events that are relevant to human health, and have global scope. To assess the publications using a common framework, we constructed a list of 17 EEBS attributes from published guidelines for evaluating health surveillance systems. We identified 11 EEBS's and 20 evaluations of these EEBS's. The number of published evaluations per EEBS ranged from 1 (Gen-Db, GODsN, MiTAP) to 8 (GPHIN, HealthMap). The median number of evaluation variables assessed per EEBS was 8 (range, 3-15). Ten published evaluations contained quantitative assessments of at least one key variable. No evaluations examined usefulness by identifying specific public health decisions, actions, or outcomes resulting from EEBS outputs. Future EEBS assessments should identify and discuss critical indicators of public health utility, especially the impact of EEBS's on public health response.

Indexed as

BiosurveillanceInternetPublic Health SurveillanceHumansPubMed

Identifiers

PMID25329886
PMCPMC4203831

What OpenQuestion holds

Textmetadata
LicenceCC0
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.