Evidence map›Paper›PMID 35457541›Full record

ArticleInternational journal of environmental research and public health2022

Syndromic Surveillance Systems for Mass Gatherings: A Scoping Review.

Eliot Spector, Yahan Zhang, Yi Guo, Sarah Bost, Xi Yang, Mattia Prosperi, Yonghui Wu, Hui Shao, Jiang Bian

Abstract readScoping Review
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Observational
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.

Eliot SpectorDepartment of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0001-7891-8127
Yahan ZhangDepartment of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL 32610, USA.
Yi GuoDepartment of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0003-0587-4105
Sarah BostDepartment of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0001-8553-9539
Xi YangDepartment of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32610, USA.
Mattia ProsperiDepartment of Epidemiology, University of Florida, Gainesville, FL 32610, USA.
Yonghui WuDepartment of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32610, USA.
Hui ShaoDepartment of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL 32610, USA.
Jiang BianDepartment of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-2238-5429

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
CDC HHS U18 DP006512NCATS NIH HHS UL1 TR001427NIH HHS UL1TR001427
6 · The paper itself

Abstract

Syndromic surveillance involves the near-real-time collection of data from a potential multitude of sources to detect outbreaks of disease or adverse health events earlier than traditional forms of public health surveillance. The purpose of the present study is to elucidate the role of syndromic surveillance during mass gathering scenarios. In the present review, the use of syndromic surveillance for mass gathering scenarios is described, including characteristics such as methodologies of data collection and analysis, degree of preparation and collaboration, and the degree to which prior surveillance infrastructure is utilized. Nineteen publications were included for data extraction. The most common data source for the included syndromic surveillance systems was emergency departments, with first aid stations and event-based clinics also present. Data were often collected using custom reporting forms. While syndromic surveillance can potentially serve as a method of informing public health policy regarding specific mass gatherings based on the profile of syndromes ascertained, the present review does not indicate that this form of surveillance is a reliable method of detecting potentially critical public health events during mass gathering scenarios.

Indexed as

Mass GatheringsSentinel SurveillanceDisease OutbreaksEmergency Service, HospitalPopulation SurveillancePublic Health Surveillancedisaster managementemergency medicineinfectious disease surveillancemass gathering medicinepublic health surveillancesyndromic surveillance

Identifiers

PMID35457541
PMCPMC9026395

What OpenQuestion holds

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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.