Evidence map›Paper›PMID 29021131›Full record

ArticleJMIR public health and surveillance2017

Participatory Disease Surveillance: Engaging Communities Directly in Reporting, Monitoring, and Responding to Health Threats.

Mark S Smolinski, Adam W Crawley, Jennifer M Olsen, Tanvi Jayaraman, Marlo Libel

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing 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

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

  1. Pooled it
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  12. Moana: Alternate surveillance for COVID-19 in a Unique Population (MASC-UP).Contemporary clinical trials communications · 2024
    Article
  13. Article
  14. Active Participatory Regional Surveillance for Notifiable Swine Pathogens.Animals : an open access journal from MDPI · 2024
    Article
  15. Article
  16. Article
  17. Article
  18. Lessons from COVID-19 for rescalable data collection.The Lancet. Infectious diseases · 2023
    Review
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  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

5 authors.

Mark S Smolinski *Skoll Global Threats Fund, Ending Pandemics, San Francisco, CA, United States.ORCID http://orcid.org/0000-0002-5713-8241
Adam W Crawley *Skoll Global Threats Fund, Ending Pandemics, San Francisco, CA, United States.ORCID http://orcid.org/0000-0002-1077-3889
Jennifer M Olsen *Skoll Global Threats Fund, Ending Pandemics, San Francisco, CA, United States.ORCID http://orcid.org/0000-0001-6547-8791
Tanvi Jayaraman *Skoll Global Threats Fund, Ending Pandemics, San Francisco, CA, United States.ORCID http://orcid.org/0000-0001-6732-6652
Marlo Libel *Skoll Global Threats Fund, Ending Pandemics, San Francisco, CA, United States.ORCID http://orcid.org/0000-0002-0019-1279

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSince 2012, the International Workshop on Participatory Surveillance (IWOPS) has served as an informal network to share best practices, consult on analytic methods, and catalyze innovation to advance the burgeoning method of direct engagement of populations in voluntary monitoring of disease.

objectiveThis landscape provides an overview of participatory disease surveillance systems in the IWOPS network and orients readers to this growing field of practice.

methodsAuthors reviewed participatory approaches that include human and animal health surveillance, both syndromic (self- reported symptoms) and event-based, and how these tools have been leveraged for disease modeling and forecasting. The authors also discuss benefits, challenges, and future directions for participatory disease surveillance.

resultsThere are at least 23 distinct participatory surveillance tools or programs represented in the IWOPS network across 18 countries. Organizations supporting these tools are diverse in nature.

conclusionsParticipatory disease surveillance is a promising method to complement both traditional, facility-based surveillance and newer digital epidemiology systems.

Indexed as

communicable diseasesepidemiologic surveillanceglobal healthpublic health surveillance

Identifiers

PMID29021131
PMCPMC5658636

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.