Evidence map›Paper›PMID 38488832›Full record

ArticleJMIR public health and surveillance2024

Using EpiCore to Enable Rapid Verification of Potential Health Threats: Illustrated Use Cases and Summary Statistics.

Nomita Divi, Jaś Mantero, Marlo Libel, Onicio Leal Neto, Marinanicole Schultheiss, Kara Sewalk, John Brownstein, Mark Smolinski

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

8 authors at 2 institutions in 1 country.

Nomita DiviEnding Pandemics, San Francisco, CA, United States.ORCID 0000-0003-0042-4148
Jaś Mantero *Ending Pandemics, San Francisco, CA, United States.ORCID 0000-0002-8132-4992
Marlo LibelEnding Pandemics, San Francisco, CA, United States.ORCID 0000-0002-0019-1279
Onicio Leal NetoEnding Pandemics, San Francisco, CA, United States.ORCID 0000-0001-5785-1867
Marinanicole SchultheissComputational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States.ORCID 0009-0000-3286-9171
Kara SewalkComputational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0002-2917-0869
John BrownsteinComputational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0001-8568-5317
Mark SmolinskiEnding Pandemics, San Francisco, CA, United States.ORCID 0000-0002-5713-8241
Boston Children's Hospital · USUniversity of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe proliferation of digital disease-detection systems has led to an increase in earlier warning signals, which subsequently have resulted in swifter responses to emerging threats. Such highly sensitive systems can also produce weak signals needing additional information for action. The delays in the response to a genuine health threat are often due to the time it takes to verify a health event. It was the delay in outbreak verification that was the main impetus for creating EpiCore.

objectiveThis paper describes the potential of crowdsourcing information through EpiCore, a network of voluntary human, animal, and environmental health professionals supporting the verification of early warning signals of potential outbreaks and informing risk assessments by monitoring ongoing threats.

methodsThis paper uses summary statistics to assess whether EpiCore is meeting its goal to accelerate the time to verification of identified potential health events for epidemic and pandemic intelligence purposes from around the world. Data from the EpiCore platform from January 2018 to December 2022 were analyzed to capture request for information response rates and verification rates. Illustrated use cases are provided to describe how EpiCore members provide information to facilitate the verification of early warning signals of potential outbreaks and for the monitoring and risk assessment of ongoing threats through EpiCore and its utilities.

resultsSince its launch in 2016, EpiCore network membership grew to over 3300 individuals during the first 2 years, consisting of professionals in human, animal, and environmental health, spanning 161 countries. The overall EpiCore response rate to requests for information increased by year between 2018 and 2022 from 65.4% to 68.8% with an initial response typically received within 24 hours (in 2022, 94% of responded requests received a first contribution within 24 h). Five illustrated use cases highlight the various uses of EpiCore.

conclusionsAs the global demand for data to facilitate disease prevention and control continues to grow, it will be crucial for traditional and nontraditional methods of disease surveillance to work together to ensure health threats are captured earlier. EpiCore is an innovative approach that can support health authorities in decision-making when used complementarily with official early detection and verification systems. EpiCore can shorten the time to verification by confirming early detection signals, informing risk-assessment activities, and monitoring ongoing events.

Indexed as

Disease OutbreaksHealth PersonnelAnimalsHumansPandemicscrisescrisiscrowdsourcecrowdsourcingdetectdetectiondigital healthdisease surveillanceearly detectionepidemic intelligence, risk assessmentoutbreakoutbreaksriskriskssurveillancethreatthreatsverificationwarningwarnings

Identifiers

PMID38488832
PMCPMC10980988
OpenAlexW4391387602

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.