Evidence map›Paper›PMID 36289243›Full record

ArticleScientific data2022

Elaboration of a new framework for fine-grained epidemiological annotation.

Sarah Valentin, Elena Arsevska, Aline Vilain, Valérie De Waele, Renaud Lancelot, Mathieu Roche

Abstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Informatics for One Health.Yearbook of medical informatics · 2023
    Article
  3. 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.

Sarah ValentinUMR TETIS (Land, Environment, Remote Sensing and Spatial Information), University of Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France.
Elena ArsevskaUMR ASTRE (Unit for Animals, Health, Territories, Risks and Ecosystems), University of Montpellier, CIRAD, INRAE, Montpellier, France.
Aline VilainVeterinary Epidemiology Service, Departement of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Valérie De WaeleDepartment of Environmental and Agricultural Studies, Public Service of Wallonia, B5030, Gembloux, Belgium.ORCID 0000-0002-5124-1205
Renaud LancelotUMR ASTRE (Unit for Animals, Health, Territories, Risks and Ecosystems), University of Montpellier, CIRAD, INRAE, Montpellier, France.
Mathieu RocheUMR TETIS (Land, Environment, Remote Sensing and Spatial Information), University of Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France. mathieu.roche@cirad.fr.ORCID 0000-0003-3272-8568

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 874850Fonds De La Recherche Scientifique - FNRS (Belgian National Fund for Scientific Research) contractRT 18/2 MORISKIN 1
6 · The paper itself

Abstract

Event-based surveillance (EBS) gathers information from a variety of data sources, including online news articles. Unlike the data from formal reporting, the EBS data are not structured, and their interpretation can overwhelm epidemic intelligence (EI) capacities in terms of available human resources. Therefore, diverse EBS systems that automatically process (all or part of) the acquired nonstructured data from online news articles have been developed. These EBS systems (e.g., GPHIN, HealthMap, MedISys, ProMED, PADI-web) can use annotated data to improve the surveillance systems. This paper describes a framework for the annotation of epidemiological information in animal disease-related news articles. We provide annotation guidelines that are generic and applicable to both animal and zoonotic infectious diseases, regardless of the pathogen involved or its mode of transmission (e.g., vector-borne, airborne, by contact). The framework relies on the successive annotation of all the sentences from a news article. The annotator evaluates the sentences in a specific epidemiological context, corresponding to the publication date of the news article.

Identifiers

PMID36289243
PMCPMC9606314

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.