Evidence map›Paper›PMID 32654387›Full record

ArticleTransboundary and emerging diseases2021

First expert elicitation of knowledge on drivers of emergence of the COVID-19 in pets.

Claude Saegerman, Juana Bianchini, Véronique Renault, Nadia Haddad, Marie-France Humblet

Abstract read
In one paragraph

Article in Transboundary and emerging diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. The First Random Observational Survey of Barrier Gestures against COVID-19.International journal of environmental research and public health · 2021
    Observational
  6. Article
  7. 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.

Claude SaegermanFundamental and Applied Research for Animal and Health (FARAH) Center, University of Liège, Liège, Belgium.ORCID https://orcid.org/0000-0001-9087-7436
Juana BianchiniFundamental and Applied Research for Animal and Health (FARAH) Center, University of Liège, Liège, Belgium.
Véronique RenaultFundamental and Applied Research for Animal and Health (FARAH) Center, University of Liège, Liège, Belgium.ORCID https://orcid.org/0000-0003-2529-3965
Nadia HaddadUMR BIPAR, Ecole nationale vétérinaire d'Alfort, Anses, INRAE, Université Paris-Est, Maisons-Alfort, France.ORCID https://orcid.org/0000-0001-7079-8319
Marie-France HumbletDepartment for Occupational Protection and Hygiene, Unit Biosafety, Biosecurity and Environmental Licences, University of Liege, Liege, Belgium.ORCID https://orcid.org/0000-0003-4069-9402

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infection with the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) induces the coronavirus infectious disease 19 (COVID-19). Its pandemic form in human population and its probable animal origin, along with recent case reports in pets, make drivers of emergence crucial in domestic carnivore pets, especially cats, dogs and ferrets. Few data are available in these species; we first listed forty-six possible drivers of emergence of COVID-19 in pets, regrouped in eight domains (i.e. pathogen/disease characteristics, spatial-temporal distance of outbreaks, ability to monitor, disease treatment and control, characteristics of pets, changes in climate conditions, wildlife interface, human activity, and economic and trade activities). Secondly, we developed a scoring system per driver, then elicited scientific experts (N = 33) to: (a) allocate a score to each driver, (b) weight the drivers scores within each domain and (c) weight the different domains between them. Thirdly, an overall weighted score per driver was calculated; drivers were ranked in decreasing order. Fourthly, a regression tree analysis was used to group drivers with comparable likelihood to play a role in the emergence of COVID-19 in pets. Finally, the robustness of the expert elicitation was verified. Five drivers were ranked with the highest probability to play a key role in the emergence of COVID-19 in pets: availability and quality of diagnostic tools, human density close to pets, ability of preventive/control measures to avoid the disease introduction or spread in a country (except treatment, vaccination and reservoir(s) control), current species specificity of the disease-causing agent and current knowledge on the pathogen. As scientific knowledge on the topic is scarce and still uncertain, expert elicitation of knowledge, in addition with clustering and sensitivity analyses, is of prime importance to prioritize future studies, starting from the top five drivers. The present methodology is applicable to other emerging pet diseases.

Indexed as

SARS-CoV-2AnimalsCat DiseasesCatsCOVID-19Dog DiseasesDogsFerretsGlobal HealthPandemicscarnivoresclustering analysisCOVID-19driversexpert elicitationpetsSARS-CoV-2sensitivity analysis

Identifiers

PMID32654387
PMCPMC7405184

What OpenQuestion holds

Textmetadata
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.