Evidence map›Paper›PMID 35608925›Full record

ArticleEmerging infectious diseases2022

Risk Factors for SARS-CoV-2 Infection and Illness in Cats and Dogs

Dorothee Bienzle, Joyce Rousseau, David Marom, Jennifer MacNicol, Linda Jacobson, Stephanie Sparling, Natalie Prystajecky, Erin Fraser, J Scott Weese

Open access · diamondAbstract read
In one paragraph

Article in Emerging infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
5.0field-weighted citation impact, top 3% 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

34 citing papers in PubMed, 50 citations in OpenAlex.

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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 at 4 institutions in 1 country.

Dorothee Bienzle
Joyce Rousseau
David Marom
Jennifer MacNicol
Linda Jacobson
Stephanie Sparling
Natalie Prystajecky
Erin Fraser
J Scott Weese
BC Centre for Disease Control · CAOntario Veterinary CollegeVancouver Biotech (Canada) · CAUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We tested swab specimens from pets in households in Ontario, Canada, with human COVID-19 cases by quantitative PCR for SARS-CoV-2 and surveyed pet owners for risk factors associated with infection and seropositivity. We tested serum samples for spike protein IgG and IgM in household pets and also in animals from shelters and low-cost neuter clinics. Among household pets, 2% (1/49) of swab specimens from dogs and 7.7% (5/65) from cats were PCR positive, but 41% of dog serum samples and 52% of cat serum samples were positive for SARS-CoV-2 IgG or IgM. The likelihood of SARS-CoV-2 seropositivity in pet samples was higher for cats but not dogs that slept on owners' beds and for dogs and cats that contracted a new illness. Seropositivity in neuter-clinic samples was 16% (35/221); in shelter samples, 9.3% (7/75). Our findings indicate a high likelihood for pets in households of humans with COVID-19 to seroconvert and become ill.

Indexed as

Cat DiseasesCOVID-19Dog DiseasesAnimalsCatsDogsImmunoglobulin GImmunoglobulin MOntarioPetsRisk FactorsSARS-CoV-2Immunoglobulin GImmunoglobulin MCanadacoronavirus diseaseCOVID-19ELISAet al. Risk factors for SARS-CoV-2 infection and illness in cats and dogs. Emerg Infect Dis. 2022 June [date cited]. https://doi.org/10.3201/eid2806.220423human-animal bondJacobson LMacNicol JMarom Dpetsrespiratoryrespiratory infectionsRousseau JSARS-CoV-2seropositivitysevere acute respiratory syndrome coronavirus 2Sparling SSuggested citation for this article: Bienzle Dviruseszoonoses

Identifiers

PMID35608925
PMCPMC9155877
OpenAlexW4280518700

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.