Evidence map›Paper›PMID 41234415›Full record

ArticleOne health (Amsterdam, Netherlands)2025

SARS-CoV-2 exposure in dogs before and after the largest COVID-19 wave in rural Guatemala, 2022.

Francisco C Ferreira, Jose G Juarez, Henry Esquivel, Norma Padilla, Pamela Pennington, Gabriel L Hamer, Sarah A Hamer

Abstract read
In one paragraph

Article in One health (Amsterdam, Netherlands), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Francisco C FerreiraDepartment of Entomology, Texas A&M University, College Station, TX, USA.
Jose G JuarezDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA.
Henry EsquivelSección de Vectores de Jutiapa de Redes de Servicios Integrados de Salud Jutiapa, Ministerio de Salud Pública y Asistencia Social, Jutiapa, Guatemala.
Norma PadillaCentro de Estudios en Salud, Universidad del Valle de Guatemala, Guatemala City, Guatemala.
Pamela PenningtonCentro de Estudios en Salud, Universidad del Valle de Guatemala, Guatemala City, Guatemala.
Gabriel L HamerDepartment of Entomology, Texas A&M University, College Station, TX, USA.
Sarah A HamerDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 pandemic disproportionately burdened low- and mid-income countries during many waves of high transmission, particularly in rural communities. We tested whether dogs from rural households were exposed to SARS-CoV-2 before and after the largest COVID-19 wave in Guatemala. We tested dogs in June and August 2022, before the rise and after the initial peak of the second Omicron wave, respectively. None of the 133 dogs tested (63 tested in June and 70 tested in August) had evidence of SARS-CoV-2 RNA in respiratory swabs. Three dogs in June and five dogs in August had neutralizing antibodies against SARS-CoV-2. Risk factor analysis showed that the largest COVID-19 wave in Guatemala did not increase dog exposure to SARS-CoV-2. However, dogs with outdoor access had higher odds of infection compared to indoors-only dogs. Public health interventions should provide education regarding pet roaming practices to mitigate the spread of zoonotic diseases in rural areas.

Indexed as

COVID-19OmicronOne healthpetsSARS-CoV-2surveillance

Identifiers

PMID41234415
PMCPMC12607110

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.