Burden of Common Respiratory Pathogens Among Cats in China

The frequency of detection of feline respiratory pathogens alone or in combinations among diseased cats was high, indicating a heavy burden of respiratory infections among cats in Kunshan, China. Continued surveillance is desired, and newly emerged respiratory pathogens should also be monitored in routine diagnostic testing.

Authors

Institutions

Publication Details

Journal
Veterinary Medicine and Science
Published
2024-11-22
DOI
https://doi.org/10.1002/vms3.70082
Citations
2
Primary Topic
Respiratory viral infections research
Type
article
Field-Weighted Citation Impact
0.77
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Burden of Common Respiratory Pathogens Among Cats in China

Di Gao, Sajid Umar, Qiu Zhongqi, Weidong Yu et al.
2 citations
Veterinary Medicine and Science
Respiratory viral infections research
0.77
article

Burden of Common Respiratory Pathogens Among Cats in China

Di Gao, Sajid Umar, Qiu Zhongqi, Weidong Yu, Shaban Muhammad, Marwa mouzahim, Shelley Marie Pleva
article en
2 citations

Abstract

The frequency of detection of feline respiratory pathogens alone or in combinations among diseased cats was high, indicating a heavy burden of respiratory infections among cats in Kunshan, China. Continued surveillance is desired, and newly emerged respiratory pathogens should also be monitored in routine diagnostic testing.

Veterinary Medicine and ScienceVol. 11(1)
Duke Kunshan University (CN)
Good health and well-being
Openalex Percentile: Top 24%
Respiratory viral infections research
0.77
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.