Evidence map›Paper›PMID 36518896›Full record

ArticleFrontiers in veterinary science2022

Unveiling of the epidemiological patterns for caprine/ovine enterovirus infection in China.

Junying Hu, Xiaoran Chang, Rudu Wang, Qun Zhang, Fan Zhang, Zhiyuan Zhang, Fuhui Zhang, Mingzhu Qian, Xinping Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 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
0.5field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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 2 institutions in 1 country.

Junying HuState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Xiaoran ChangState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Rudu WangState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Qun ZhangState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Fan ZhangState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Zhiyuan ZhangState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Fuhui ZhangState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Mingzhu QianState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Xinping WangState Key Laboratory for Zoonotic Diseases, Key Laboratory of Zoonosis Research of Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, China.
Jilin University · CNHenan Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Caprine/ovine enterovirus (CEV/OEV) infection is an emerging disease and remains largely unknown for its infection distribution, epidemic pattern, and the underlying contribution factors. Here, we report the investigation on CEV/OEV infection pattern and the underlying contribution factors by employing a sandwich ELISA kit for detection of CEV/OEV antigen. Epidemiological investigation revealed a wide range of infection rates of CEV/OEV from 19.80%-39.00% on goat/sheep farms in the major goat/sheep-raising provinces as such Henan, Shandong, Ningxia, Jilin, Inner Mongolia autonomous region, and Xinjiang autonomous region in China. Epidemic patterns and infection rates for CEV/OEV were affected by the breeds, raising mode, regions, and seasons. CEV/OEV infection rates were varied in different regions in China and significantly higher in the diarrheal herds (40.30%) than these in non-diarrheal herds (13.83%). Moreover, infection rate was higher in sheep (24.59%) than that in goats (9.84%), even dramatic difference among different breeds of goat or sheep. Out of different breeds of goat, Boer (20.13%) had the highest infection rate, followed by local breed (5.62%) and Saanen (2.61%). Among these breeds of sheep, higher infection rates were detected in local breed sheep (42.86%) and small-tailed Han sheep (35.91%) than these of Hu sheep (13.41%) and Dorper sheep (16.34%). Furthermore, raising modes were showed to contribute to the infection rate, where higher rates were detected among goats/sheep in captivity (27.10%) than these in free-range (12.27%) and semi-free range (19.24%). Additionally, CEV/OEV infection rate had obvious seasonality, while they increased from year 2015 to 2019. In summary, we investigated the CEV/OEV infection among the goat/sheep herds from different regions in China, revealed the epidemic pattern and the contribution factors to the infection, which provided the epidemiological data for future prevention and control of this emerging infection.

Indexed as

caprine/ovine enterovirus infectionCEV/OEVcontribution factorsepidemic patternepidemiologygoat/sheep

Identifiers

PMID36518896
PMCPMC9742414
OpenAlexW4310262038

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.