Evidence map›Paper›PMID 31565899›Full record

ArticleJournal of veterinary science2019

The difference of detection rate of avian influenza virus in the wild bird surveillance using various methods.

Gang San Kim, Tae Sik Kim, Joo Sung Son, Van Dam Lai, Jung Eun Park, Seung Jun Wang, Weon Hwa Jheong, In Pil Mo

Open access · goldAbstract readComparative Study
In one paragraph

Article in Journal of veterinary science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 26% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 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

8 authors at 2 institutions in 1 country.

Gang San KimAvian Disease Laboratory, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Korea.ORCID https://orcid.org/0000-0002-3864-5379
Tae Sik KimAvian Disease Laboratory, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Korea.ORCID https://orcid.org/0000-0002-5986-0537
Joo Sung SonAvian Disease Laboratory, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Korea.ORCID https://orcid.org/0000-0002-1989-8047
Van Dam LaiAvian Disease Laboratory, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Korea.ORCID https://orcid.org/0000-0001-9084-3076
Jung Eun ParkEnvironmental Health Research Division, National Institute of Environmental Research, Incheon 22689, Korea.
Seung Jun WangEnvironmental Health Research Division, National Institute of Environmental Research, Incheon 22689, Korea.
Weon Hwa JheongEnvironmental Health Research Division, National Institute of Environmental Research, Incheon 22689, Korea.
In Pil MoAvian Disease Laboratory, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Korea. moip@cbu.ac.kr.ORCID https://orcid.org/0000-0003-2793-2628
Chungbuk National University · KRNational Institute of Environmental Research · KR

Funding

National Institute of Environmental Research NIER-SP2018-111
6 · The paper itself

Abstract

Korea is located within the East Asian-Australian flyway of wild migratory birds during the fall and winter seasons. Consequently, the likelihood of introduction of numerous subtypes and pathotypes of the Avian influenza (AI) virus to Korea has been thought to be very high. In the current study, we surveyed wild bird feces for the presence of AI virus that had been introduced to Korea between September 2017 and February 2018. To identify and characterize the AI virus, we employed commonly used methods, namely, virus isolation (VI) via egg inoculation, real-time reverse transcription-polymerase chain reaction (rRT-PCR), conventional RT-PCR (cRT-PCR) and a newly developed next generation sequencing (NGS) approach. In this study, 124 out of 11,145 fresh samples of wild migratory birds tested were rRT-PCR positive; only 52.0% of VI positive samples were determined as positive by rRT-PCR from fecal supernatant. Fifty AI virus specimens were isolated from fresh fecal samples and typed. The cRT-PCR subtyping results mostly coincided with the NGS results, although NGS detected the presence of 11 HA genes and four NA genes that were not detected by cRT-PCR. NGS analysis confirmed that 12% of the identified viruses were mixed-subtypes which were not detected by cRT-PCR. Prevention of the occurrence of AI virus requires a workflow for rapid and accurate virus detection and verification. However, conventional methods of detection have some limitations. Therefore, different methods should be combined for optimal surveillance, and further studies are needed in aspect of the introduction and application of new methods such as NGS.

Indexed as

BirdsAnimalsAnimals, WildEpidemiological MonitoringInfluenza A virusInfluenza in BirdsPopulation SurveillancePrevalenceRepublic of KoreaAvian influenzaconventional methodKoreanext generation sequencingwild bird

Identifiers

PMID31565899
PMCPMC6769331
OpenAlexW2973645414

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.