Evidence map›Paper›PMID 41716172›Full record

ReviewVeterinary world2025

Advances and emerging technologies in the diagnosis of viral infections in pigs: Progress, challenges, and One Health perspectives.

Kydyr Nazerke, Asaubayev Ruslan, Daugaliyeva Saule, Daugaliyeva Aida, Vitmer Svetlana

Abstract readReview
In one paragraph

Review in Veterinary world, 2025. 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
–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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

5 authors.

Kydyr NazerkeLLP "Scientific and Production Center, Center of Advanced Technologies in Agriculture", 23 Karim Sutyshev, 150000, Petropavlovsk, Republic of Kazakhstan.
Asaubayev RuslanLLP "Scientific and Production Center, Center of Advanced Technologies in Agriculture", 23 Karim Sutyshev, 150000, Petropavlovsk, Republic of Kazakhstan.
Daugaliyeva SauleLLP "Scientific Production Center of Microbiology and Virology", 105 Bogenbay Batyr, 050010, Almaty, Republic of Kazakhstan.
Daugaliyeva AidaLLP "Kazakh Research Institute for Livestock and Fodder Production", 51 Zhandosov, 050035, Almaty, Republic of Kazakhstan.
Vitmer SvetlanaLLP "Scientific and Production Center, Center of Advanced Technologies in Agriculture", 23 Karim Sutyshev, 150000, Petropavlovsk, Republic of Kazakhstan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral infections continue to pose major challenges to pig health, farm productivity, and global food security. Early and accurate diagnosis is the cornerstone of disease prevention, surveillance, and control in swine populations. In recent years, remarkable progress has been achieved in molecular, serological, and digital diagnostic technologies, enabling more rapid, sensitive, and field-adaptable detection of important porcine viruses such as African swine fever virus, porcine reproductive and respiratory syndrome virus, and classical swine fever virus. This review summarizes current and emerging diagnostic approaches, highlighting polymerase chain reaction (PCR) and its advanced forms, quantitative PCR and digital PCR, as the gold standards for laboratory confirmation. The advent of next-generation sequencing and metagenomics has revolutionized pathogen discovery and genomic surveillance, providing comprehensive insights into viral evolution and transboundary transmission. Isothermal amplification techniques such as loop-mediated isothermal amplification and recombinase polymerase amplification have shown strong potential for on-farm diagnosis due to their simplicity, rapidity, and minimal equipment requirements. Innovations such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated-based assays, biosensors, lab-on-a-chip platforms, and point-of-care testing devices are bridging the gap between laboratory precision and field application, allowing rapid decision-making during outbreaks. The integration of artificial intelligence, machine learning, and geographic information systems has further enhanced diagnostic interpretation, real-time data sharing, and early outbreak prediction under the One Health framework. Despite these advances, challenges remain in ensuring assay standardization, affordability, and equitable access in resource-limited regions. Continued international collaboration, data sharing, and policy harmonization under the guidance of the Food and Agriculture Organization, the World Organization for Animal Health, and the World Health Organization are essential for the global control of swine viral diseases. Ultimately, combining molecular innovation with digital adaptability offers the most promising path toward resilient, cost-effective, and sustainable diagnostic systems for safeguarding animal and public health.

Indexed as

artificial intelligencebiosensorsemerging technologiesmicrofluidic platformsmolecular diagnosticsOne Healthviral infections

Identifiers

PMID41716172
PMCPMC12914012

What Socratic 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 Socratic graph.