Evidence map›Paper›PMID 42599520›Full record

ReviewCurrent microbiology2026

Emerging and Re-Emerging Viral Infections in Poultry: Integrating Traditional and AI-Based Control Strategies.

Asiya Mushtaq, Maliha Gulzar, Syedah Asma Andrabi, Priyanka Syal

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current microbiology, 2026. 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

4 authors.

Asiya MushtaqDepartment of Veterinary Microbiology, International Institute of Veterinary Education and Research, BahuAkbar Rohtak, Haryana, India. drasiyalone@gmail.com.ORCID http://orcid.org/0000-0001-8620-6509
Maliha GulzarDivision of Veterinary Clinical Complex, Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir, Srinagar, Jammu & Kashmir, India.ORCID http://orcid.org/0000-0002-2568-7342
Syedah Asma AndrabiDepartment of Veterinary Pathology, College of Veterinary Science, Guru Angad Dev Veterinary and Animal Sciences University, Rampura Phul, Bathinda, Punjab, India.ORCID http://orcid.org/0000-0001-7397-8470
Priyanka SyalDepartment of Veterinary Pathology, College of Veterinary Science, Guru Angad Dev Veterinary and Animal Sciences University, Punjab, , Ludhiana, India.ORCID http://orcid.org/0000-0002-8829-9996

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Poultry production remains significantly challenged by emerging and re-emerging avian viral diseases, which are influenced by host-pathogen interactions, viral evolution, and intensified farming systems. Viruses like avian influenza viruses (AIV) and Newcastle disease virus (NDV) remain the most persistent threats, while chicken anaemia virus (CAV), avian metapneumovirus (aMPV), adenoviruses, and astroviruses are increasingly recognized for their potential to affect poultry health and productivity. Despite the continued use of vaccination, biosecurity, and conventional diagnostics, effective control is often limited by delayed detection and inadequate integration of surveillance data. This review aims to critically examine the limitations of existing control strategies for major avian viral diseases and to evaluate the potential of artificial intelligence (AI) in improving disease surveillance and management. The current knowledge is synthesized on the basis of epidemiology and drivers of key viral infections and how AI-based tools can enhance predictive surveillance, real-time diagnostics, outbreak risk assessment, and vaccine development. The analysis indicates that AI-driven approaches can improve early detection and enable more effective use of heterogeneous data sources across animal, environmental, and public health domains. Integrating these approaches within a One Health framework offers opportunities to strengthen preparedness and response systems. Notwithstanding these benefits many issues regarding use of AI still need to be addressed for successful deployment of AI in diagnosing diseases.

Indexed as

Artificial IntelligenceCommunicable Diseases, EmergingPoultry DiseasesVirus DiseasesAnimalsDisease OutbreaksPoultry

Identifiers

What Socratic holds

Textmetadata
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.