Evidence map›Paper›PMID 40285016›Full record

ArticleViruses2025

Environmental Suitability of Kazakhstan to Highly Pathogenic Avian Influenza Using Data on Eurasian Outbreaks, 2020-2024.

Asem Zh Abenova, Yersyn Y Mukhanbetkaliyev, Ablaikhan S Kadyrov, Igor I Sytnik, Alexander B Shevtsov, Fedor I Korennoy, Irene Iglesias Martin, Andres M Perez, Sarsenbay K Abdrakhmanov

Abstract read
In one paragraph

Article in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Ecological Niche Modeling of PathogenicPathogens (Basel, Switzerland) · 2026
    Article
  3. Article
  4. Review
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.

Asem Zh AbenovaFaculty of Veterinary and Animal Husbandry Technology, S. Seifullin Kazakh Agro Technical Research University, Astana 010011, Kazakhstan.
Yersyn Y MukhanbetkaliyevFaculty of Veterinary and Animal Husbandry Technology, S. Seifullin Kazakh Agro Technical Research University, Astana 010011, Kazakhstan.
Ablaikhan S KadyrovFaculty of Veterinary and Animal Husbandry Technology, S. Seifullin Kazakh Agro Technical Research University, Astana 010011, Kazakhstan.
Igor I SytnikNational Center for Biotechnology, Astana 010011, Kazakhstan.
Alexander B ShevtsovNational Center for Biotechnology, Astana 010011, Kazakhstan.ORCID 0000-0002-0307-1053
Fedor I KorennoyFederal Centre for Animal Health (FGBI ARRIAH), Vladimir 600901, Russia.ORCID 0000-0002-7378-3531
Irene Iglesias MartinCentro de Investigación en Sanidad Animal (CISA), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Consejo Superior de Investigaciones Científicas (CSIC), 28130 Madrid, Spain.ORCID 0000-0003-3472-6873
Andres M PerezCenter for Animal Health and Food Safety, College of Veterinary Medicine, University of Minnesota, St. Paul Campus, St. Paul, MN 55108, USA.
Sarsenbay K AbdrakhmanovFaculty of Veterinary and Animal Husbandry Technology, S. Seifullin Kazakh Agro Technical Research University, Astana 010011, Kazakhstan.ORCID 0000-0003-3707-3767

Funding

Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan AP23489183
6 · The paper itself

Abstract

Highly pathogenic avian influenza (HPAI) is a highly contagious disease of domestic, synanthropic, and wild birds that has demonstrated a sharp rise globally since 2020. This study intends to examine environmental and demographic factors most significantly associated with HPAI (H5N1 and H5N8) outbreaks in Kazakhstan, 2020-2024, and to identify areas of potential underreporting of the disease. Two ecological niche models were developed, namely an "occurrence model" (considering climatic and environmental factors influencing the likelihood of HPAI occurrence) and a "reporting model" (that assesses the probability of disease reporting based on human and poultry population demography). Both models were trained using outbreak locations in countries neighboring Kazakhstan (Afghanistan, China, Hong Kong, Iran, Iraq, Pakistan and Russia), and then tested using the HPAI outbreak locations in Kazakhstan. Results suggested a good fit for both models to Kazakhstani outbreaks (test AUC = 0.894 vs. training AUC = 0.915 for "occurrence model", and test AUC = 0.869 vs. training AUC = 0.872 for "reporting model"). A cluster of high occurrence-to-reporting ratio was detected in the south-western region of Kazakhstan, close to the Caspian Sea, suggesting a need for enhancing surveillance efforts in this zone as well as in some other areas of Pavlodar, Northern Kazakhstan, Western Kazakhstan, Qyzylorda, and Eastern Kazakhstan. Results presented here will help inform the design and implementation of control strategies for HPAI in Kazakhstan with the ultimate goal of promoting disease prevention and control in the country.

Indexed as

Disease OutbreaksInfluenza A Virus, H5N1 SubtypeInfluenza A Virus, H5N8 SubtypeInfluenza in BirdsAnimalsBirdsHumansKazakhstanPoultryPoultry Diseasesepidemiologyhighly pathogenic avian influenzaKazakhstanmaxentoutbreakssuitabilityunderreporting

Identifiers

PMID40285016
PMCPMC12031396

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Registered trials

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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.