Evidence map›Paper›PMID 41305379›Full record

ArticlePathogens (Basel, Switzerland)2025

Risk Assessment of Avian Influenza Virus Subtype H7 Introduction and Spread in the Russian Federation.

Dmitry Varvashenko, Sergey Shcherbinin, Andrey Varkentin, Viktor Irza, Ilya Chvala, Alexander Sprygin, Mikhail Volkov

Abstract read
In one paragraph

Article in Pathogens (Basel, Switzerland), 2025. 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

7 authors.

Dmitry VarvashenkoFederal Centre for Animal Health, 600901 Vladimir, Russia.ORCID 0009-0004-3906-2302
Sergey ShcherbininFederal Centre for Animal Health, 600901 Vladimir, Russia.ORCID 0000-0002-6434-0683
Andrey VarkentinFederal Centre for Animal Health, 600901 Vladimir, Russia.
Viktor IrzaFederal Centre for Animal Health, 600901 Vladimir, Russia.
Ilya ChvalaFederal Centre for Animal Health, 600901 Vladimir, Russia.ORCID 0000-0002-1659-3256
Alexander SpryginFederal Centre for Animal Health, 600901 Vladimir, Russia.ORCID 0000-0001-5982-3675
Mikhail VolkovFederal Centre for Animal Health, 600901 Vladimir, Russia.ORCID 0000-0002-8819-0720

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Avian influenza (AI) is a highly contagious viral disease affecting both domestic and wild birds, posing a significant threat to poultry farming worldwide. This study aims to analyze the key landscape and population factors associated with H7 avian influenza outbreaks across the Euro-Asian continent and to identify high-risk areas in Russia for the virus's introduction and subsequent spread. Two models were developed using the Maximum Entropy algorithm (MaxEnt): An introduction model predicting the likelihood of avian influenza presence based on climatic, landscape, wild waterfowl and semiaquatic bird population density data; and a spread model estimating outbreak risk in poultry farms using data on synanthropic birds, poultry flock density, and proximity to wild bird habitats. The first model was trained via maximum likelihood using data from H7 avian influenza outbreaks in Europe (Italy, Germany, France, Denmark, Lithuania, the Netherlands) and Southeast Asia (China, Hong Kong, Taiwan, Japan, Cambodia, North Korea, South Korea, Vietnam). The second model was trained using output from the first model. Specifically, areas with a predicted probability of H7 outbreak between 0.9 and 1.0 were used as occurrence points for the model in Russia. The results demonstrated that both models achieved high predictive reliability for avian influenza outbreaks in the Russian Federation: the introduction model (AUC = 0.855) and the spread model (AUC = 0.993). Areas with a high probability of disease occurrence were identified in the Central, Southern, North Caucasian, and Volga Federal Districts. These findings underscore the necessity of enhanced disease surveillance in these regions, as well as in the border areas of the Ural, Siberian, and Far Eastern Federal Districts. The authors recommend strengthening biosecurity measures, enhancing wild bird monitoring in high-risk areas, and maintaining stocks of relevant vaccines to timely contain the outbreaks.

Indexed as

Disease OutbreaksInfluenza A virusInfluenza in BirdsAnimalsBirdsPoultryRisk AssessmentRussiaavian influenzaH7 subtypeprobability of introductionrisksynanthropic birdswild waterfowl

Identifiers

PMID41305379
PMCPMC12655408

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.