Evidence map›Paper›PMID 40777847›Full record

ArticleGeoHealth2025

Integrating Citizen Science and Remote Sensing Data to Identify Key Environmental Factors Influencing H5N1 Avian Influenza Virus Potential Spillover Risk in the Philippines.

John Oliver Sayseng, Ting-Wu Chuang

Abstract read
In one paragraph

Article in GeoHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

John Oliver SaysengInternational Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei Taiwan.ORCID https://orcid.org/0000-0002-5849-8804
Ting-Wu ChuangDepartment of Molecular Parasitology and Tropical Diseases School of Medicine College of Medicine Taipei Medical University Taipei Taiwan.ORCID https://orcid.org/0000-0001-8359-8172

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highly pathogenic avian influenza (HPAI) virus presents a serious threat to poultry and public health worldwide, with transmission dynamics shaped by avian migration patterns and environmental conditions. Recent outbreaks in the Philippines highlight the urgent need for effective control measures. While previous studies have shown the importance of waterfowl-to-poultry transmission and farm-to-farm spread, the spillover risk to local avian species remains underexplored. This study aimed to examine H5N1-HPAI outbreaks in poultry in relation to environmental factors and local avian species in the Philippines. We applied a two-step ecological niche modelling approach using maximum entropy algorithms. First, environmental variables from remote sensing images were used to predict the distribution of 10 common avian species based on citizen science data from the eBird platform. Next, these avian distribution data were combined with environmental variables to create a risk map for H5N1-HPAI outbreaks in the Philippines. The H5N1-HPAI risk model demonstrated strong predictive performance, with an AUCROC value of 0.936 ± 0.026. Key factors contributing to predicted H5N1-HPAI risk included precipitation levels, population density, and avian species such as the Eurasian Tree Sparrow and Zebra Dove. The higher risk of spillover for the two local avian species may be due to their shared similar environmental signatures with outbreak poultries. The risk map highlighted Metro Manila and Central Luzon as high-risk regions of H5N1-HPAI. This study identified the main clusters and environmental factors associated with avian influenza outbreaks in poultry in the Philippines. Additionally, the transmission risk may threaten the local avian population.

Indexed as

avian influenza viruseBirdMaxentremote sensing

Identifiers

PMID40777847
PMCPMC12329429

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.