Evidence map›Paper›PMID 42756954›Full record

ArticleOne health (Amsterdam, Netherlands)2026

Exploring the impacts of wildlife trade on zoonotic spillover and disease outbreaks: A multiple-perspective study.

Kai Wang, Emilio Pagani-Núñez, Ziyi Wang, Junjie Ren, Xintong Wei, Ying Chen, Binbin V Li, Chengxiu Ling, Lingyun Xiao

Abstract read
In one paragraph

Article in One health (Amsterdam, Netherlands), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

9 authors.

Kai WangAcademy of Life and Natural Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.
Emilio Pagani-NúñezCentre for Conservation and Restoration Science, School of Applied Sciences, Edinburgh Napier University, Edinburgh EH114BN, UK.
Ziyi WangAcademy of Life and Natural Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.
Junjie RenPublic Health Clinical Center Affiliated to Shandong University, Jinan 250013, China.
Xintong WeiAcademy of Life and Natural Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.
Ying ChenAcademy of Life and Natural Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.
Binbin V LiEnvironmental Research Center, Duke Kunshan University, Kunshan 215316, China.
Chengxiu LingAcademy of Life and Natural Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.
Lingyun XiaoAcademy of Life and Natural Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of zoonotic pathogens from wildlife poses a major global health threat, contributing to frequent and impactful disease outbreaks. While wildlife trade is recognized as a key driver of zoonotic spillover, no studies have quantitatively assessed how trade volume relates to the occurrence and frequency of emerging infectious diseases (EIDs) at a global scale, especially regarding the impact of extreme volumes. This study addresses this gap by conducting a multiple-perspective analysis on country-level yearly zoonotic EID data from 1975 to 2013 using a Bayesian zero-inflated negative binomial spatiotemporal model combined with extreme value theory to evaluate the influence of wildlife trade on EID occurrence, frequency and extreme events. After adjusting for reporting bias and conducting rigorous sensitivity analyses, we find that wildlife import volume significantly increases the probability of zoonotic EID occurrence and extreme outbreaks, but does not affect the frequency. In contrast, wildlife export volume shows no significant impact on either EID occurrence or frequency, and a much weaker effect on extreme events. Beyond wildlife trade, mammalian richness and socioeconomic indicators exhibit complex associations with EID patterns mediated by the varying effectiveness of national disease surveillance systems. This integrated methodology advances understanding of zoonotic disease drivers and underscores a critical import-driven risk profile, suggesting that pandemic prevention strategies should prioritize biosecurity and regulation at wildlife importation points.

Indexed as

Bayesian spatiotemporal modelEmerging infectious diseasesExtreme value theoryWildlife tradeZoonotic spillover

Identifiers

PMID42756954
PMCPMC13583772

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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.