The global distribution and diversity of wild-bird-associated pathogens: An integrated data analysis and modeling study

Yunbo Qiu; Chenlong Lv; Jinjin Chen; Yanqun Sun; Tian Tang; Yuanyuan Zhang; Yufeng Yang; Guolin Wang; Qiang Xu; Xiaoai Zhang; Feng Hong; Simon I Hay; Liqun Fang; Wei Liu

doi:10.1016/j.medj.2024.11.006

The global distribution and diversity of wild-bird-associated pathogens: An integrated data analysis and modeling study

Med. 2024 Dec 7:S2666-6340(24)00447-1. doi: 10.1016/j.medj.2024.11.006. Online ahead of print.

Authors

Yunbo Qiu¹, Chenlong Lv², Jinjin Chen², Yanqun Sun², Tian Tang², Yuanyuan Zhang², Yufeng Yang³, Guolin Wang², Qiang Xu², Xiaoai Zhang², Feng Hong⁴, Simon I Hay⁵, Liqun Fang⁶, Wei Liu⁷

Affiliations

¹ School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 550025, P.R. China; State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, P.R. China.
² State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, P.R. China.
³ State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, P.R. China; School of Public Health, Anhui Medical University, Hefei 230022, P.R. China.
⁴ School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 550025, P.R. China. Electronic address: hongfeng-73@163.com.
⁵ Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. Electronic address: sihay@uw.edu.
⁶ School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 550025, P.R. China; State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, P.R. China; School of Public Health, Anhui Medical University, Hefei 230022, P.R. China. Electronic address: fang_lq@163.com.
⁷ State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, P.R. China; School of Public Health, Anhui Medical University, Hefei 230022, P.R. China. Electronic address: liuwei@bmi.ac.cn.

PMID: 39701096
DOI: 10.1016/j.medj.2024.11.006

Abstract

Background: Wild birds are significant vectors in global pathogen transmission, but the diversity and spatial distribution of the pathogens detected in them remain unclear. Understanding the transmission dynamics and hotspots of wild-bird-associated pathogens (WBAPs) is crucial for early disease prevention.

Methods: We compiled an up-to-date dataset encompassing all WBAPs by conducting an extensive search of publications from 1959 to 2022, mapped their diversity and global distribution, and utilized three machine learning algorithms to predict geospatial hotspots where zoonotic and emerging WBAPs were prevalent.

Findings: Based on 1,834 selected studies, a total of 760 pathogens associated with 1,438 wild bird species were identified, including 387 emerging and 212 zoonotic pathogens. Migratory birds exhibited higher pathogen richness (593 species) but a lower proportion of zoonotic pathogens (27.2%) compared to resident birds (303 species and 39.3%, both p < 0.01). When comparing different ecological groups, waterfowl had the highest richness of zoonotic pathogens (128 species), followed by songbirds (76 species). The distribution of WBAPs was significantly influenced by the habitat suitability index of wild birds, mammalian richness, and climatic factors. The potential geographical hotspots of zoonotic and emerging WBAPs were widely distributed in tropical areas of Asia, Africa, and South America, with zoonotic WBAPs having a wider distribution in South America.

Conclusions: Our study illustrates that the geographical hotspots of WBAPs are more widespread than reported, especially in low-income areas, and that the identification, surveillance, and prevention of WBAP infections should be prioritized.

Funding: This work was funded by the National Key Research and Development Program of China.

Keywords: Translation to population health; diversity; emerging pathogens; geographical hotspots; machine learning model; wild birds; zoonotic pathogens.