Genomic epidemiology reveals the origins and transmission dynamics of chikungunya virus in China.

IF 5.5 1区 医学
Wei Chang, Mengyuan Zheng, Yanxian Jiang, Gaowen Liu, Xiao Chen, Xue Wang, Yan Guo, Li Liu, Yue Feng, Xueshan Xia
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引用次数: 0

Abstract

Background: The chikungunya virus (CHIKV) poses a significant public health threat in China, driven by travel-related introductions and local outbreaks. A comprehensive understanding of the spatiotemporal dynamics, viral genetic diversity, and origins of these outbreaks is imperative for surveillance and control measures. This study aimed to characterize the spatiotemporal dynamics of CHIKV in China and elucidate the evolutionary origins of outbreak lineages.

Methods: A systematic collection of epidemiological data on CHIKV cases in China was conducted up to December 2025, resulting in the identification of 416 imported cases and 25,948 local cases. A comprehensive retrieval of all publicly available CHIKV genomes from China was conducted. The composition of viral lineages was determined by employing maximum likelihood phylogeny. Substitution rates were estimated, and time-scaled transmission clusters were generated using Bayesian evolutionary analysis. Discrete phylogeographic reconstruction was used to infer spatial diffusion pathways, with statistical support evaluated using Bayes Factors.

Results: From 1987 to 2025, imported chikungunya cases in China mainly originated from Southeast Asia, especially Myanmar, and were accompanied by several major local outbreaks. Significant outbreaks were reported in Guangdong (2010 and 2025), Yunnan (2019), and Taiwan (2019), with the largest outbreak occurring in Guangdong in 2025 and involving 25,335 cases. Genomic analysis of 314 sequences revealed that the East/Central/South African lineage was the most prevalent, accounting for 92.0% of cases. This lineage includes the Indian Ocean (IOL) and Central African clades. The Asian lineage accounted for the remaining 8.0%. Bayesian analysis identified four independent outbreak clusters. Phylogeographic data supported the conclusion that there were multiple introductions. The IOL clusters spread from Africa and South Asia to Southeast Asia. The 2025 Guangdong outbreak cluster (Central African clade) suggests a possible association with introduction from Africa. The Asian lineage circulated persistently in Southeast Asia before entering Yunnan Province.

Conclusions: CHIKV outbreaks in China are linked to imported cases, and outbreak lineages consistently match recent imports. The virus entered through various, geographically independent routes. These findings underscore the need for genomic-informed surveillance at key entry points and in high-risk regions to anticipate and prevent local epidemics.

基因组流行病学揭示基孔肯雅病毒在中国的起源和传播动力学。
背景:基孔肯雅病毒(CHIKV)在中国造成了重大的公共卫生威胁,主要是由与旅行有关的传入和当地疫情造成的。全面了解这些暴发的时空动态、病毒遗传多样性和起源对于监测和控制措施至关重要。本研究旨在描述中国CHIKV的时空动态特征,并阐明暴发谱系的进化起源。方法:系统收集截至2025年12月中国境内流行病学资料,共发现输入病例416例,本地病例25948例。对来自中国的所有可公开获得的CHIKV基因组进行了全面检索。采用最大似然系统发育法确定病毒谱系的组成。利用贝叶斯进化分析方法估计了替代率,并生成了时间尺度的传播聚类。离散系统地理重构用于推断空间扩散路径,并使用贝叶斯因子评估统计支持度。结果:1987 - 2025年,中国输入性基孔肯雅热病例主要来源于东南亚,以缅甸为主,并伴有几次重大地方性暴发。广东(2010年和2025年)、云南(2019年)和台湾(2019年)均有重大疫情报告,其中2025年广东疫情最大,累计病例25335例。对314个序列的基因组分析显示,东部/中部/南非谱系最为普遍,占病例的92.0%。这个谱系包括印度洋(IOL)和中非分支。亚洲血统占剩余的8.0%。贝叶斯分析确定了四个独立的爆发集群。系统地理学数据支持有多次引种的结论。人工晶状体群从非洲和南亚扩散到东南亚。2025年广东暴发集群(中非分支)表明可能与非洲传入有关。亚洲血统在进入云南省之前一直在东南亚传播。结论:中国的CHIKV暴发与输入病例有关,暴发谱系与最近的进口病例一致。病毒通过各种地理上独立的途径进入。这些发现强调需要在关键切入点和高风险地区进行基因组知情监测,以预测和预防当地流行病。
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来源期刊
Infectious Diseases of Poverty
Infectious Diseases of Poverty INFECTIOUS DISEASES-
自引率
1.20%
发文量
368
期刊介绍: Infectious Diseases of Poverty is an open access, peer-reviewed journal that focuses on addressing essential public health questions related to infectious diseases of poverty. The journal covers a wide range of topics including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies and application. It also considers the transdisciplinary or multisectoral effects on health systems, ecohealth, environmental management, and innovative technology. The journal aims to identify and assess research and information gaps that hinder progress towards new interventions for public health problems in the developing world. Additionally, it provides a platform for discussing these issues to advance research and evidence building for improved public health interventions in poor settings.
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