Luo Fei, Jiang Dan, Xu Jing-Ru, Tan Yan, Yang Meng-Ping, Xie Jun, Yang Sen-Ping, Shen Hai-Mo, Zhou Shuang, Chen Jun-Hu
National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Center for Tropical Diseases; National Center for International Research On Tropical Diseases, Shanghai, 200025, China.
Chongqing Center for Diseases Control and Prevention, Chongqing, 400042, China.
Malar J. 2025 Jul 11;24(1):225. doi: 10.1186/s12936-025-05476-6.
Although China has achieved malaria elimination, the risk of reintroduction persists due to imported Plasmodium falciparum cases. Occasional infections without a clear travel history present challenge to routine epidemiological investigation and underscore the need for advanced tracing tools.
Whole-genome sequencing (WGS), principal component analysis (PCA), and identity-by-descent (IBD) analysis were applied to investigate a P. falciparum case reported in Chongqing, China, in 2019. The patient had no overseas travel history but was treated at the same hospital with a confirmed imported case from the Democratic Republic of the Congo (DRC).
Genomic analysis placed the unidentified case within the West and Central African parasite cluster. IBD analysis showed a high degree of relatedness (IBD = 0.9) between this case and the DRC-imported case, suggesting a potential transmission link. These findings indicate the likely Central African origin of the infection and raise concerns about local transmission risk even in a post-elimination setting.
This case highlights the limitations of traditional epidemiology in detecting cryptic transmission routes. Genomic epidemiology enables finer-scale resolution of parasite origin and relatedness, providing critical evidence in elimination-phase malaria control.
Genomic tools such as WGS, PCA, and IBD analysis can enhance national malaria surveillance systems by identifying infection sources and clarifying transmission routes. Their integration supports elimination-stage strategies and helps prevent malaria reintroduction in formerly endemic regions.
尽管中国已实现疟疾消除，但由于输入性恶性疟原虫病例，仍存在重新引入疟疾的风险。偶尔出现的无明确旅行史感染病例给常规流行病学调查带来挑战，并凸显了先进追踪工具的必要性。
应用全基因组测序（WGS）、主成分分析（PCA）和同源性分析（IBD）对2019年在中国重庆报告的1例恶性疟原虫病例进行调查。该患者无海外旅行史，但在同一家医院接受治疗，该院有1例来自刚果民主共和国的确诊输入病例。
基因组分析将该不明病例归入西非和中非寄生虫簇。IBD分析显示该病例与刚果民主共和国输入病例之间存在高度相关性（IBD = 0.9），提示可能存在传播联系。这些发现表明该感染可能起源于中非，并引发了对即使在消除疟疾后环境中本地传播风险的担忧。
该病例凸显了传统流行病学在检测隐匿传播途径方面的局限性。基因组流行病学能够更精细地解析寄生虫的起源和相关性，为消除阶段的疟疾控制提供关键证据。
WGS、PCA和IBD分析等基因组工具可通过识别感染源和阐明传播途径来加强国家疟疾监测系统。它们的整合支持消除阶段的策略，并有助于防止疟疾在以前的流行地区重新引入。
