State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, 20 Dong-Da Street, Fengtai District, Beijing 100071, China.
Department of Disease Control and Prevention, No. 926 Hospital of Joint Logistics Support Force, Kaiyuan 661600, China.
Viruses. 2024 Oct 12;16(10):1606. doi: 10.3390/v16101606.
Usutu virus (USUV) is an emerging mosquito-transmitted flavivirus with increasing incidence of human infection and geographic expansion, thus posing a potential threat to public health. In this study, we established a comprehensive spatiotemporal database encompassing USUV infections in vectors, animals, and humans worldwide by an extensive literature search. Based on this database, we characterized the geographic distribution and epidemiological features of USUV infections. By employing boosted regression tree (BRT) models, we projected the distributions of three main vectors (, , and ) and three main hosts (, , and ) to obtain the mosquito index and bird index. These indices were further incorporated as predictors into the USUV infection models. Through an ensemble learning model, we achieved a decent model performance, with an area under the curve (AUC) of 0.992. The mosquito index contributed significantly, with relative contributions estimated at 25.51%. Our estimations revealed a potential exposure area for USUV spanning 1.80 million km globally with approximately 1.04 billion people at risk. This can guide future surveillance efforts for USUV infections, especially for countries located within high-risk areas and those that have not yet conducted surveillance activities.
乌苏图病毒（USUV）是一种新兴的蚊媒传播黄病毒，其人类感染率和地理分布范围不断增加，因此对公共卫生构成潜在威胁。本研究通过广泛的文献检索，建立了一个包含全球蚊媒、动物和人类中 USUV 感染的综合时空数据库。基于该数据库，我们描述了 USUV 感染的地理分布和流行病学特征。通过使用增强回归树（BRT）模型，我们预测了三种主要媒介（ 、 、 ）和三种主要宿主（ 、 、 ）的分布，以获得蚊虫指数和鸟类指数。这些指数进一步作为预测因子纳入 USUV 感染模型。通过集成学习模型，我们实现了较好的模型性能，曲线下面积（AUC）为 0.992。蚊虫指数的贡献显著，估计相对贡献为 25.51%。我们的估计显示，全球有 180 万平方千米的潜在 USUV 暴露区域，约有 10.4 亿人面临风险。这可以指导未来对 USUV 感染的监测工作，特别是针对位于高风险地区的国家和尚未开展监测活动的国家。
