Travel-related importation risk of mpox from Hong Kong to Shenzhen in 2023: A modeling study

IF 2.5 3区医学 Q1 Medicine

Infectious Disease Modelling Pub Date : 2025-09-14 DOI:10.1016/j.idm.2025.09.005

Ruohan Chen , Jia Wan , Dongfeng Kong , Cong Niu , Zengyang Shao , Chijun Zhang , Mingda Xu , Yuan Bai , Eric Lau , Zhen Zhang , Zhanwei Du

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引用次数: 0

Abstract

Mpox, a viral zoonotic disease formerly known as monkeypox, has gained global attention following a multi-country outbreak in 2022-23, primarily linked to close intimate contact. In China, mpox cases surged in June 2023, with nearly a quarter of new cases concentrated in Guangdong Province, particularly Shenzhen. This study aimed to estimate the importation risk of mpox cases from Hong Kong to Shenzhen in 2023, utilizing cross-regional population mobility data from January to October 2023. The analysis focused on local transmission in Hong Kong and the probability of mpox importation into Shenzhen. Results revealed a significant importation risk, with over a 50 % chance of at least one travel-based mpox case from Hong Kong in June 2023. The study underscores the necessity of enhancing inbound surveillance for travelers from high mpox prevalence regions. It is suggested that regional governments implement tailored strategies, including enhanced surveillance and dynamic risk assessment for effective cross-border disease management, supported by robust monitoring and coordinated actions across jurisdictions.

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2023年香港到深圳麻疹的旅游相关输入风险：模型研究

Mpox是一种病毒性人畜共患疾病，以前称为猴痘，在2022-23年多个国家暴发后引起了全球关注，主要与密切接触有关。在中国，mpox病例在2023年6月激增，近四分之一的新病例集中在广东省，特别是深圳。本研究旨在利用2023年1 - 10月的跨区域人口流动数据，估计2023年香港到深圳的麻疹病例输入风险。分析的重点是在香港的本地传播和m痘输入到深圳的可能性。结果显示存在显著的输入风险，2023年6月香港至少有一例基于旅行的麻疹病例的可能性超过50%。该研究强调有必要加强对来自麻疹高流行地区的旅行者的入境监测。建议区域政府实施有针对性的战略，包括加强监测和动态风险评估，以实现有效的跨界疾病管理，并辅以强有力的监测和跨管辖区协调行动。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Infectious Disease Modelling Mathematics-Applied Mathematics

CiteScore

17.00

自引率

3.40%

发文量

审稿时长

17 weeks

期刊介绍： Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.