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评估非流行地区伊蚊传播虫媒病毒病的时空风险:以西班牙北部为例。

Assessing the spatio-temporal risk of Aedes-borne arboviral diseases in non-endemic regions: The case of Northern Spain.

作者信息

Guerrero Bruno V, Steindorf Vanessa, Blasco-Aguado Rubén, Mateus Luís, Cevidanes Aitor, Barandika Jesús F, Pérez Ana Ramírez de La Peciña, Van-Dierdonck Joseba Bidaurrazaga, Armentia Jesús Angel Ocio, Stollenwerk Nico, Aguiar Maíra

机构信息

BCAM - Basque Center for Applied Mathematics, Bilbao, Spain.

Animal Health Department, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), Derio, Bizkaia, Spain.

出版信息

PLoS Negl Trop Dis. 2025 Jul 28;19(7):e0013325. doi: 10.1371/journal.pntd.0013325. eCollection 2025 Jul.

Abstract

Arboviral diseases represent a growing global health challenge. While dengue cases surge in endemic regions, non-endemic areas in southern Europe are seeing a rise in imported cases of dengue, Zika, and chikungunya, along with the first autochthonous dengue transmissions. The expanding Aedes mosquito populations, influenced by climate change, and increased international travel introducing viremic cases further elevate the risk of outbreaks. These trends emphasize the urgent need for effective risk assessment and timely intervention strategies. We present a data-driven methodology to assess the spatio-temporal risk of Aedes-borne arboviral diseases in non-endemic settings, addressing key limitations of models developed primarily for endemic regions and challenges related to limited data availability. Our approach builds on the SIRUVY human-vector compartmental model and incorporates stochastic formulations to capture variability in imported cases and mosquito density - two critical drivers of autochthonous transmission and outbreak emergence. This framework improves risk estimation and offers insights into transmission dynamics in regions where outbreaks are rare and unpredictable, shaped by sporadic case importations and a non-persistent vector presence. Using data from the Basque Country (2019-2023), including Aedes mosquito egg counts as a proxy for vector abundance and records of imported cases, we mapped the monthly risk of local transmission at the municipal level and conducted a scenario-based risk assessment aligned with Spain's entomological classification. Our findings indicate a growing presence of Aedes mosquitoes and an increasing transmission risk in urban and peri-urban areas of the Basque Country, revealing shifting hotspots of possible arboviral disease transmission. These results highlight the importance of sustained surveillance to identify high-risk locations and prioritize targeted public health interventions to prevent potential outbreaks.

摘要

虫媒病毒病是全球日益严峻的健康挑战。在登革热病例在流行地区激增的同时,南欧的非流行地区登革热、寨卡病毒病和基孔肯雅热的输入病例也在增加,同时还出现了首例本地登革热传播。受气候变化影响,伊蚊种群不断扩大,国际旅行增加导致病毒血症病例输入,进一步提高了疫情爆发的风险。这些趋势凸显了进行有效风险评估和及时采取干预策略的迫切需求。我们提出了一种数据驱动的方法,用于评估非流行地区伊蚊传播的虫媒病毒病的时空风险,解决了主要为流行地区开发的模型的关键局限性以及与数据可用性有限相关的挑战。我们的方法基于SIRUVY人-媒介分区模型,并纳入随机公式以捕捉输入病例和蚊虫密度的变异性——这是本地传播和疫情爆发的两个关键驱动因素。该框架改进了风险估计,并深入了解了疫情罕见且不可预测的地区的传播动态,这些地区受零星病例输入和非持久性媒介存在的影响。利用巴斯克地区(2019-2023年)的数据,包括将伊蚊卵计数作为媒介丰度的指标以及输入病例记录,我们绘制了市级层面本地传播的月度风险图,并进行了与西班牙昆虫学分类一致的基于情景的风险评估。我们的研究结果表明,巴斯克地区城市和城郊地区伊蚊的存在日益增加,传播风险也在上升,揭示了可能的虫媒病毒病传播热点的变化。这些结果凸显了持续监测对于识别高风险地点以及优先开展有针对性的公共卫生干预措施以预防潜在疫情爆发的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e271/12313078/db84854c8eab/pntd.0013325.g001.jpg

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