Center Agriculture Food Environment, University of Trento, San Michele all'Adige, Italy.
Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Italy.
Sci Data. 2024 Jun 15;11(1):636. doi: 10.1038/s41597-024-03482-y.
Modelling approaches play a crucial role in supporting local public health agencies by estimating and forecasting vector abundance and seasonality. However, the reliability of these models is contingent on the availability of standardized, high-quality data. Addressing this need, our study focuses on collecting and harmonizing egg count observations of the mosquito Aedes albopictus, obtained through ovitraps in monitoring and surveillance efforts across Albania, France, Italy, and Switzerland from 2010 to 2022. We processed the raw observations to obtain a continuous time series of ovitraps observations allowing for an extensive geographical and temporal coverage of Ae. albopictus population dynamics. The resulting post-processed observations are stored in the open-access database VectAbundance.This initiative addresses the critical need for accessible, high-quality data, enhancing the reliability of modelling efforts and bolstering public health preparedness.
建模方法在通过估计和预测病媒丰度和季节性来支持地方公共卫生机构方面发挥着至关重要的作用。然而,这些模型的可靠性取决于标准化、高质量数据的可用性。为了满足这一需求,我们的研究重点是收集和协调 2010 年至 2022 年期间通过在阿尔巴尼亚、法国、意大利和瑞士进行的监测和监测工作中的诱卵器获得的蚊子 Aedes albopictus 的卵计数观察结果,并对其进行了协调。我们处理原始观察结果,以获得连续的诱卵器观察时间序列,从而可以广泛地了解 Ae. albopictus 种群动态。处理后的观察结果存储在开放获取数据库 VectAbundance 中。这一举措满足了对可访问、高质量数据的迫切需求,提高了建模工作的可靠性,并增强了公共卫生准备。