利用 GPS 人员流动数据进行流行病建模的巨大潜力和艰巨挑战。

IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Nature computational science Pub Date : 2024-06-19 DOI:10.1038/s43588-024-00637-0
Francisco Barreras, Duncan J. Watts
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引用次数: 0

摘要

大规模 GPS 定位数据集在测量人类流动性和人际接触方面具有巨大的潜力,而这两方面对于数据驱动的流行病学都至关重要。然而,尽管这些数据具有潜力并在 COVID-19 大流行期间被广泛采用,但这些数据仍面临着一些挑战,使人们对其应用的有效性和稳健性产生了担忧。在此,我们概述了两类挑战--一些与访问和处理这些数据有关,一些与数据质量有关--并提出了解决这些挑战的几个研究方向。
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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The exciting potential and daunting challenge of using GPS human-mobility data for epidemic modeling
Large-scale GPS location datasets hold immense potential for measuring human mobility and interpersonal contact, both of which are essential for data-driven epidemiology. However, despite their potential and widespread adoption during the COVID-19 pandemic, there are several challenges with these data that raise concerns regarding the validity and robustness of its applications. Here we outline two types of challenges—some related to accessing and processing these data, and some related to data quality—and propose several research directions to address them moving forward. While large-scale GPS location datasets have been instrumental to applications in epidemiology, there are still several challenges with these data that should be considered and addressed to make data-driven epidemiology more reliable.
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