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    基于人口流动大数据的传染病初期感染人数估计:以新冠肺炎为例

    Initial Infections Number Estimation of Infectious Diseases Based on the Big Data of Population Flow

    • 摘要: 基于运营商提供的匿名、累计手机定位大数据,提取全国人口在春节期间的出行信息,并基于爆发地区人口流动情况构建模型推算武汉感染患者数量以及增长趋势。研究结果表明,截止武汉“封城”前,基于湖北省外 50 座城市感染情况构建DPNA-M 模型估计武汉感染人数为 26 464 人,与依据境外检出概率的估计结果接近。与现有的估计方法相比,该模型不严格依赖于疫区统计数据,估计结果更准确,在模型稳健性与应用普适性方面更具优势。

       

      Abstract: Based on the anonymities provided by the service providers, accumulated mobile positioning bit data, the travel information of nationwide population during the spring festival is extracted, population mobility situation in the epidemic outbreak area is based on to construct model to calculate the number of infected individuals in Wuhan and the increasing trends. The study results show that before the lockdown of Wuhan, based on the infected status of 50 cities outside Hubei province, DPNA-M model is built to estimate the number of infected people in Wuhan to be 26 464, the result is close to early overseas estimate results. Compared with existing estimation methods, the model is not strictly dependent on the statistics data in the epidemic area, its estimation results are more accurate, more superior in the stability and application universality of model.

       

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