基于社交网络信息的新冠疫情抽检策略研究

Sampling Strategy of COVID-19 Based on Social Network Information

为解决全员定期核酸检测成本高,导致间隔周期长且效率低的问题,给出了基于社交网络信息的抽检策略,将在线社交网络信息与新冠肺炎传播规律融合,建立了带抽检策略的新冠肺炎传播模型。在此基础上,研究了随机抽检策略、熟人监测策略、度大节点目标抽检监测策略三种策略对新冠肺炎传播的影响。研究发现在校园等人群密集接触的环境下,熟人和度大节点目标抽检策略在峰值幅度、峰值时间、早期预警等指标下都好于随机监测策略,减少了新冠病毒传播天数以及感染人数,能更早、更快地控制住疫情,预警效果从高到低依次是度大节点目标监测策略、熟人监测策略、随机监测策略。

The cost of regular nucleic acid testing for all staff is high,resulting in long intervals and low efficiency.This paper presents a sampling strategy based on social network information,integrates online social network information with the spread of COVID-19,and establishes a novel coronavirus spread model with a sampling strategy.On this basis,this paper studies the impact of three strategies on the spread of new coronary pneumonia,namely random sampling strategy,acquaintance monitoring strategy,and large node target sampling monitoring strategy.The study found that the random monitoring strategy is better than the random monitoring strategy in the three indicators of peak amplitude,peak time,and early warning in the specific situation of the campus environment,reducing the number of days of new coronavirus transmission and the number of infected people,and more.To control the epidemic earlier and faster,the early warning effect is from high to low:target monitoring strategy for large nodes,acquaintance monitoring strategy,and random monitoring strategy.