考虑传染概率的政府防疫管控策略演化仿真

Evolutionary simulation of governments'pandemic control strategies in presence of infection probability

为提高重大公共卫生事件的管控效率,以新型冠状病毒肺炎疫情为例,首先,构建考虑传染概率的政府部门-公众演化博弈模型,刻画政府部门与公众之间的博弈关系;然后,求解模型,分析影响政府部门与公众行为演化的关键要素;最后,结合武汉疫情演变的实际情况进行Matlab仿真分析,验证模型的有效性与可行性。结果表明:传染概率对政府部门与公众的策略选择具有重要影响,当传染概率较小,且政府的管控成本大于管控收益时,系统最终演化为政府消极应对、公众不自律的稳定状态;当传染概率突破一定阈值、政府部门的管控收益小于成本时,增加对公众的惩罚力度反而会降低政府部门与公众应对疫情变化的响应速度;而加强对政府部门的惩罚却能提高政府的响应速度,公众选择自律策略的概率也会提高,可以促进疫情向较好方向发展。

In order to effectively curb the rapid spread of major public health emergencies,taking COVID-19 as an example,firstly,a government-public evolutionary game model considering the probability of infection was constructed to depict the game relationship between the government and the public.Then,the key factors affecting the evolution of the government and public behavior were analyzed through the model solution.Finally,MATLAB simulation analysis was carried out based on the actual situation of the evolution of the epidemic in Wuhan to verify the validity and feasibility of the model and conclusions.Results indicate that infection probability plays an indispensable role in the selection of strategies of the government and the public.When the probability of infection is small,and the cost of government is greater than the benefit,the system eventually evolves into a stable state in which the government responds passively and the public does not exercise self-discipline.When the infection probability reaches a fixed value and the revenue of the government is less than cost,the increase of punishment on the public would slow down the response time of government and the public.However,in terms of the same situation,the increase of punishment on the government is useful to upgrade their response efficiency.In addition,it is conducive to enhancing the probability of the selection of self-discipline strategies for the public,which can promote the development of the epidemic in a better direction.