| The spread of COVID-19 is an important challenge facing human and a hot spot in modern infectious disease research.Research using traditional infectious disease dynamics models and analysis of geospatial and temporal characteristics is currently the main approach to COVID-19.The parameters of the infectious disease dynamics model are complex and changeable,and it is difficult to obtain appropriate parameter values.The methods of geographic spatiotemporal feature analysis do not consider human mobility,but human activities are closely related to the spread of the epidemic.This paper proposes a COVID-19 epidemic analysis method based on human migration network communities.Firstly,a single network and a sequence network of population migration are constructed by using population migration data at the city level,and communities in the network are mined by community discovery algorithm.Then,the spatial distribution characteristics of the single network community of human migration were analyzed,and the data of COVID-19 epidemic in the single network community were statistically analyzed through spatial superposition calculation.Finally,dynamic regions were found from the network communities of human migration sequence,and the COVID-19 epidemic data in the dynamic regions were statistically analyzed through spatial superposition operation,and the changing relationship between the network communities of human migration and the spread of COVID-19 was obtained.Based on the method proposed in this paper,experiments are carried out based on the data of the population migration network community and the COVID-19 epidemic during the Spring Festival in China in 2020.The contents of the experimental results include:(1)Spatial distribution characteristics of a single network community: There is no spatial isolation in the composition of the community structure except for Hainan Province and Northeast China.Affected by the COVID-19 epidemic,people’s travel is mainly short-distance and neighboring cities,so the community structure is basically composed of nearby cities.In the first stage,Hainan province had a close connection with northeast China to form same community,but as COVID-19 spread across the country,long-distance travel was restricted and the close connection began to disappear.(2)Statistical analysis of the COVID-19 epidemic in a single network community: The COVID-19 epidemic spreads according to distance in space.Communities close to Hubei Province are greatly affected by the epidemic,and communities far away are less affected by the epidemic.The number of confirmed cases in a single network community(except Hubei Province)in different time periods showed a trend of rise to decline.(3)Spatial distribution characteristics of unstable regions found in sequential network communities: The unstable areas are unevenly distributed,mainly in the northwest and border areas of china.Remote areas are less affected by the Covid-19 pandemic,so there are no restrictions on crowd travel,leading to the definition of unstable areas in these areas.(4)Statistical analysis of the COVID-19 in unstable areas: The degree of instability of cities including unstable areas has a negative correlation with the data of the COVID-19 epidemic,and the reciprocal of the distance to Wuhan has a positive correlation with the data of the COVID-19 epidemic.The higher the instability of the city including the unstable area,the less number of people infected by the COVID-19 epidemic in the city,but the closer the distance to Wuhan,the greater the impact of the COVID-19 epidemic,and the more the number of infected people.For the prevention and control of the new crown epidemic,the strategy of controlling distance can be adopted.Areas close to the epidemic area should strictly abide by the epidemic prevention and control policy and control crowd activities.In areas far from the epidemic area,crowd activities can be implemented with looser policies,does not affect the economic and social production of the region. |
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