Visual analytics of urban epidemic situation development and dynamic regulation - Song WANG; Shijie CHEN; Hanglin LI; Xiaohui LI; Qiongfang FENG; Huijie WANG (大数据)
In order to solve the reasonable allocation of limited medical resources for patients, a visual platform for dynamic control of cabin hospital was built based on the dataset of the COVID-19 epidemic in Wuhan cabin hospital, which integrates multi-source data such as public opinion, space-time trajectory and science popularization.The droppingwater diagram was introduced to dynamically monitor the overall situation of the cabin hospital.The theme model and sentiment dictionary were used to extract the emotional features of the masses, the WordStream were used to visually present the trend of urban public opinion.The path planning algorithm based on hospital load capacity were built for treatment route, the population-oriented science information of access to cabin hospital and the urban recovery model can enhance anti-epidemic confidence.The system is helpful to realize the reasonable allocation of human and material resources, timely guide the emotional trend of the masses, pay attention to the change of public opinion after the release of new polices/decisions, and slow down the phenomenon of patients gathering.The function and effectiveness of the system was verified by the analysis of several cases.