Research On The Risk Assessment Of COVID-19 Infection Based On TOPSIS

The massive spread of Corona Virus Disease 2019(COVID-19)around the world has led to health systems of many countries on the verge of collapse.In order to further implement the general policy of "comprehensive clearing" of epidemic prevention and control,it is necessary to conduct research on the infection risk of COVID-19.On one hand,the infection risk assessment of COVID-19 can help lead individuals to establish correct awareness of epidemic prevention and take effective protective measures;on the other hand,it can classify epidemic risk levels for local governments.According to the level of risk,government departments conduct graded,classified prevention and control,this can restore a healthy economic order as soon as possible.The research on infection risk of COVID-19 can be divided into two parts: regional infection risk and individual infection risk.In terms of regional infection risk,the existing risk assessment method does not take into account the regional economic level,population mobility and other influencing factors,so there may be certain risk deviations.In terms of personal infection risk,existing risk assessment methods do not take into consideration the impact of vaccination and personal protective equipment on personal infectious risk.For the above problems,this paper used the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)method to research the regional infection risk and individual infection risk of COVID-19.The main research contents of this paper are as follows:(1)By introducing the immune population and the dead population into the traditional SEIR(Susceptible-Exposed-Infected-Recovered)model,propose a SVEIRD(Susceptible-Vaccinated-Exposed-Infected-RecoveredDead)model taking into account vaccines and non-drug interventions,and use this new model to calculate infectious indicators such as symptomatic infection rate,asymptomatic infection rate,case fatality rate,cure rate and incubation period and so on.(2)In view of the unreasonableness of the existing interval entropy weight method,an improved interval entropy weight method is proposed,which will be applied to calculate the weight of COVID-19 regional infection risk factors.(3)By taking into consideration regional infection risk factors in four aspects: infection index,economic level,health level and population,establish a TOPSIS regional infection risk assessment model considering risk preference,and calculate the infection risk index of each region by means of this new model.(4)According to the personal infection risk data of vaccination status,regional epidemic risk level,14-day travel history and personal protective equipment,establish a TOPSIS personal infection risk assessment model considering the correlation of risk factors,and verify the validity of the new model by comparing the results of model assessment with individual infection profiles.Through the research of the above,it is found that vaccination and nondrug intervention have inhibited the spread of the epidemic,and they are both reasonable and effective epidemic prevention measures.In addition,there will be some differences in the risk of infection in the new coronary pneumonia region under different risk preferences,and an appropriate risk attitude should be adopted for risk assessment.