Effect evaluation of non-pharmaceutical interventions taken in China to contain the COVID-19 epidemic based on the susceptible-exposed-infected-recovered model

This paper takes confirmed cases of COVID-19 from January 20 to March 18, 2020 as the sample set to establish the susceptible-exposed-infected-recovered (SEIR) model. By evaluating effects of different non-pharmaceutical interventions (NPIs), the research expects to provide references to other countries for formulating corresponding policies. This article divides all non-pharmaceutical interventions into three types according to their different roles. The results show that type-A and type-B non-pharmaceutical interventions both can delay the timing of large-scale infections of the susceptible population, timing of the number of exposed individuals to peak, and timing of peaking of the number of infected cases, as well as decrease the peak number of exposed cases. Moreover, type-B non-pharmaceutical interventions have more significant effects on susceptible and exposed populations. Type-C non-pharmaceutical interventions for improving the recovery rate of patients are able to effectively reduce the peak number of patients, greatly decrease the slope of the curve for the number of infected cases, substantially improve the recovery rate, and lower the mortality rate; however, these non-pharmaceutical interventions do not greatly delay the timing of the number of infected cases to peak. And based on the above analysis, we proposed some suggestions.

Automated summary

This paper utilizes confirmed cases of COVID-19 from January 20 to March 18, 2020 to construct an SEIR model, evaluating the effects of different non-pharmaceutical interventions. The results show that type-A and type-B interventions can delay the timing of large-scale infections and decrease the peak number of exposed cases, with type-B interventions having more significant effects on susceptible and exposed populations. Type-C interventions focusing on improving recovery rates can effectively reduce the peak number of patients and mortality rate.