A research group led by Associate Professor Genya Kobayashi of Chiba University, in collaboration with Nospare Co., Ltd., analyzes infectious disease data before and after the declaration of an emergency under the epidemic of new coronavirus infection using a statistical model.As a result, it was found that it is important to maintain the duration of self-restraint measures and to keep the infection rate at a low level, especially after the end of the epidemic, in order to control the epidemic.In addition, it was estimated that after the state of emergency, the infection rate was 40% to 50% lower than before the declaration.

 The Government of Japan issued a state of emergency on April 4 to combat new coronavirus infections.After that, the increase in the number of newly infected people settled down, but the socio-economic situation was severely damaged by requests for leave of absence and refraining from going out.Considering future measures, it is important to predict the effects of behavior change of people before and after the declaration of an emergency and the transition of the number of infected people after the declaration is lifted.

 In the study, a model called "state-space SIR model" was used and analyzed by a statistical method.For the analysis, the prediction model was verified using the data of the infection status from March 2020, 3 to April 1, two weeks after the declaration was issued, and to May 2, 4 thereafter.

 As a result, if the number of days of intervention measures is short, the infection rate may increase after a certain period of time and the number of infected people may increase again. Was shown.It was found that it is important to keep the infection rate low for a long period of time, especially after the measures are completed, in order to control the epidemic.

 In addition, the infection rate after the intervention was estimated to have decreased by about 40% to 50% due to behavioral changes of people due to measures such as refraining from going out.Furthermore, the estimated value (effective reproduction number) of the average number of infected people from one infected person considering the intervention effect is lower than the value at which the infection epidemic is considered to converge, and behavioral changes due to refraining from going out under an emergency declaration etc. Was presumed to have had a certain effect.

Paper information:[BioScience Trends] Predicting intervention effect for COVID-19 in Japan: state space modeling approach

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