Modeling of viral infection behavior to evaluate countermeasures against infection causing social disaster

Abstract

Infection control and protection from the emerging diseases should be rationally formulated and operated based on epidemiologically determined infection characteristics. In order to respond to this requirement, this study proposes a mathematical model of the progression of the spread of viral infection in the society. In addition, the model was applied to cases of transmission of the new coronavirus COVID-19. From the results, the following is clarified: the progress of the viral infection can be simply modeled by the daily-rate basic reproduction number r and the infection detection rate k; r is determined by the epidemiologically determined values of basic reproduction number R_o and the infection lifetime T of virus; the daily-rate effective reproduction number r_eff can be defined by r_eff = r(1 – k), and r_eff < 1 indicates that the infection is suppressed; the infection suppression can be realized to make k greater than the critical value k_cr corresponding to the epidemiological parameters; this model fits well with the practical infection behavior of COVID-19 and enables the quantitative evaluation of infection suppress measures; In the case of China, thorough detecting and isolation would have improved the infection condition to the suppression phase after only 10 days.