バイオケミカルシステム理論に基づく日本での新型コロナウィルス感染症の経路解析

抄録

A network system of new coronavirus infection disease (COVID-19) is characterized using Biochemical systems theory (BST). A differential equation model is constructed in the framework of BST and the parameter values in the equations are determined from the infection data reported for the infected, recovered, and dead individuals (from January 15 to April 29, 2020) in Japan. Nondimensional analysis suggests that the time courses of dependent variables related to the infection are governed by two dimensionless parameters: G (the ratio of rate constants) and x₂₀ (the initial value for the ratio of infected individual number and population), and G must be greater than unity in order to certainly decrease the infected individual number to zero. The infection data in the initial stage indicates that if there was no action to protect, the infected individual number exponentially increased because G=0.0839143 < 1; for 120 million of the population in Japan, almost all persons were infected and the dead individual number increased to 16.8 million. Actually, however, the numbers of infected and dead individuals were only 16,305 and 749, respectively, suggesting that the contact rate was significantly reduced in a very short period of time. The analysis also indicates that x₂ takes a maximum when x₁ (the ratio of uninfected individual number and population) is equal to G. When the nosocomially infected individual number is equal to 10 % of the total number of infected individuals, the infected individual number never becomes zero unless the nosocomial infection is regulated even when the community infection is kept zero; in this case, the nosocomial infection must be aggressively reduced.