The Global Dynamic Transmissibility of COVID-19 and its Influencing Factors: an Analysis of Control Measures from 176 Countries

Abstract

Abstract Objective To summarise the dynamic characteristics of COVID-19 transmissibility; To analyse and quantify the effect of control measures on controlling the transmissibility of COVID-19; To predict and compare the effectiveness of different control measures. Methods We used the basic reproduction number (R0) to measure the transmissibility of COVID-19, the transmissibility of COVID-19 and control measures of 176 countries and regions from January 1, 2020 to May 14, 2022 were included in the study. The dynamic characteristics of COVID-19 transmissibility were summaried through descriptive research and a Dynamic Bayesian Network (DBN) model was constructed to quantify the effect of control measures on controlling the transmissibility of COVID-19. Results The results show that the spatial transmissibility of COVID-19 is high in Asia, Europe and Africa, the temporal transmissibility of COVID-19 rises with the epidemic of Beta and Omicron strains. Dynamic Bayesian Network (DBN) model shows that the transmissibility of COVID-19 is negatively correlated with control measures: Restricting population mobility has the strongest effect, Nucleic Acid Testing (NAT) has a strong effect, and vaccination has the weakest effect. Conclusion Strict control measures are essential for the control of COVID-19 outbreak; Restricting population mobility and Nucleic Acid Testing have significant impacts on the control of the COVID-19 transmissibility, while vaccination has no significant impact. The development of future control measures may be the large-scale application of new nucleic acid testing technology and the mass popularization of booster immunization.