Factors Influencing the Trajectory of COVID-19 Evolution: A Longitudinal Study of 12 Asian Countries

BackgroundThe effectiveness of different strategies in addressing the COVID-19 pandemic has been assessed, but there is still not enough evidence in Asian countries. This study aims to examine the factors influencing the trajectory of COVID-19 evolution in Asia, to provide insights for optimizing public health policies. MethodsIn this longitudinal analysis, we combined COVID-19 cases and vaccination percentages from Our Word in Data with the policy stringency index from the Oxford COVID-19 Government Response Tracker for 12 Asian countries between January 1, 2021, and September 30, 2022. An agglomerative hierarchical cluster analysis (HCA) was conducted to identify countries with similar COVID-19 evolution trajectories. We also investigated the potential impact of seasonal variations on the virus trajectory. The relationship between the level of policy response, vaccination coverage, and COVID-19 cases was explored using Generalized Additive Models (GAMs). FindingsThere were noticeable differences in the evolution trajectory of COVID-19 among the countries. The 12 Asian countries were grouped into two clusters based on evolutionary similarities. Cluster 1 consisted of West Asian countries (Azerbaijan, Turkey, Bahrain, Israel and Lebanon); while Cluster 2 included Japan, South Korea, Singapore, Malaysia, Thailand, Cambodia and Indonesia. The analysis revealed that the stringency index and vaccination coverage were associated with a statistically significant impact (both P values < 0{middle dot}0001) on the evolution trajectory of COVID-19 (adjR2=0{middle dot}54). The dose-response relationships demonstrated that the continuous high levels of stringency index ([&ge;]87{middle dot}6) or vaccination coverage ([&ge;] 42{middle dot}0%) have led to a decrease in COVID-19 infection rates. In early 2021, the adjR2 increased to 0{middle dot}93 for all countries. Furthermore, the adjR2 for Cluster 1 and Cluster 2 were 0{middle dot}86 and 0{middle dot}90 respectively. All GAMs models have significantly improved compared to null model (P values <0{middle dot}0001). InterpretationBy strengthening vaccination ahead of susceptible seasons and enhancing personal self-protection measures, the transmission of COVID-19 among the population can be reduced even during the highly infectious Omicron era. FundingSenior Talent Startup Fund of Nanchang University