Global analysis of the COVID‐19 policy activity levels and evolution patterns: A cross‐sectional study

Abstract

AbstractBackground and AimsSince the beginning of the coronavirus disease 2019 (COVID‐19), a large number of government policies have been implemented worldwide in response to the global spread of COVID‐19. This paper aims at developing a data‐driven analysis to answer the three research questions: (a) Compared to the pandemic development, are the global government COVID‐19 policies sufficiently active? (b) What are the differences and characteristics in the policy activity levels at the country level? (c) What types of COVID‐19 policy patterns are forming?MethodsUsing the Oxford COVID‐19 Government Response Tracker data set, we present a global analysis of the COVID‐19 policy activity levels and evolution patterns from January 1, 2020 to June 30, 2022, based on the differential expression‐sliding window analysis (DE‐SWAN) algorithm and the clustering ensemble algorithm.ResultsWithin the period under study, the results indicate that (a) the global government policy responses to COVID‐19 are very active, and the policy activity levels are significantly higher than those of global pandemic developments; (b) a high activity of policy is positively correlated to pandemic prevention at the country level; and (c) a high human development index (HDI) score is negatively correlated to the country policy activity level. Furthermore, we propose to categorize the global policy evolution patterns into three categories: (i) Mainstream (152 countries); (ii) China; and (iii) Others (34 countries).ConclusionThis work is one of the few studies that quantitatively explores the evolutionary characteristics of global government policies on COVID‐19, and our results provide some new perspectives on global policy activity levels and evolution patterns.