Effects of government policies on the spread of COVID-19 worldwide

Abstract

The outbreak of novel COVID-19 disease elicited a wide range of anti-contagion and economic policies like school closure, income support, contact tracing, and so forth, in the mitigation and suppression of the spread of the SARS-CoV-2 virus. However, a systematic evaluation of these policies has not been made. Here, 17 implemented policies from the Oxford COVID-19 Government Response Tracker dataset employed in 90 countries from December 31, 2019, to August 31, 2020, were analyzed. A Poisson regression model was applied to analyze the relationship between policies and daily confirmed cases using a generalized estimating equations approach. A lag is a fixed time displacement in time series data. With that, lagging (0, 3, 7, 10, and 14 days) was also considered during the analysis since the effects of policies implemented on a given day may affect the number of confirmed cases several days after implementation. The countries were divided into three groups depending on the number of waves of the pandemic observed in each country. Through subgroup analysis, we showed that with and without lagging, contact tracing and containment policies were significant for countries with two waves, while closing, economic, and health policies were significant for countries with three waves. Wave-specific analysis for each wave showed that significant health, economic, and containment policies varied across waves of the pandemic. Emergency investment in healthcare was consistently significant among the three groups of countries, while the Stringency index was significant among all waves of the pandemic. These findings may help in making informed decisions regarding whether, which, or when these policies should be intensified or lifted.

Impact of immobility and mobility activities on the spread of COVID‐19: Evidence from European countries

“…Stringency policies also have a negative and significant effect on the number of new cases. This confirms the findings of the extensive literature on the impact of containment and mobility restriction policies (Brauner et al, 2021 ; Chung et al, 2021 ; Fiore et al, 2021 ; Khan et al, 2021 ; Md Zamri et al, 2021 ; Pan et al, 2021 ; Violato et al, 2021 ). However, the effect of the stringency index becomes insignificant when the mobility/immobility variables are introduced, except in the case of the parks and workplace variables.…”

“…Maloney and Taskin ( 2020 ) show that the reduction in mobility in the United States is more voluntary than linked to compulsory stay‐at‐home measures. While several studies have looked at the impact of stringency measures and mobility restrictions on the evolution of the COVID‐19 pandemic (Brauner et al, 2021 ; Chung et al, 2021 ; Fiore et al, 2021 ; Herby et al, 2022 ; Khan et al, 2021 ; Md Zamri et al, 2021 ; Pan et al, 2021 ; Violato et al, 2021 ), few have focussed on analysing the direct effect of mobility practices (Milani, 2021 ; Xiong et al, 2020 ; Yilmazkuday, 2021 ).…”

Vaccination and Government Stringent Control as Effective Strategies in Preventing SARS-CoV-2 Infections: A Global Perspective

“…As a result, the prevention of COVID-19 cases is not only related to population vaccination but also depended on government control measures (e.g., public event cancellations, gathering restrictions, public transportation shut down, and quarantine requirements). As shown by the reported experience of addressing SARS-CoV-2, countries with stricter prevention and control measures are better at containing the epidemic (8)(9)(10).…”

“…Therefore, it is imperative to clarify the relationships between the vaccination, government control measures, human development index (HDI), and the incidence of COVID-19 from a global perspective. Previous studies have analyzed the relationship between COVID-19 incidence, vaccination, and government control measures (8)(9)(10)(13)(14)(15)(16)(17)(18). However, these studies mostly focused on local areas or individual countries, and there are no worldwide reports based on long-term data to examine VE and stringent measures concurrently.…”

COVID-19 lockdown introduces human mobility pattern changes for both Guangdong-Hong Kong-Macao greater bay area and the San Francisco bay area

“…Countries throughout the world enacted a series of containment strategies during the initial phase of the coronavirus disease 2019 (COVID-19) pandemic, aiming to control the spread of this disease ( Fisher and Wilder-Smith, 2020 , Sohrabi et al, 2020 , Chung et al, 2021 , Iftimie et al, 2021 ). These policies included traffic controls, self-quarantining, travel restrictions, and limitations of public activities such as closures of schools and businesses as well as suspended operations of industries or largely reduced production ( Grépin et al, 2021 , Gwee et al, 2021 ).…”