The Drivers of Policies to Limit the Spread of COVID-19 in Europe

Abstract

While many articles have analyzed the effectiveness of the policies that aimed to limit the spread of COVID-19, very little research work has examined the determinants that drove these policies. Therefore, we proposed to study the determinants that led government authorities to implement more or less restrictive policies to limit the spread of the pandemic. Using the COVID-19 stringency index, we highlighted a positive effect of the incidence rate on the stringency level. Patient capacity in intensive care units was also a key variable. This is indicative of the capacity of countries to have a sufficient and appropriate health system to absorb such pandemic crises. On the other hand, we show that epidemiological data regarding the risk of excess mortality (diabetes, cancer, and cardiovascular pathologies) had a negative effect. We conclude by recalling the importance of policy coordination between countries when it comes to lowering the stringency levels of measures, in order to avoid a resurgence of the epidemic.

The Advantages of the Zero-COVID-19 Strategy

“…It is also important to note that the adoption of the zero-COVID-19 strategy is not a guarantee for sustained pandemic control success. Many factors could shape the formation and impacts of pandemic control policies [ 58 , 96 , 97 , 98 ]. For instance, in addition to the makeup and structure of anti-pandemic measures, differences in policy administration and prioritization of public health may also explain why there are variations in zero-COVID-19 countries’ pandemic performances [ 76 ].…”

Effects of the COVID-19 lockdown and recovery on People's mobility and air quality in the United Arab Emirates using satellite and ground observations

“…The SI was used in this study as a proxy to assess the degree of the strictness of UAE government lockdown measures. SI is an overall composite score derived on the basis of nine response indicators that entail the closure of schools, workplaces, cancellation of public events, restrictions on gatherings, closure of public transportation, stay-at-home orders, restrictions on internal movements, international travel restrictions, and public information campaign ( Bourdin et al, 2022 ; Chan et al, 2021 ; Liang et al, 2021 ; Piquero and Kurland, 2021 ). Daily SI was obtained and converted into weekly averages.…”

COVID-19 and the Mortgage Market in Luxembourg

“…The design of optimal policies has been studied by Janiak et al (2021) in a Susceptible, Infectious, or Recovered (SIR) model. On the empirical front, Bourdin et al (2022) study the drivers of the restrictiveness of health measures to tackle COVID-19. They argue that the number of patients in intensive care units is a key driver of the stringency of health measures, further highlighting the necessity of these measures to contain the virus despite their economic costs.…”