COVID-19 Deaths Linked to Restrictions Stringency Lag: A G7 and Global Analysis, Implications for Public Policy

  • Marcella Lucchetta, Department of Economics, University Ca’ Foscari, Venice, Italy
  • Lois Tullo, Schulich School of Business, York University, Toronto, Canada; Executive in Residence, Global Risk Institute, Toronto, Canada
Computer generated image of coronavirus.

Executive Summary

By Lois Tullo

The Delta plus and Lambda variants increased transmissibility and breakthrough cases has highlighting potential vaccine resistance. This increases the urgency for policymakers to understand and immediately enforce regulations through reducing the stringency lag of their policies. This recommendation is supported by restriction stringency lag research focused on the G7 countries, with data from 184 countries that confirmed that after an increase in restrictions, there was an increase in new COVID-19 deaths.

COVID-19 cases and deaths have started to climb in Canada and globally due to the Delta Variant. Governments are again having to
re-examine the need for implementing restrictions including face covering, indoor gatherings, business, and school reopening, etc.

Public policy can be informed from the research results of the G7 countries, from the analysis of daily data from 184 countries of the world during the COVID-19 epidemic. To understand the influences on number of deaths by country, the analysis reveals that per capita income was significantly positively correlated with mortality from COVID-19. This suggests that the epidemic first hit rich countries the hardest through the correlation to the human development index. This finding was contrary to what was predicted by the Global Health Security Index on pre-pandemic preparedness. Within affluent countries, deaths and cases were higher among socio-economic challenged populations. This was supported by the number of deaths that are positively influenced by the GINI index that is an indicator of disparity of income and wealth.

The research indicates that after an increase in restrictions, there is an increase in new COVID-19 deaths and cases. This along with the finding on the stringency index, correlated with the stringency lag, point to the effectiveness of policies being negatively correlated due to a lag in implementation and partial application. Moreover, the uncertainty or the variability of the stringency index has a negative impact on mortality.

The “Power Distance” by was used to understand individual’s reaction to restrictions indicated by the stringency index and the stringency lag, COVID-19 death numbers were also found to be positively influenced by a countries’ “Power Distance”. These findings are key to improve policy management of the virus.