ABSTRACT
The wide-ranging evidence accumulated in this book contests the value of comparisons based on a single dimension of the pandemic in a small number of EU member states, or with other countries in the world, if the statistics fail to take account of context. By drawing together the contextual dimensions examined in each of the preceding chapters, this chapter identifies overlapping clusters of countries that share comparable input variables – socio-demographic and epidemiological risk factors and policy settings – with a view to uncovering similarities and differences in outcomes as measured by COVID-19 cases and deaths. Granular analysis captures the great diversity of possible explanatory factors concealed within any single set of statistics or within clusters of countries. It shows that many of the factors considered to explain outcomes in specific spatial and temporal circumstances do not necessarily have the same explanatory value elsewhere. The implication is that certain policy interventions would not readily be transferable to different policy settings, at international, national or local levels, without contextually informed adaptations.
