efficient measures?
When checking the infographics of the week highlighted by Nature, I came across this comparison of France and Germany for the impact of their respective vaccination mandates on health and economics. And then realised this was from a preprint from a Paris Dauphine colleague, Miquel Oliu-Barton (and co-authors). The above graphs compare the impact of governmental measures towards vaccination, short of compulsory vaccination (unfortunately). Between Germany and France, it appears as if the measures were more effective in the latter. Which may be interpreted as either a consequence of the measures being more coercive in [unruly] France or an illustration of the higher discipline of the German society [despite the government contemplating compulsory vaccination for a while]. As an aside, I am very surprised at the higher death rate in Germany but, beside a larger percentage of people over 65 there and a lower life expectancy, the French curve is interrupted in December 2021. Looking at 2022, the peak was reached at 3.3 cases per day per million people.
Concerning the red counterfactual curves, I did not find much explanation in the preprint, apart from
“Our results are supported by the well-established econometric method of synthetic control.³⁰ We construct counterfactuals for each treated country based on a weighted average of countries that did not implement the COVID certificate and find consistent trajectories for the time period where this method is feasible, i.e., until the end of September 2021.”
and
“constructing counterfactuals ( i.e., by modelling vaccine uptake without this intervention), using innovation diffusion theory.⁶Innovation diffusion theory was introduced to model how new ideas and technologies spread”
which is not particularly helpful without further reading.
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