I could use a bit more of an explanation of how certain countries could have consistently higher excess deaths than others. Is the chart measuring against a European average, or do more and more people keep dying in Spain each year, or what?
You’re forgetting one possible reason that Seatlle or SF did substantially better than New York. Perhaps the virus was circulating freely among the population In winter 2019.
"Although we fully support the ambition of Flaxman et al.1—to estimate the effectiveness of different NPIs from the available data—we find the underlying modelling approach problematic. Flexible parameterization leads to issues with identifiability, which are masked by model assumptions. In particular, we find it questionable to designate a country-specific effectiveness parameter to the last NPI that was introduced in each country. Besides the problems illustrated in Fig. 2, with large variations in the estimated effectiveness of NPIs, this prohibits prospective use of the model, as it is unknown at any given time whether the latest NPI will also be the last to be implemented in a particular country.
We conclude that the model1,3 is in effect too flexible, and therefore allows the data to be explained in various ways. This has led the authors to go beyond the data in reporting that particular interventions are especially effective. This kind of error—mistaking assumptions for conclusions—is easy to make, and not especially easy to catch, in Bayesian analysis. As NPIs are revoked, and possibly reintroduced over an extended period of time, more data will become available and practical identifiability of the separate effects of NPIs may be obtained. Until then, we suggest that the model1,3, and its conclusion that all NPIs apart from lockdown have been of low effectiveness, should be treated with caution with regard to policy-making decisions."
I could use a bit more of an explanation of how certain countries could have consistently higher excess deaths than others. Is the chart measuring against a European average, or do more and more people keep dying in Spain each year, or what?
You’re forgetting one possible reason that Seatlle or SF did substantially better than New York. Perhaps the virus was circulating freely among the population In winter 2019.
It'd be interesting to use Lemoine's updated model to model U.S. states; might have to learn R.
This article in Nature also discussed some of the issues with Flaxman, et al: https://www.nature.com/articles/s41586-020-3025-y
"Although we fully support the ambition of Flaxman et al.1—to estimate the effectiveness of different NPIs from the available data—we find the underlying modelling approach problematic. Flexible parameterization leads to issues with identifiability, which are masked by model assumptions. In particular, we find it questionable to designate a country-specific effectiveness parameter to the last NPI that was introduced in each country. Besides the problems illustrated in Fig. 2, with large variations in the estimated effectiveness of NPIs, this prohibits prospective use of the model, as it is unknown at any given time whether the latest NPI will also be the last to be implemented in a particular country.
We conclude that the model1,3 is in effect too flexible, and therefore allows the data to be explained in various ways. This has led the authors to go beyond the data in reporting that particular interventions are especially effective. This kind of error—mistaking assumptions for conclusions—is easy to make, and not especially easy to catch, in Bayesian analysis. As NPIs are revoked, and possibly reintroduced over an extended period of time, more data will become available and practical identifiability of the separate effects of NPIs may be obtained. Until then, we suggest that the model1,3, and its conclusion that all NPIs apart from lockdown have been of low effectiveness, should be treated with caution with regard to policy-making decisions."