a French paradox?

There has been some debate (in France at least) as to why the country was one with the highest rate of infection (among West European countries), still rising [with half a million new cases reached on 25 Jan., almost 1% of the entire population].However, the increase in the number of ICU admissions has been much less dire, with hospitals still operating below maximum capacity (although in tense conditions) and a stable death rate (in the entire population) below the US and the UK rates [and therefore a decreasing fatality rate].While arguments on a much higher testing rate have been discarded, other explanations for the elevated levels of contamination include the general slackness in enforcing and respecting distanciation and protection rules, as shown below by the more limited decrease in commuting (although there are many confounding factors), and the high contamination rate among young (and not yet vaccinated) children and their unrestricted access to schools…While the vaccination rate is rather high (at 93% of people above 12 being vaccinated to some extent), it could explain for the lower fatality rate and hence for the country being one of the best achievers in terms of excess mortality.

insanity at its height

capture-recapture homeless deaths

In the newspaper I grabbed in the corridor to my plane today (flying to Bristol to attend the SuSTaIn image processing workshop on “High-dimensional Stochastic Simulation and Optimisation in Image Processing” where I was kindly invited and most readily accepted the invitation), I found a two-page entry on estimating the number of homeless deaths using capture-recapture. Besides the sheer concern about the very high mortality rate among homeless persons (expected lifetime, 48 years; around 7000 deaths in France between 2008 and 2010) and the dreadful realisation that there are an increasing number of kids dying in the streets, I was obviously interested in this use of capture-recapture methods as I had briefly interacted with researchers from INED working on estimating the number of (living) homeless persons about 15 years ago. Glancing at the original paper once I had landed, there was alas no methodological innovation in the approach, which was based on the simplest maximum likelihood estimate. I wonder whether or not more advanced models and [Bayesian] methods of inference could [or should] be used on such data. Like introducing covariates in the process. For instance, when conditioning the probability of (cross-)detection on the cause of death.