The ratio of positive deaths in England is almost three times lower than in Italy. But there are reasons to explain this paradox.
Invited to a national news program, I had to deal with a new discovery – the so-called “English paradox”, also reported in national newspapers. For example, La Stampa wrote: “The United Kingdom has seven times the number of infections of Italy but proportionately fewer deaths. Compared to the United Kingdom, Italy has 200 percent more Covid victims than positive people.” . three times as much”. Now I don’t want to go back and repeat the same thing over and over, but unfortunately I am forced to. Let’s talk about a bias, the sample bias.
Notably, the deaths in both countries are compared to those who are positive for the virus. We must therefore first ask ourselves whether the positive subjects, in England and Italy, have comparable populations, so as to avoid placing two non-estimable quantities as the denominator of the relationship between deaths and positives.
How are positive subjects identified in Italy and England? Certainly through testing for the virus. But the number of people to be tested, and hence who are identified as positivity, depend on the strategy with which these tests are carried out. First, we can see how many more tests are conducted per resident in England than in Italy: for example, on 15 December, the United Kingdom conducted about 1,636,000 tests, while Italy conducted about 635,000 tests on the same day Were. ,
The British population, ie, is much more tested than the Italian; As we know, this means that there will be many more positive results in that country – if we imagine a linear ratio, about three times more. These plus, of course, since the two populations are about the same size, there will be predominantly poissymptotic or asymptomatic subjects, who will not die except in very rare and rare cases.
As it happens, the ratio between reported deaths and positives in the famous “paradox” in England is almost three times less than in Italy; Now, for what we have said, it is quite possible that this is simply due to the fact that two thirds of the positive, asymptotic or posisymtomatic are missing in the Italian denominator and are not intercepted.
I do not claim that this is an explanation of what is observed, but I only point out that the bias due to different sampling strategies in the two countries is only one of thousands of confounding factors that are not taken into account, So any gross analysis is only misleading to the extent that it is useless. For example, there are other considerations relating to different age distributions in populations – with an average of 40.5 years in the United Kingdom and 47.3 in Italy – that are equally important factors for evaluating and correcting similar analyses. , before pronouncing.
Trying instead to say that the United Kingdom would have done better than Italy, because with less restrictive measures it would have achieved a lower fatality, based not only on the analysis we presented for the reasons we mentioned, but above all , if yes if he wants to discuss the effectiveness of the measures and cut down on unfairness, then we should not look at the lethality of the virus, but the mortality rate. Despite the quoted figures of the older population, we had the same English mortality in the end – about 2.2 per thousand inhabitants, despite the fact that we started vaccination much later, despite the fact that the virus came to our country earlier. Instead, as one would expect, a worse one.
Let’s stop looking at the contradictions about poorly chosen samples, the contradictions were then used to reinforce ideas that were not far from the infamous Great Barrington Declaration, from time to time in English, Swedish, Japanese or other data. I looked badly. Of course, many measures will need to be revised and re-examined as data becomes available; Certainly some choices would be excessive, unnecessary, or conversely too weak; But the scale of decision-making goes far beyond the crude relationship between deaths and positives for infections.
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