By Enza Ferreri

Historical phenomena of a large scale, including medical ones like epidemics and pandemics, take time to be understood; we’ll probably unravel the “Covid-19 pandemic” event when it is over (soon, I hope).

About lockdowns, we now know a few things.

Whereas the mainstream mass media tend to publish stories that sell, among which those that create alarm are predominant, some medical, scientific and other academic journals have been publishing peer-reviewed research which not always has reached the general public.

Let’s take “The illusory effects of non-pharmaceutical interventions on COVID-19 in Europe” , an article by Stefan Homburg and Christof Kuhbandne published in Frontiers of Medicine in answer to an essay by Flaxman et al in the scientific journal Nature which was claiming that non-pharmaceutical interventions imposed by 11 European countries saved millions of lives. Non-Pharmaceutical Interventions (NPI) is the technical name for lockdowns, and the paper refers to the original 2020 lockdowns.

Homburg and Kuhbandne explain the well-known phenomenon that the time-varying reproduction number R(t), where t denotes time, and representing the expected number of infections generated by one infected individual, tends to spontaneously decrease over time, ceteris paribus (all things being equal). This happens because the number of individuals vulnerable to the infection but not yet infected decreases as the virus spreads.

The authors accuse Flaxman’s paper of circularity in its argument, by artificially assuming that reproduction number R(t) remained constant, in the example case of the UK, before 14 March and after 23 March, the date the lockdown was first introduced.

It is generally thought that, in statistically numeric terms, deaths are more reliable than cases, so that by looking at the death data we can gauge the trend of the reproduction number R(t).

The authors conclude:

Considering a total delay of 23 days between infection and death, possible effects of the
23 March lockdown should only become visible in the data around April 15. However, the series does not show the slightest break in mid-April. Hitherto, the growth factor had already declined from 1.54 to 0.97, and thereafter it continued its slowdown. Contrary to the findings of Flaxman et al., Fig. 2 strongly suggests that the UK lockdown was both superfluous (it did not prevent an otherwise explosive behavior of the spread of the coronavirus) and ineffective (it did not slow down the death growth rate visibly).

The argument of a delay of 23 days between infection and death can also be used in the opposite direction. With the growth rate of daily corona deaths falling since mid March, the underlying growth rate of daily infections must have started receding in the second half of February, long before the problem was recognized and any measures were taken. The continuous decrease in the growth factor shown in Fig. 2, even at dates before any NPI could have become effective, corroborates the theoretical insight that R(t) falls automatically over time. We have checked that the growth factors in the remaining 10 countries considered by Flaxman et al. show a similar pattern.

Our final remark regards Sweden, the only country in the dataset that refrained from strong measures, but has lower corona deaths per capita than Belgium, Italy, Spain, or the United Kingdom. In the absence of a lockdown, but with an effective reproduction number that declined in the usual fashion, Flaxman et al. (Extended Data Fig. 1) attribute the sudden decline in Sweden’s R(t) on March 27 almost entirely to banning of public events, i.e., to a NPI that they found ineffective in all other countries. This inconsistency underlines our contention that the results of Flaxman et al. are artefacts of an inappropriate model.[Emphasis mine]

Further evidence comes from more recent studies, which we’ll see in the II Part of this article.