The statistics published Monday, October 19 by Public Health France, extracted from its Monic computer system (MONitorage des Clusters) for monitoring and forecasting the risks of epidemic outbreaks set up at the end of containment, is surprising.
Since May 9, 4,365 sources of contamination (clusters) in Covid-19 were identified, for a total of 50,550 reported cases. At the same time, 630,820 infections were diagnosed through screening. Less than 10% of known infections therefore come from clusters.
This surprising figure explains in particular the differences of appreciation between, at random, the government and the teachers’ unions. In the clusters under investigation, schools and universities (376) come first ahead of nursing homes (304), businesses (248), health establishments (130) and private or public events (89). But the real hierarchy of contaminations is undoubtedly very different.
Individual ultramajoritary contaminations
The weak involvement of the clusters identified means above all that only a small part of them is identified, and that investigative capacities are exceeded in sectors where the circulation of the virus is overactive. Is it still useful to look for new clusters, outside the communities of vulnerable people? Yes, if it helps to react quickly, which might be the case with antigen testing.
The figure above all means that the individual contaminations are ultramajoritary. And in the absence of adherence to tracing systems (we will say alert), identifying the precise dynamics and quantifying these modes of contamination is not easy. What can justify the large format umbrella measures curfew type.
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