The management of crises, when based on data, relies on correlations that underly rules which, in turn, are translated into actions or regulations. If, for example, there were a strong correlation between driving speed and number of traffic accidents, this would lead to a rather obvious rule that “driving fast increases the risk of accidents”, hence the authorities would lower the maximum speed limit. This is indeed one reason why there are speed limits.
Something similar is taking place nowadays, when Covid-19-related data is used to trigger lockdowns, limit personal freedoms, reshape the global economy (to use a euphemism). Here too, correlations extracted from data are used for the purpose of supporting the said policies, or simply transmitting information to the public. In the majority of cases, linear (Pearson) correlations are used.
A recent study by John Hopkins University speaks of correlation between the number of covid-19 deaths and percentage…
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