Aside from the dismal coding, was it robust? Models based on assumptions in the absence of data can be over-speculative and open to over-interpretation. Professor John Ioannidis of Stanford University issued a strong warning9 to disease modellers to recognise the severe deficiencies in reliable data about Covid-19, including assumptions about its transmission and its essentially unknown fatality rates. For instance, the model assumed no existing immunity to Covid. Since then, six studies have shown T-cell reactivity (which gives protection) from previous coronaviruses in 20% to 50% of people
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