If it's raining outside but modelling tells you it's sunny, do you believe what you can see and the clear data? Triangulation of modelling, observational data, & common sense is vital. More complex doesn't mean more accurate. bmj.com/content/369/bm…
If you have very few people testing positive, positivity is <0.5%, genetic sequencing shows that 1st strains were eliminated, what does this tell you about level of COVID? Or believe complex, untransparent mathematical models w/ predetermined assumptions? heraldscotland.com/news/18931916.…
Some modellers also saying last Jan 2020 that 80% of Chinese population would get COVID-19 and this would be uncontrollable. Guess what? China controlled it. So did Taiwan, Singapore, Hong Kong, S. Korea, Australia, NZ -> the list goes on. Public health measures can and do work.
The mistake modelling made was not to account for value of TIME. Buying time for science saved thousands of lives in countries that went for 'no COVID tolerance'. Now they will vaccinate their populations & escape this pandemic with few deaths & faster economic recovery.
We must learn from this pandemic & do better next time. More humility, listening & cooperation. Honoured to be Vice-chair of new Commission on global pandemic preparedness for @theNASEM, at request of the US Dept of Health & Human Services. Follow it here: nationalacademies.org/our-work/our-w…
And final tweet -> just because someone says something with absolute confidence & arrogance, doesn't make it right. Think of our former Pres Donald Trump. Those who acknowledge uncertainty, who listen & are humble & reflective -> tend to make better scientists & leaders.
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