Thread by @nicolamlow

This piece on #SARSCoV2 viral load in children and adults has been highly influential.
Can you extrapolate from “Data on viral load” that “we have to caution against an unlimited re-opening of schools and kindergartens in the present situation”
I have serious concerns. 1/7

There are two issues: science and politics
On the science
1. There is no methods section about how study population was selected and who they represent
– yes, I know it is a bunch of samples tested in a virology lab - with no denominators about how many samples tested by age 2/7

2. The very low number of samples from children already says a lot about selection into the study. There is no information about their clinical characteristics, stage of infection, etc.
And unequal numbers across the groups makes them very difficult to compare, even visually 3/7

3. There is no statistical analysis section
So, weekend homework for #epitwitter #statstwitter on #pvalues and #StatisticalSignificance @StatModeling @vamrhein @jonathanasterne @nataliexdeean @epiellie @profmattfox I don't think we can conclude ‘no difference’ 4/7

4. Some issues
- statistical analysis of distributions, when there is a detection threshold
- justification for non-parametric methods, but all summarised data are means and SD and multiple pairwise comparisons of means
- an ‘overwhelming conclusion from… post hoc testing’ 5/7

On the politics
1. Experts on #COVID19 are highly trusted and their words are printed as truth, often without reflection or criticism
2. Experts have limits to their expertise
3. Going beyond the data is #BadScience
4. Bad science leads to bad decisions 6/7

So
- Extrapolation from #SARSCoV2 viral load in laboratory specimens to a public policy recommendation about school closures is not justifiable
- We need to see full methods and description to assess risks of bias
- Make raw data available for #OpenScience @c_drosten 7/7