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Prof Norman Fenton Profile picture
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16 Apr, 4 tweets, 1 min read
1. Remember the May 2020 headline story "Black people are 4 times more likely to die from Covid-19"? Our article on why these death risk statistics were misleading has been published today in the Royal Statistical Society's Significance Magazine
significancemagazine.com/701
2. The full back story describing the role of the Office for National Statistics is here: probabilityandlaw.blogspot.com/2021/04/revisi…
3. What is clear is that the original figures, which were so widely seized on by the media, were exaggerated - as we originally said. And even the current figures are also likely to be exaggerated by failure to account for demographic changes since the 2011 census.
4. Yet it is the figures in the original report that remain in the popular narrative and which have created an unjustified level of fear and anxiety among the Black community.

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More from @profnfenton

Prof Norman Fenton Profile picture
16 Apr
1. Note the crucial difference in wording between eye-catching graphic which says "1 in 480 ...with COVID-19" and the simple text which says "1 in 480 ...tested positive for COVID-19". The graphic is the one which is the lie.
2. The most important lesson from our work analysing the Cambridge data is that, with a false positive rate of around 0.35% for asymptomatics, most asymptomatics who test positive do NOT have COVID-19.
3. In the period we looked at there were 43 positives from the pooled PCR testing, of which 36 were found to be false positives after a confirmatory tests.
Read 6 tweets
Prof Norman Fenton Profile picture
12 Apr
1. This is a thread about the barriers to academic publication for work that challenges the ‘official narrative’ on Covid-19 such as our work challenging the 'official' data about asymptomatics.
2. Our paper about the “1 in 3 people with Covid-19 have no symptoms” claim has already had 4093 reads since posted on researchgate on Friday, and 337,255 impressions to the tweet about it. The video summary has been watched by 7,530 people in 2 days. doi.org/10.13140/RG.2.…
3. But, this was the response we got less than 24 hours after we submitted it to the BMJ:
Read 11 tweets
Prof Norman Fenton Profile picture
9 Apr
1. This 6 minute video summarises the findings in our new report exposing the "1 in 3 people with Covid-19 have no symptoms" claim:
2. The full report is here:
doi.org/10.13140/RG.2.…
3. And here is a blog post containing a summary of the report: probabilityandlaw.blogspot.com/2021/04/smashi…
Read 7 tweets
Prof Norman Fenton Profile picture
23 Mar
1. Here is an up-to-date table of results from the Cambridge University #Covid19UK study of asymptomatics since the start of 2021
2. Some key points about it:
3. The explanation of why this means the much repeated Government claim that “1 in 3 people with the virus has no symptoms” is a massive exaggeration was provided in this previous analysis of the Cambridge study: probabilityandlaw.blogspot.com/2021/02/the-ca…
Read 6 tweets
Prof Norman Fenton Profile picture
14 Mar
1. This article nicely explains why (because of possible false positives) a positive LFT test result does NOT mean you certainly have Covid. However, it's focus on false negatives (implying we should also be wary of a negative result) is misleading. theguardian.com/theobserver/co…
2. In fact, with the assumptions used in the article and the current results of the Cambridge University study of asymptomatics, it follows that there's ony a 1 in 10,000 chance a person testing negative with LFT will have the virus
3. The results suggest we should NOT be mass testing asymptomatic people. The lastest Cambridge asymptomatic study results are here: cam.ac.uk/sites/www.cam.…
Read 6 tweets
Prof Norman Fenton Profile picture
28 Feb
1. As I pointed out yesterday with this graphic (now updated) the Cambridge study data shows that since December only a miniscule percentage of people without COVID-like symptoms have the virus. But it also exposes massive contradications in the official Government data.
2. First it demonstrates (for one UK city) that the much publicised claim that "1 in 3 people with the virus has no symptoms" cannot be correct if the ONS estimated infection rate is correct. Here's an informal explanation (formal proof follows later in thread)
3. In fact, if the "1 in 3" claim is correct then the ONS estimated infection rate is massively inflated - the currently reported ‘case’ numbers must be at least 8 times greater than the true number of cases.
Read 16 tweets

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