Covid-19

The way the government’s coronavirus dashboard tells it, we can hardly move for covid lateral flow tests. Back of the envelope sums suggest there are now ‘only’ 600,000 plus daily LF tests, down from a peak of around a million daily tests in mid March. It’s a wonder we aren’t awash with grimy discarded test kits, jetsam from the ghost ship the New Normal. In Australia, where they take these things very seriously, the jetsam could have been far worse. A few months back, a zeroid (an endemic-covid denialist who believes instead in zero-covid, whatever it takes, and whatever it means) suggested that adding anal swabs for kids — zeroids believe kids and schools are hotbeds of infection and transmission — might pick up the covid that other tests can’t reach. What could possibly go wrong?

It is a truth universally acknowledged that a pharmaceutical company in want of a profit will use relative risk. It will do this because presenting the results of clinical trials as relative risk reductions tends to make their new wonder drug appear dramatically effective. But relative risk reduction is only one way of presenting the data. We can also look at the absolute risk reduction, and a useful number derived from the absolute risk reduction, the number needed to treat. This tells us the number of people we need to treat to prevent one adverse outcome. As we shall see, absolute risk reductions and numbers needed to treat tend to dramatically lower the apparent, and so perceived, benefits of treatment. These observations, we shall further see, can be applied to all treatments, including covid vaccines.

Has the novel vaccine for a novel coronavirus led to a novel case of hiding something bad in plain sight? We are constantly told by the authorities and mainstream media that the novel coronavirus vaccines are exceptionally effective and safe. Yet at the same time there is a constant drip feed, now running more like a torrent, of reports of numerous and sometimes serious side effects from the vaccines. Dan Astin-Gregory of the Pandemic Podcast recently received, but failed to publish, a “113 page report documenting the tragic accounts of people who had sadly died following the COVID-19 vaccination”. Mr Astin-Gregory’s heart is clearly in the right place, but the mind needs data. An anecdote of anecdotes? Without seeing the report, it is impossible to make any assessment of it.

The Covid Inquisition has had a rather hard time of it lately. As UK test positives, hospitalisations and deaths have plummeted, they have had in recent weeks to rely on scariants and foreign outbreaks in Brazil and India to maintain fear levels, but over the last few days a game changer has emerged: the virus is airborne. WHO have marginally up-rated their assessment of risk from aerosol transmission, triggering a raft of tweets from the Inquisition saying we told you so, but the real bombshell is a pre-print that puts some E notation numbers and extra computer generated colours on the Milk Curdler’s earlier three colour crayon box model #CovidRiskChart. The Inquisition now know that H, or your airborne infection risk parameter, for a brief, silent masked outdoor encounter is 2.33E-05. Prolonged shouting without masks in a poorly ventilated crowded room, on the other hand, pushes your H up to 1.00E+02. If shout turns to shove, your H jumps even higher, to 2.33E+02. Cripes.

What’s in a baseline? We now have all cause mortality data for the first quarter of 2021 for England and Wales, and so it is time to add this data to one of the many charts Dr No has squirreled away in his covid dossiers. This chart shows quarterly standardised mortality ratios (SMRs) from Q1 2000 to Q1 2021, the last two decades. They are calculated using the indirect method, using all 2000 mortality data as the standard. Each point represents that quarter’s SMR compared to all 2000 all cause mortality, adjusted for population size and age distribution, with values above 100 meaning observed mortality was higher than expected using the 2000 baseline, and values below 100 meaning it was less than expected. Quarters 1 to 4 are identified by the colours shown in the key. What do we see?

Early on in the pandemic, Dr No coined the phrase hot stiff bias to describe the habit of doctors of the covid tendency to attribute any death that might, however vaguely,  be due to covid, as being definitely due to covid. It is a covid specific form of the more general hot stuff bias, in which doctors tend to attribute illness and deaths to ‘hot’ diseases, the ones that are currently ‘hot’ topics. It is a practical expression of there’s a lot of it about, the old medical standby for when one doesn’t have a clue, but wants to sound as if one does. An easy concept to understand, hot stiff bias is typically hard to quantify, but the latest ONS data does gives us a clue. It seems that as the weather warms up, covid hot stiff bias cools off.

Isn’t it curious how describing deaths brought forward by a short interval by covid as dry tinder garners disapproval, while the MHRA’s breezy description of Yellow Card deaths associated with covid vaccination as spontaneous combustion — most likely would have died anyway, dear boy — goes quite un-remarked. Be that as it may, Dr No has taken a look at the MHRA’s Yellow Card Scheme for reporting adverse drug reactions, after some discussion in a recent post about a BMJ Rapid Response which suggested significant underreporting of covid vaccination side-effects. What can the Yellow Card Scheme tell us about adverse reactions to the covid vaccines? Is there any evidence for or against significant under-reporting of adverse reactions?