So the test correction based on FINDDx increases the Gangelt IFR by ~4, and/or renders Gangelt less relevant since corrected seroprevalence overlaps with 0%.
There are other cases in which using FINDDx decreases IFR. For example:
Based on the above paper's FINDDx-based analysis, some of the worse offenders in terms of sensitivity (i.e. false negatives) at particular times post-infection are:
Sweden did not lockdown in response to COVID-19. Many politically-motivated COVID-19 contrarians try to support Sweden's policy by making misleading comparisons between Sweden + other countries. This thread will address that.
A lot of COVID-19 contrarians abuse the idea of "cross-reactivity" to make SARS-CoV-2 (the virus that causes COVID-19) look less dangerous than it really is. Many of them do this to avoid policies they dislike, like lockdowns.
Immune cells known as T cells and B cells have receptors that recognize viruses.
Think of the receptors as a lock, + portions of the virus as a key; i.e. the lock (receptor) binds to a specific key (virus region), + not to other keys
Even if you've never been infected with a virus, bacteria, etc., you almost certainly have T + B cells that recognize it.
When you're first infected, those cells (especially B cells) take a few days to increase in number (and activity) + generate their full immune response.
Interesting method from @GidMK and co-authors for calculating IFR from PCR-based cases.
(IFR is the proportion of SARS-CoV-2-infected people who die COVID-19;
PCR measures viral genetic material in people;
Cases are people who were infected)
The basic idea is that some countries had relatively few infected, and tested with PCR so thoroughly, that their PCR testing got a relatively large proportion of infected people.
Their method yields a range of IFR values consistent with those from serology [i.e. antibody testing], which provides independent validation for their method.
green: their PCR-based methods
blue: Serology-based estimates