It was originally assumed that only those who had previously been infected by the virus and developed an antibody response had any immunity, hence the initial focus on testing for the presence of these antibodies as well as infection. However, studies of antibodies in formerly infected patients demonstrated accuracy issues which subsequently could be explained instead by the antibodies’ rapid decay in recovering patients. The often disappointingly low levels of antibodies in population samples is often used as evidence that herd immunity is not a realistic goal without a vaccine.
This is not correct.
At the end of May there was a significant breakthrough in understanding of COVID antibodies which was not widely reported: a Swiss study from Zurich led by Professor Onur Boyman demonstrated that a large proportion of the population had a natural immunity through existing antibodies on the mucous membrane (IgA) or cellular immunity (T cells), likely to have been acquired through previous exposure to coronaviruses such as influenza or the common cold (the absence of exposure to previous coronavirus is now thought to explain the opposite effect in 1918).
The study found that that the presence of (IgG and IgM) antibodies generated on infection which tests had previously focused on, were NOT in fact required to defeat the virus and that existing (IgA and T cell) antibodies that gave a natural immunity. Moreover, the population with this natural immunity was demonstrated to be five times greater than those with the IgG and IgM antibodies on which tests had hitherto focused. If this could be substantiated, then the population already exposed to COVID would also be five times greater than previously assumed. In other words, if a population sample showed 10% had IgG and IgM antibodies (which might be subject to decay) then it was likely that at least half of the population had already been exposed to COVID.
It followed that antibody studies that measured only IgG and IgM that were now predicting population-based mortality risk of 0.1% to 0.5% (lower than the 1% in the elderly population aboard the Diamond Princess) could be even further reduced by a factor of five to 0.02% to 0.1% and the level of symptomatic exposure from 20% to below 5% (consistent with the flu season ironically predicted by Fauci in March).