A Head Full of Coronavirus Research, Part 30

Another study on T cell response to CV-19.  (Nature Article)   The authors studied both 116 CV-19 patients and 104 unexposed individuals to identify the regions of the virus that were identified by T cells and any level of cross-reactive response.  While there was significant variability across individuals and across specific virus fragments,  every infected person showed a T cell response to some viral fragments, and a 80 percent of the unexposed individuals did as well.  Overall, T cell responses were stronger in CV-19 patients than in the unexposed group.   Antibody responses were also assessed, and even those few patients who appeared to have weak or non-existent antibody responses, had a T cell response.  The evidence seems fairly clear at this point that pre-existing T cell responses account for some variation in infection levels and severity.

A very interesting Wall Street Journal explores what other research I have reported on suggests, that the virus was spreading here far earlier than was initially believed.  (WSJ Article)  The most conclusive proof of this is retesting of specimens collected early this year to detect virus.  In my home state of Minnesota, for example, the research estimates that there were likely at least ten new cases a day by mid-February.  This relatively silent spread, with symptoms similar to the flu, went un-noticed for some time.

According to this study, CV-19 infection results in a robust antibody response across the spectrum of disease severity.  (Medrxiv Paper)   203 recovered patients with a range of severity were included in the analysis.  99% had strong antibody responses and 95% showed specific neutralizing activity.  In addition, over 90% had T cell adaptive immune responses as well.  The authors also observed that these CV-19 patients had strong cross-reactive responses to the common seasonal coronaviruses.  The majority of studies on the adaptive immune response are finding a strong and durable antibody and/or T cell response which bodes well for the development of population immunity.

This paper discusses age-specific infection fatality rates.  (NBER Paper)   Using seroprevalence and contact tracing data, the authors estimated numbers of infections and calculated death rates across a number of countries.  Data from about 30 prior studies was used in the analysis.   As we already know, a very steep age gradient was found in the infection fatality rate.  For people aged 0 to 34, it was .004%, for those 35 to 44 years old, .064%; while for those 75 to 84 it was 7.6% and for those over 85, 22.3%.  The researchers attempted to adjust for lags in deaths and death reporting to match deaths up to prevalence studies, but the manner in which they did this would suggest to me that they are over-estimating deaths compared to infections.   The researchers also found that about 90% of the difference in infection fatality rates across geographies is due to age variation in the population.

Another study on viral loads and testing.  (Medrxiv Paper)   The authors expressed concern that extrapolating viral load from raw PCR test cycle numbers might be misleading.  They proposed an alternative approach to adjust the results.  If I understood, they were suggesting that variation in the samples or sampling method needs to be adjusted for and this can be done by comparison with a reference gene included in the test kit.  Gives a good sense of the complicated nature of PCR testing and result interpretation.

Thanks to a reader who passed on the Qwest Diagnostics FDA insert for PCR testing.  Dry and technical but gives an interesting glimpse into the process and potential issues.  (Qwest FDA Insert)