Even TELLURIDE testing has problems....and they were forward thinking FIRST

Pony Soldier wrote: www.washingtonexaminer.com/news/random-s...tter_impression=true

Impressions of this study?

I was hoping for SC’s input on that study. If it to be believed, it seems that there are many more asymptomatic carriers than previously thought. I’m not sure what the ramifications of that would be. They still have no cure for the common cold and it is the same family of virus. I’m not going to believe that a vaccine is forthcoming based on that. Where do we go from here?

With the caveat that it has not yet undergone peer-review verification, that study seems (see sampling issues in next reply and why this study has to be taken very skeptically) to be confirming what we have known: the SARS-CoV-2 has a higher transmissibility rate, many more asymptomatic carriers, and lower mortality rate than original numbers indicated.

"We can use our prevalence estimates to approximate the infection fatality rate from COVID-19 in Santa Clara County. As of April 10, 2020, 50 people have died of COVID-19 in the County, with an average increase of 6% daily in the number of deaths. If our estimates of 48,000-81,000 infections represent the cumulative total on April 1, and we project deaths to April 22 (a 3 week lag from time of infection to death 22), we estimate about 100 deaths in the county. A hundred deaths out of 48,000-81,000 infections corresponds to an infection fatality rate of 0.12-0.2%. If antibodies take longer than 3 days to appear, if the average duration from case identification to death is less than 3 weeks, or if the epidemic wave has peaked and growth in deaths is less than 6% daily, then the infection fatality rate would be lower. These straightforward estimations of infection fatality rate fail to account for age structure and changing treatment approaches to COVID-19. Nevertheless,our prevalence estimates can be used to update existing fatality rates given the large upwards revision of under-ascertainment.

As of today, Santa Clara has 73 deaths - in line with the study's estimates.

The U.S. currently has 40,665 deaths reported which would correspond to an estimated 20,332,500-33,887,500 infections using their 0.12-0.2% CFR (note: the Johns Hopkins site says we have 759,118 confirmed cases, and Trump said today in his press briefing that 4 million Americans have been tested - significantly less than what is estimated in those numbers). In order to achieve herd immunity, we need at a minimum 70% of the population to have been infected, or 245,000,000 Americans - 7.23-12.05X the number we have now. That equals 294,008-490,013 Americans dead before we could, with high confidence, say we're past this. Keep in mind that number would go higher if we were to fully open and most people go back to their usual behaviors - we'd have a rapid spike in cases overloading hospitals causing a significant number of unrelated deaths (acute trauma, heart attacks, cancer, etc) due to lack of beds and healthcare workers to attend to those cases.

As far as a vaccine, it is wholly possible one can be created. During the 2002-2003 SARS pandemic (caused by SARS-CoV), a vaccine was developed, but never used because the pandemic ended before they could finish testing it. That SARS coronavirus uses the same spike protein to infect cells that this SARS-CoV-2 coronavirus does, and from what I've read at least one (probably many more) laboratories are targeting that protein for antibody creation. I saw an article postulating testing the previously created SARS antibody to see if it's effective on this virus, but I haven't seen nor heard of any studies (I think the previous SARS antibody never made it past the animal testing phase? I could be wrong about that).

Trevor Bedford @trvrb April 17

Very interesting new preprint by Eran Bendavid and colleagues reports seroprevalence estimates from Santa Clara county. Great to have seroprevalence work start to emerge, but I'd be skeptical of the 2-4% seroprevalence result. 1/8

@nataliexdean
gives an excellent overview here and includes a few caveats to keep in mind. 2/8

So, the major reasons why I remain skeptical:
- Unstable population weighting
- Wide bounds after adjusting for clustering
- Is test specificity really that high?
- Unavoidable potential for consent bias
- Is this consistent with other emerging serosurvey data?
Fin 10/10

I'd pay particular attention to the dependence of results on test performance. The authors assume that the antibody test has 99.5% specificity (point estimate) based on manufacturer + Stanford validation samples where 399 out of 401 pre-COVID samples showed as negative. 3/8

Using equation from the appendix we can see how the estimate of prevalence varies with test specificity. A specificity of 99.5% converts an observed 1.5% positive to an estimated prevalence of 1.3%. 4/8

However, if we assume that the test is just slightly worse and has specificity of 98.5%, then, with observed 1.5% positivity, we'd estimate a prevalence of 0%. 5/8

I've ignored demographic weighting here as it doesn't play into this calculation. 6/8

Given how sensitive these results are to performance of the assay, I don't think it's safe to conclude that infections are "50-85-fold more than the number of confirmed cases". 7/8

Again, important to have this work being done. I'd just urge caution in interpretation. I will note again that I've been using a 10-20X ratio of cases-to-infections, but will be great to have more data here (I'd be happy to be wrong). 8/8

And see here for a full posterior seroprevalence estimate that takes into account uncertainty in sensitivity and specificity of the assay

@NimwegenLab thread on how NOT to do statistics like this study