The biology of coronavirus COVID-19 - including research and treatments

Coronavirus: Hospital cuts COVID-19 death rates with 'black boxes' for sleep disorder

"Medics fighting COVID-19 in a hospital in Cheshire seem to have cut mortality rates and improved the chances of a quick recovery from the virus by adapting breathing machines normally used for a sleeping disorder.

Doctors at Warrington Hospital have modified devices known as "black boxes" which usually treat sleep apnoea - a condition which means breathing stops and starts while sleeping."

 

There is a bivalent norovirus vaccine that is currently undergoing phase 2 trials, it is based on recombinant capsid proteins, combined with an adjuvant.

https://clinicaltrials.gov/ct2/show/NCT03039790
https://www.clinicaltrialsarena.com...al-tak-214-treat-norovirus-infection-4928408/

 

Does anybody know how reliable the current antibody tests are? Or does that depend on the manufacturer?

 

Medscape: The Great Invader: How COVID-19 Attacks Every Organ

 

IT consultant interviewed on news last night (UK) said that what they needed were not more ventilators but CPAP machines and dialysis machines.

 

Not really answering your question!

The head of Roche was interviewed recently; they are due to release a test soon (next month?). He mentioned they're main competitor was also releasing a test about the same time.

I assume they'll vary i.e. in accuracy.

I don't know if they will be accurate enough for personal use. 99% would be great; i.e. you might be inclined to risk your life/your families life on it. However, if they're 60% that's not much better than random but for a population it might tell you something.

Seen something on rates of populations infected in Europe --- really low 2-3% levels.

 

I actually just came across this article from Stat news about this very subject!

https://www.statnews.com/2020/04/24...to-be-released-heres-how-to-kick-their-tires/

If you scroll down to the subheading:

“So about those false positives and false negatives?

No test is perfect. And the sheer number of antibody tests — Dutch virologist Marion Koopmans recently saw nearly 275 on a list maintained by the WHO — makes it very tough at this stage to know how good any of them actually are. The WHO is working with a number of labs trying to validate tests, said Van Kerkhove, who added: “Unfortunately that takes a little bit of time.”

In particular, the rapid tests appear not to perform well at all. Koopmans, the head of virology at Erasmus Medical Center in Rotterdam, said the Dutch national serology task force has recommended that people not use the rapid tests, because of the risk that people will get a false result and assume — if it was a positive — that they have protection they do not in fact have.

Every serology test is going to produce some erroneous results. Some people who were truly sick will test negative — that’s a false negative. Some people who were not sick will test positive — that’s a false positive.

Each commercial test comes with guidance from the manufacturer about how “sensitive” it is — in other words, what percentage of true positive cases it will detect — as well as how “specific” it is, meaning how good it is at not generating false positive results.

Those estimates are especially important when the rate of infection in an area is likely low. Even a small over-estimate — say a 5% false positive rate — can vastly increase the final projection of how many people in a location had been infected.

Michael Osterholm, director of the Center for Infectious Diseases Research and Policy at the University of Minnesota, drew up a chart to explain how different rates of sensitivity and specificity will impact a serology study in an area with 1 million people, using a test that had 95% sensitivity (caught all but 5% of true positives) and 95% specificity (designated as positive only 5% of people who were actually negative).

If 5% of the population had been infected with SARS-CoV-2, there would have been 50,000 infected people. This test would find 47,500 (the true positives) but it would miss 2,500 (the false negatives). And it would detect 47,500 false positives — as many false positives as true positives. If the rate of infection in the community was smaller, the percentage of wrong results would rise.

If the rate of infection in the community increased, the errors become less substantial. If 15% of the community — 150,000 — had been infected, this test would find 142,500 true positives, 42,500 false positives, and would miss 7,500 cases — the false negatives.

Applying this knowledge to Thursday’s results from New York puts the picture in sharper focus. The release from the state doesn’t disclose the sensitivity of the test used, but it does note the specificity is between 93% and 100%, a “huge range,” Ashish Jha, head of Harvard’s Global Health Institute, noted on Twitter. If the test performed at the low end of that range, New York’s infection rate would be closer to 7%— half the figure Cuomo announced — and nearly one out of every two positives would have been a false positive, Jha said.

“These tests don’t perform like people think they do and so there are a lot of crazy results,” Osterholm said. “You can often find more than half of the positives you do document are actually false positives.”

There’s a lot more in the article after that.

 

@Leila there is also this:

https://www.nytimes.com/2020/04/24/health/coronavirus-antibody-tests.html
Coronavirus Antibody Tests: Can You Trust the Results?

 

Thank you!

The cross reaction with other cold related coronaviruses and the fact that you can't even rely on the manufacturer's data on sensitivity and specifity is unfortunate :/

 

It takes years to validate a test and do all the tweaking necessary to make them consistent and even then individual batches can go wrong. You are dealing with biological systems which are different from the straightforward biochemical tests that are done in medicine.

 

Background immunity from previous corona infections?

"According to Berlin-based virologist Christian Drosten, mild or symptom-free corona courses could be related to previous infections with cold coronaviruses.

Referring to a study by a Charité colleague, the scientist confirmed on Friday in the NDR podcast that a certain background immunity appeared to exist in the population.

Drosten’s team was involved in the study of so-called T helper cells, which are central to the immune response."

 

It doesn't just depend on the manufacturer, it depends on the batch, how patient samples are gathered and processed.

Both sensitivity and specificity in the 80-95% range are typical of these sorts of tests. I am very sceptical of claims of 95%+ specificity, given no large validation studies (comparing to other tests and various clinical diagnostic criteria) have been published. Which is to say, the reliability will be acceptable at best for pre-screened populations (eg clinical signs and known exposure) and have very high error rates on unscreened populations.

There is still no confirmatory of "symptom-free" COVID-19 cases. Lots of people are speculating on the back of poor test accuracy and not understanding that symptom questionnaires and symptom reporting to doctors is also subject to a variety of biases that could give the wrong impression.

I've seen similar arguments suggesting the opposite: based on the original antigenic sin hypothesis that those who have prior exposures may be more at risk.

 

https://twitter.com/user/status/1253814761470509057

 

I've heard the term "oligosymptomatic" to describe low level symptoms.

According to this Korean study over the course of 14 days only 4.1% of the infected people in a call centre truly remained completely asymptomatic.

"Among the 97 confirmed case-patients, 89 (91.7%) were symptomatic at the time of investigation and 4 (4.1%) were presymptomatic during the time of investigation but later had onset of symptoms within 14 days of monitoring; 4 (4.1%) case-patients remained asymptomatic after 14 days of isolation."

 

'Presymptomatic' (or reporting a low level of symptoms before they subsequently get worse) is not what I'm talking about. I'm saying there aren't cases that are so 'mild' that the person is infected and recovers without ever realising they had an infection.

That is 4/1143 people tested, or 0.3%. Or a test specificity of 99.7%, if they are false positives.


A specificity of 99.7% is in the typical range of these tests, according to this recently published meta analysis:
https://pubs.rsna.org/doi/10.1148/radiol.2020201343

Even good labs can suffer from contamination and other technical issues.

 

I think this is also a result of people w/o health problems being used to more favorable timelines. They assume they whole scientific community is working on it day and night so it must be possible.

It'll be interesting if they do force a untested vaccine out after preliminary phase II trials. For everyone under a certain age, the risk of an untested vaccine could conceivable be higher than their chances of severe illness. Thus getting to a quick herd-immunity via vaccines that are not well vetted my require political or social pressure. And depending on how safe the vaccine is that could be a good or bad thing. And this will on depend on how things look when the vaccine becomes avaible to the public.

On TV here, there are two great fallacies being spread by doctors on the news networks (real doctors! not just the dr. ozs).

1) That most who get the virus will be asymptomic or have no obvious symptoms.

2) They optimistic "believe" a vaccine will be out in 12 months ( said to be a point of fact).

 

Now 2 minkfarms infected in the netherlands. Likely by humans.

No sighns of infection of big farm animals yet.

 

Study of twins reveals genetic effect on Covid-19 symptoms

https://www.theguardian.com/world/2...s-reveals-genetic-effect-on-covid-19-symptoms