My working assumption was that anyone interested in discussing epidemiology models and their implications would understand the relevant terminology.
Peace,
Chris
My working assumption was that anyone interested in discussing epidemiology models and their implications would understand the relevant terminology.
Peace,
Chris
My working assumption was that anyone interested in discussing epidemiology models and their implications would understand the relevant terminology.
Peace,
Well, that certainly limits the audience of the valuable information you have to provide.
Have you considered broadening the potential recipients of your wisdom?
About 1.1% of detected cases in the 20-24 year old group in FL ended up hospitalized. Source (warning takes some time to load): https://public.tableau.com/shared/87CYDHBM5?:display_count=y&:origin=viz_share_link
I wonder how many of their compadres were asymptomatic or mildly asymptomatic.
asymptotic or mildly asymptotic.
Pushing the line?
Autofill and autocorrect are my worst enemas.
Fortunately, people with integrity and compassion ignore typos. But people who want to “count coup” don’t.
I wonder how many of their compadres were asymptomatic or mildly asymptomatic.
The answer is just enough to downplay or ignore the virus. You know 70% of Polio infections were asymptomatic too.
In all honesty, the asymptomatic rate is probably about 40% but keep in mind the FL statistics I shared is detected cases. We probably miss at least 4-6x of all cases for that age range. Here were my estimates from what the true toll of college students was using the best data I could find at the time:
How badly could COVID-19 impact college students this year? That’s a tough question to answer, but let’s begin with a few things. (Also, If you see anything that I’m missing or have a bad estimate for, let me know. ) There are about 20,000,000 college students at any given time, but about 3 million are exclusively online. [1] This number might be higher this semester than usual, so let’s go with double that will be exclusively online. This leaves maybe 14,000,000 college students returning to …
The answer is just enough to downplay or ignore the virus.
It is neither downplaying or ignoring.
It is noting there are many infections which cause no or negligible ill effects.
There is a difference.
We probably miss at least 4-6x of all cases for that age range.
It could be substantially higher than that. I suspect it is, given the CDC estimates.
It is neither downplaying or ignoring.
It is noting there are many infections which cause no or negligible ill effects.
There is a difference.
Yes, but we didn’t make a big deal about Polio because of the 70% asymptomatic people. And just say ‘meh, it’s no big deal since the vast majority of people just recover without any symptoms… or stop your fear mongering, less than 1% of people actually are left paralyzed.’
It could be substantially higher than that. I suspect it is, given the CDC estimates.
Yeah probably not. I don’t have any energy to say more right now but the estimate you are thinking of is for a specific time and place and could be biased toward the high end since they were getting samples from people who already went in for bloodwork. But many people who went into the doctor’s during such times were more likely to have COVID-19 than the general population.
Yeah probably not.
Antibody testing reveals that more people have been infected with Covid-19 than confirmed testing shows, though most Americans are still vulnerable.
Est. reading time: 5 minutes
“Still, the data reflect what CDC Director Robert Redfield recently said — that true case numbers are 10 times higher than confirmed diagnoses.‘
Yes I know. Limitations from the paper itself:
Our study has limitations that are associated with both the samples and with the tests used. The specimens were collected for clinical purposes from persons seeking health care and were shared with the CDC with minimal accompanying data. No data on recent symptomatic illness, underlying conditions, or possible COVID-19 exposures were available. It is possible that specimens were drawn from patients seeking care for suspected COVID-19 symptoms, potentially biasing results, particularly in settings such as NY where disease incidence was higher. Lab B sampled sera from metabolic panels taken at routine outpatient visits; Lab A sampled randomly with respect to clinical test type and admission status. Residual clinical specimens from screening or routine care are more likely to come from persons who require monitoring for chronic medical conditions despite the ongoing pandemic. These persons may not be representative of the general population, including in their health care seeking and social distancing behavior, immune response to infection, and disease exposure risk. Representativeness may vary by age group as well. Therefore, our seroprevalence estimates should be confirmed and extended by other studies, including serosurveys that use targeted sampling frames to enroll more representative populations.
Basically, it was a convenience sample which likely over-estimated prevalence.
See this discussion of the study:
https://twitter.com/DiseaseEcology/status/1285696432478052355?s=20
Some other samples likely more representative:
3x detected cases: https://healthcare.utah.edu/publicaffairs/news/2020/07/utah-hero-project-phase-1.php
4x detected cases: IUPUI, ISDH release findings from Phase 2 of COVID-19 testing in Indiana: IU News
4.5-5x detected cases: https://washoecounty.us/outreach/2020/07/2020-07-08-jic-update-0708.php
4-6x detected cases: Phase II results of Co-Immunity Project show higher-than-expected rates of exposure to novel coronavirus in Jefferson County — School of Medicine University of Louisville
Many of these results were methodologically more robust than a convience sample which was already biased towards more people with COVID-19 like the CDC study was. I hope I just didn’t waste my time.
Interesting studies.
I found this noteworthy from the Utah study:
I find the estimate surprising low, don’t you? I would have suspected people living in the same household would have a much higher likelihood of infecting one another. Of course, this could be an indication of substantial natural immunity.
I find the estimate surprising low, don’t you?
Yes, that is surprisingly low!
I find the estimate surprising low, don’t you?
I don’t know, I have no knowledge of SAR for various infectious diseases. Do you?
I would have suspected people living in the same household would have a much higher likelihood of infecting one another.
The numbers published so far seem to vary widely depending on various practices from as low as 4.6% and as high as 49.56% as per this review paper:
Summary. Coronavirus disease 2019 (COVID-19) is a novel virus with continuously evolving transmission trends. Contact tracing and quarantining of positive cases
Of course, this could be an indication of substantial natural immunity.
Yes of course, the pandemic is basically over worldwide according to that one Utah study.
I don’t know, I have no knowledge of SAR for various infectious diseases. Do you?
I have seen some reports such as:
Blood samples taken before the COVID-19 pandemic showed that some people already had certain immune cells that recognize SARS-CoV-2, possibly because of common colds.
I have seen some reports such as
Yes, but what does this have to do with the wide variance of secondary attack rates in households? All that it means is perhaps some people might have lesser infections (but still get infected) due to previous infections. It wouldn’t protect against you not getting the virus.
Yes, but what does this have to do with the wide variance of secondary attack rates in households?
If people in the household are immune to Covid-19 from infections years ago, then we could expect a low secondary infection rate.
This disease has been described as quite infectious, but if only 1 in 8 people in the same household get infected, then it appears there is some natural immunity from some source.
It wouldn’t protect against you not getting the virus.
Is that a triple negative?
Big if.
Big if.
Feel free to offer an alternative explanation for the estimate that only 1 in 8 people in the same household get an infection.
Because 40% are asymptomatic? I saw one estimate that was 20%, and I think they thought that was low. There are lots of estimates aren’t there.
Could you elaborate on a 40% asymptomatic rate meaning 1 in 8 people in the same household with an infected person don’t get the infection?
Note that being asymptomatic is not the same as not getting the infection.
See the earlier post:
When one member of a household had antibody to SARS-CoV-2, the proportion of other members of the household that were seropositive was 12.4%. This figure is a rough estimate of the secondary attack rate of COVID-19 infection within households.
Doesn’t seropositive imply past infection, whether asymptomatic or not?
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