OSUmetstud

Yeah the nature of testing is that there's larger error bars when the seroprevalence is lower.

The CDC has been doing a Commercial Lab Seroprevalence Survey in each state. In Indiana, as of September 15th, they had 4%. That should be representative of the infections around September 1st. https://covid.cdc.gov/covid-data-tracker/#national-lab And the caveats on the interpreting the data. Interpreting Serology Results from These Surveys These surveys have limitations to consider when interpreting the results. The surveys aim to collect specimens nationwide, although results might not represent the geographic and demographic distribution of the population. Blood samples for the study were not chosen randomly and might not be representative of the US population. People who have blood taken for routine medical care or sick visits might not represent people in the general population because of differences in their overall health, their disease exposure risk, because they sought health care and had a blood test, or because of their immune response to SARS-CoV-2 infection. Seroprevalence estimates for age and sex might not be available for all places. This can occur when there are too few samples to calculate the estimates for a specific age or sex group. Some results could be false-positive results (the test result is positive, but the person does not really have antibodies to SARS-CoV-2), or false-negative results (the person has antibodies to SARS-CoV-2, but the test doesn’t detect them). False-positive results are more likely to change the survey results if it is an area where the percentage of people previously infected is relatively low. This might cause results to estimate that more people are infected in the community than actually are. Results from seroprevalence surveys should not be interpreted to mean that people who have tested positive for having SARS-CoV-2 antibodies are immune. We do not know whether having SARS-CoV-2 antibodies provides protection against getting infected again. Other studies are planned to learn more about SARS-COV-2 antibodies, including how long they last, whether they provide protection against getting infected again, and if people get infected again, whether having antibodies can make that illness milder. While some seroprevalence surveys study risk factors for infection, such as a person’s occupation or underlying health conditions, this seroprevalence survey was not designed to be able to provide that information. Finally, other seroprevalence surveys are designed to show how long antibodies last in people’s bodies following infection. This survey was not designed to provide that information.

Sigh. Early on in the pandemic we didn't know how to best treat people. It was typical practice to put people on low oxygen with covid on ventilators. Now that we know more they don't put people on ventilators as much. They're still used at a certain point when oxygen is really low. There's 6000 people on ventilators with Covid right now. Covid sucks. The ventilators didn't cause the breathing issues and they didn't cause the pneumonia. Why is it so hard to you to accept that this a terrible disease killing lots of people and the doctors and scientists on the frontlines are doing their very best to treat people?

Theres 6000 people in the US right now on ventilators because they have covid 19 and need oxygen.

Dude is a ****ing nut.

You have no idea what you're talking. Literally none. Not everyone has it...most haven't. We aren't killing people with ventilators. These people need oxygen.

Stop polluting the board with your nuttiness.

This is an old article. The NYT article which does a better job at describing the issue discusses why. Its likely that these people are being caught too late in their illness/infection when they get their positive test. Michael Mina discusses this back a few months ago on this week in virology. The average cycle to positive was 35 on the the RT-PCR meaning the majority of people are being caught after they are infectious. The point of care antigen testing thats being done more now is less sensitive so if you're positive from that you're more likely to fall in the infectious band. The high sensitivity RT-PCR test is still needed for clinic diagnosis. When people are late in their illness and show up at the hospital sometimes they have very little virus left. The inflammatory response is whats killing people generally not when they have a huge amount of virus.

When there's a high volume of cases...its really difficult to do effective contract tracing. So its hard to say where the most likely source is of the majority of infections.

More likely to catch staph or gonorrhea at the gym...

It's because it seems like a very circuitous way to get to your end goal. Scientist and health folks certainly know that being overweight leads to poor health outcomes in general, but you're going to get far more bang for your buck with social distancing, masking then you are with hoping that some people listen and get healthier. I don't believe obesity is as big of a problem in Europe as it is in US, but they're still having a hell of a time.

I think your point is well taken from an individual risk standpoint. You could potentially reduce your risk a bit by losing a bit of weight and exercising. The idea that we can exercise our way out of a pandemic though seems pretty tough, though.

Nice. This estimates look much more reasonable imo than his previous model estimates. His previous model had the summer wave like double the size of the spring wave which just didn't seem reasonable and wasn't consistent with the CDC antibody studies. I still might peg the summer wave a bit smaller than he does. I'm not sure equal size makes sense.

The population being infected does not represent a perfect slice of the US population. The implied IFR lowers since older folks are protecting themselves more than younger folks. You can see this reflected in the age stratified CDC commercial lab survey. https://covid.cdc.gov/covid-data-tracker/#national-lab I know the CDC IFR estimates from March/April is slightly over 1% when adjusted for population distribution and afaik we have not cut the disease IFR by better treatments in excess of 60 percent. The UK hospitalization data is better than the US because its more nationalized. The in-hospital death rate there appears about 45% lower than the first wave. 16x early on is too high imo. The antibody data from that time averaged more like 12x.