I personally know two people who have long 'recovered' from Covid but still have no smell, or a reduced sense of smell. Not life threatening or really holding them back from anything, but they say it effects their quality of life more than they expected.
Luckily a long haul isn't always a forever haul, we can hope.
- 30 gallon plastic bin (look for one with flat sides, not a "heavy duty" model with ridges along the side -- if your cat is a side-pee-er, this will be difficult to clean).
- Cut a hole in the side with a utility (aka x-acto) knife, 9 inches from the bottom.
- Fill with 3.5-4 inches of unscented, clumping litter. I've tried Dr Elsey's and World's Best, and prefer the former, which I found clumps better; I believe other clay-based litters are equivalent to it.
- Buy a litter-lifter, it's the best scoop, hands down. After I tried it the first time, I actually placed a bulk order (25 scoops) so that I have a guaranteed lifetime supply (and for gifts), because I never want to use another scoop.
- Clean the litter box at least once per day. I know this sounds like a lot, but it's actually not -- with the scoop above, it takes me ~10 seconds per "item" (pee ball or poop cluster) you scoop out (unless your cat is a side-pee-er), plus maybe 30s moving the litter around to find the items and even out the litter at the end. (I've timed this; in total it's around 1 minute if I scoop once per day).
Info is sourced from https://catinfo.org (specifically https://catinfo.org/the-litter-box-from-your-cats-point-of-v... and https://catinfo.org/making-cat-food/#Constipation ) and verified by personal experience.
https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/burd...
And obviously a number of people have been infected since. But just using the 83 million number from the CDC, 2% of that would be 1.6 million people.
How can you possibly believe this, given the seroprevelance data? Every indication is that more than twice this number (some surveys suggesting substantially more even than that) were already infected a few months ago.
Given that effectively nobody was dying from COVID prior to March, and the three giant waves of exponential growth that followed, I have severe doubts about the accuracy of these tests. I have a feeling that if those same tests were ran back in 2018, they would have said the same thing.
That's not quite true. The surveys in that time frame were mostly < 10%. The > 10% surveys came months later.
However, it's certainly possible that these are false positives (particularly the wastewater studies).
However I'm not sure that this particular observation is a good basis for that conclusion. It takes a substantial mass of cases to produce excess population-level mortality, which is what gets our attention.
Since we weren't testing for cases prior to March 2020, we really don't know how many people died while infected with the virus. Now of course we count nearly every such case meticulously.
It's possible that it was fairly widespread, and some people were dying (and perhaps being reported to ILInet, etc), but not enough to cause a notable increase in population-level mortality for anybody to notice.
There is ongoing conjecture on this point all over expert circles.
2. Mortality rates were not above the baseline prior to March.
3. We know that the virus spreads like wildfire when no quarantine measures are taken. No quarantine measures were taken at any point prior to March.
4. The growth in known cases and above-baseline mortality closely matches, starting in March.
It's impossible for there to have been a significant presence of the virus in the United States at the start of 2020, as claimed by seroprevalence data, because within a matter of weeks it would have infected a large enough percentage of the population to be clearly visible in the above-baseline mortality rates, and hospitalization rates. A large percentage of people who catch COVID end up going to the hospital, or the morgue when they are unable to breathe. In a pre-quarantine/lockdown world, they also tend to get everyone around them, as well as a whole bundle of unrelated people sick in the process.
Either the seroprevalence data is wrong, or the virus was somehow uncontagious or unlethal, until March, when all across the country, all at once, somehow, it turned into something that was quite contagious, and quite lethal.
When your measurements claim an invisible, inaudible, imperceptible phenomena that has no physical influence on any other object, the prudent scientific conclusion is that your measurements are broken.
This is only true if we presume that it was equally spread across risk strata. But it's also possible that it didn't make its way from younger travelers into the higher risk stratum in sufficient measure to start causing significant mortality for weeks.
> A large percentage of people who catch COVID end up going to the hospital
This is simply false, unless your definition of 'large' is a fraction of a percent.
> In a pre-quarantine/lockdown world, they also tend to get everyone around them, as well as a whole bundle of unrelated people sick in the process.
This is true of a lockdown world as well; in fact lockdowns don't appear to be negatively correlated with population-level mortality at all, spare a very few examples, all of which are island nations which have also maintained various travel bans and similar measures. But in the USA and mainland Europe, lockdown states have fared quite horribly. I can't tell you how happy I am to be in Florida (no lockdown, mortality substantially below average, risk-adjusted mortality notably and incredibly low) instead of my home state of NY (intense lockdowns and a resulting bloodbath).
I don't see any reason to believe that widespread presence of the virus would have been noticed as anything but an uptick in ILInet (which of course we did see) until it got into long-term care homes and other places with high concentrations of at-risk populations.
> Either the seroprevalence data is wrong
Again, this is possible; I'm not saying it's not. But it has been reproduced over 20 times now, with different tests, some of which appear to have a perfect record of selectivity and also good record of sensitivity.
> or the virus was somehow uncontagious or unlethal, until March, when all across the country, all at once, somehow, it turned into something that was quite contagious, and quite lethal.
In the vast majority of the population, the virus isn't particularly lethal. That's really the discussion here - whether it might have spread more widely through the lower-risk strata prior to widespread infections among the vulnerable.
It may not have been equally spread across risk strata, but in a pre-lockdown world, even if you are in a low-risk group, you have social contact with people who are in high-risk groups, through public transit, grocery stores, services that you visit, relatives that you visit, hospital waiting rooms, urgent care waiting rooms, hospital wards where doctors don't wash their hands as frequently as they should, workplaces, and the list goes on.
Is it possible for a small group of people (low thousands) to have had the virus across the country, when the official count was in the tens and low hundreds? Absolutely! I can see this happening. It seems to fit with the pattern of infections flaring up all across the country at roughly the same time.
Was it possible for millions of people to have had the virus (which is what the sero data points to), for over two months, without getting other people sick in a manner that would show up on the statistics? That is an incredibly strong claim, with only one data point that supports it, and a lot of data points that oppose it.
With the benefit of hindsight, it is clear that the sero data was not a good predictor of the future in March of 2020. What has changed about it, that makes it a good predictor of the future in March of 2021?
> I can't tell you how happy I am to be in Florida (no lockdown, mortality substantially below average, risk-adjusted mortality notably and incredibly low) instead of my home state of NY (intense lockdowns and a resulting bloodbath).
If Florida had the population density of NYC, with people of all demographics sharing the same public transit infrastructure, sharing the same elevators, packing the same grocery stores, it would be a graveyard. You're ignoring all sorts of conflating factors, by pointing at two vastly different datasets, and concluding that because one had a lockdown, and the other one didn't, lockdowns don't work.
Counterpoint - Washington state has had lockdowns, and despite having a similar population density to Florida, has half the death rate of it. To the surprise of absolutely nobody, death rates are much higher in counties with lower compliance rates (Yakima versus Pierce, for example...)
Oh, and when lockdowns would get relaxed, three weeks later, like clockwork, infections and deaths would spike up.
It's an infectious airborne disease. The more people that carriers are in close quarters with, the faster it spreads. Reducing the number of people the average person is in contact with, healthy, or otherwise, reduces it's rate spread. I am not sure why this is still controversial in 2021.
You're arguing with an imaginary friend. Nobody is making the points you are refuting.
The reason that lockdowns have so spectacularly failed isn't that there's some mystery about the nature of spread of respiratory pathogens; it's that lockdowns don't actually achieve any of the conditions that prevent spread except for people wealthy enough to have the means to isolate (and there's no reason to believe they'd refrain from isolating even in the absence of a state mandate).
Instead, lockdowns shift risk onto poor people ("essential workers") without regard to their level of risk. So, instead of a more acute spread occurring through the lower risk strata, we get a more acute spread occurring through the less affluent economic strata.
I don't have sufficient knowledge to concur with or refute your assertion that the sociological conditions of the high-risk stratum (ie, sharing public transit, etc) make the results of the dozens of seroprevalence surveys implausible. However, I do note that people who study these things for a living are saying that it is plausible.
That said, I have some doubts about the 2% number. Estimates vary widely from about 2% as the lowest plausible number I've seen to about 10% at the highest plausible number. If it's really 10% of infected people reporting long-term symptoms, that changes things a bit. Also note that pretty much all of the sources are preprints or otherwise not peer reviewed articles -- an actual rigorous investigation is very welcome here, and hopefully that is what the $1B from NIH will buy.
Uh, what? The WHO updated their guidelines a month and a half ago because PCR tests were being misused: Too many cycles and not taking symptoms into account was resulting in too many false positives.
https://www.reuters.com/article/uk-factcheck-who-instruction...
The part that primarily caught my eye, which isn't what Reuters is attempting to debunk:
> Where test results do not correspond with the clinical presentation, a new specimen should be taken and retested using the same or different NAT technology.
"clinical presentation" - in other words, the symptoms. This advice runs contrary to the entire past year, where a single positive test in an asymptomatic person has counted as a case. This alone is enough to inflate the numbers, without even taking PCR cycles into account.
And Reuters ends up just barely short of confirming the part about PCR cycles anyway:
> ”The WHO are saying that if the manufacturer has defined a value but you could if you chose to adjust that setting, please don’t - stick to what the manufacturer has stated because they have done the earlier work to determine the best value for that threshold,” Mackay said.
Labs using too high a threshold has been a concern for about half a year: https://www.nytimes.com/2020/08/29/health/coronavirus-testin... (And note the numbers in this article, almost all in the range of 33-40 cycles - I recall on rare occasion seeing higher reported elsewhere, around 45 and 50 cycles)
This is right-wing conspiracy theory.
>the tests were not being used in compliance with instructions
This is science.