Coronavirus Pandemic (COVID-19) (SARS-CoV-2) [2020]
- Thread starter RDGoodla
- Start date
Yeah, these are counting those coming into hospital with a covid19 infection, not necessarily because of it. We're still in the dark. 
Each Nation in UK will determine this slightly differently. But just reading through some notes here on the APIYeah, these are counting those coming into hospital with a covid19 infection, not necessarily because of it. We're still in the dark.
From my standpoint, 'New Admissions' is probably the closest metric you'll get to 'because' of covid-19.
It is reasonable to use it as a proxy. There is enough give / take to use this represent the majority of covid admissions as meaning, admitted due to covid.
England:
The majority of inpatients with Covid-19 are admitted as a result of the infection. A subset of those who contract Covid in the community and are asymptomatic, or exhibited relatively mild symptoms that on their own are unlikely to warrant admission to hospital, will then be admitted to hospital to be treated for something else and be identified through routine testing. However these patients still require their treatment in areas that are segregated from patients without Covid, and the presence of Covid can be a significant co-morbidity in many cases. Equally, while the admission may be due to another primary condition, in many instances this may have been as a result of contracting Covid in the community. For example research has shown that people with Covid are more likely to have a stroke (Stroke Association); in these cases people would be admitted for the stroke, classified as ‘with’ Covid despite having had a stroke as a result of having Covid.
Wales
From 29 June 2020, patients admitted for elective procedures were only included in COVID-19 related admissions if they received a positive COVID-19 test result on arrival at the hospital. Health boards were also asked to exclude transfers between acute and community hospitals from admissions figures. Prior to this, some transfers may have been captured as new admissions.
From 3 July 2020, guidance was updated to only include emergency admissions in the COVID-19 related admissions figures.
Try the following link:
https://anthonybmasters.medium.com/primary-diagnoses-covid-patients-ii-964fd4fbabc
The majority (i.e. around 75%) of Covid admissions reported are due to Covid and not incidental, regardless of what a Telegraph/Daily Mail journalist might misunderstand.
Can we put this one to bed now?
Another 1,000 patients in hospital today compared to yesterday:
Still a long way below the January peak, of course. It also does seem as though the number of people requiring ventilation isn't rising at a similar level, so hopefully pneumonia caused by Omicron will continue to remain at lower levels compared to previous variants. Just depends on what we see as it reaches older age groups.
Can somebody explain to me why the UK government doesn't think any mitigations need to be put in place to control the spread of Omicron whilst at the same time making plans to open up field hospitals in car parks? It doesn't really seem as though it should be an either/or situation. Still, I suppose at least they are making plans as to what can be done in case of overwhelming numbers requiring treatment. Would be better to try and avoid the risk of overwhelming numbers first.
https://anthonybmasters.medium.com/primary-diagnoses-covid-patients-ii-964fd4fbabc
The majority (i.e. around 75%) of Covid admissions reported are due to Covid and not incidental, regardless of what a Telegraph/Daily Mail journalist might misunderstand.
Can we put this one to bed now?
Another 1,000 patients in hospital today compared to yesterday:
Still a long way below the January peak, of course. It also does seem as though the number of people requiring ventilation isn't rising at a similar level, so hopefully pneumonia caused by Omicron will continue to remain at lower levels compared to previous variants. Just depends on what we see as it reaches older age groups.
Can somebody explain to me why the UK government doesn't think any mitigations need to be put in place to control the spread of Omicron whilst at the same time making plans to open up field hospitals in car parks? It doesn't really seem as though it should be an either/or situation. Still, I suppose at least they are making plans as to what can be done in case of overwhelming numbers requiring treatment. Would be better to try and avoid the risk of overwhelming numbers first.
Last edited:
This is what I feared would happen from the first day of those lockdowns. People, notably the youngs, would badly react because of those lockdowns, masks and privation of liberty. They main stat we should look at is excess deaths as this is the only reliable way to assess the results of those policies.
If you look around you you'll see how notably those lockdowns have terrible results on the youngs, notably children. Just look around you. Fear (caused here by the governements) as the basis of a community has always being bad news and caused terrible things.
If you look around you you'll see how notably those lockdowns have terrible results on the youngs, notably children. Just look around you. Fear (caused here by the governements) as the basis of a community has always being bad news and caused terrible things.
https://nationalpost.com/opinion/sabrina-maddeaux-lockdowns-are-killing-young-canadians
That article is a bit off. Official death records require death by covid by the coroner to be counted as an official death. There are lots of ways to die while complicated with covid and they won’t report it as a covid death.
Excess deaths globally for 2020 to end of 2021 is 20M. Official death count by covid is only 4M.
that means a lot of people are dying from covid; there is no way we have 4X more suicides than covid deaths.
national post is … eh.
Read the economist on this subject for actually looking at and doing proper stats. https://www.economist.com/graphic-detail/coronavirus-excess-deaths-estimates
That's will be complex as there are positive side-effects to lockdowns beyond COVID. For instance, nightclubs being closed mean less completely drunk people will drive their car. Or people won't get flu and die of it because they stay at home most of time or have learned hygiene.
digitalwanderer
Legend
For some reason this is the one that I keep watching, and it looks like we (the USA) should break all sorts of records by tomorrow.
My wife was watching some news show last night and I spit coke on my monitor in a not-laughing way when I heard the announcer say, "New CDC guidance warning of traveling on cruise ships as the omicron variant tears through ships at see, more coming up!".
All I could say was, "People are still taking cruises now, WHY?!!??".
My wife was watching some news show last night and I spit coke on my monitor in a not-laughing way when I heard the announcer say, "New CDC guidance warning of traveling on cruise ships as the omicron variant tears through ships at see, more coming up!".
All I could say was, "People are still taking cruises now, WHY?!!??".
My general take here, and I've not really added my opinion on anything since these are UK numbers; but I'll address a growing rise of discussion around covid admissions to hospitalizations since it's happening locally as well.
Previously, hospitalized by covid during the earlier strains was fairly representative of respiratory issues. And with the recent omicron strain, it may no longer reflect that well. That is something the general public is now becoming aware of, so I should address this.
The real world has long been using a particular type of classifier called a Niave Bayes Classifier, or Bayes Theorem. You can wiki it, but we use it for a bunch of conditional probability cases, in particular we still use it for weather etc. So when people want to know if it's going to rain, we look at what the probability it will rain, given it's cloudy. Or given the humidity is X. the key take away is we are looking at dependent probabilities, not independent ones (ie flipping a coin the probability is always independent).
So there is a lot of discussion centered around what are the real numbers of being admitted to the hospital due to covid, because the current provided numbers are hospitalization admissions with covid. In Bayes Theorem we would define this as
A) What is the probability for being admitted to the hospital due to covid
and
B) What is the probability for being admitted to the hospital given you have covid
And so in a discussion around severity - what is severe? Severe for most people should be going to the hospital to treat _anything_ when going to a doctor or a clinic would suffice for minor things. So it must be major enough to go to a hospital. We should remove elective surgeries, because they won't admit a patient for elective surgeries if you are covid positive, so that really just leaves people who have conditions that are severe enough that they require hospital treatment.
So if this is true then (B) is not a misleading metric. In fact it's an important metric to take note of for severity. That means, if you have covid, you have a higher % chance of being hospitalized. And in the same vein taken a step further
A) What is the chance I die from X ?
B) What is the chance I die from X given I have covid?
And B is likely higher than A, so once again it's an important metric. Because you never know when your ticket is up, and you don't want covid around to make things that you could have recovered from to make things worse.
Which is relevant when Covid has a potential impact on your treatment, but not when it's independent, such as a broken leg. So then you need breakdowns not only of how many cases are positive, but then what is the hospitalisation for, will a respiratory infection risk aggravating the condition, what are the co-morbidities and which ones compound with C19 and the primary care requirement, etc.
The Guardian article did a good job of explaining the additional issues of large numbers of hospital cases even if C19 isn't the driving cause of admission, but people's behaviour is considerably affected by an understanding of the risks as described, and there's a lot of talk that Omicron isn't any worse than a cold. We don't have any comparable metrics to actually question what that even means - for all we know, for decades we've been allowing simple viruses into hospitals that have then resulted in complications that could have been prevented with significant measurable impact.
From a data science POV, it's actually incredibly difficult to describe the data that we should be gathering necessary for a proper understanding. There's no nice formula that just needs case numbers, tests, and barometric pressure at sea level that come together to give a number that tells as Good or Bad outcome. Big Data almost seems to come unravelled by Too Much Data that doesn't fit together. Ever since inventing numbers, human beings have relied on them to gain an understanding, but they are quite limited in their ability to 1) correctly describe complex systems and 2) effectively communicate those system to the everyman and influence decision making for the best outcomes. For every number presented for a case, someone produces a number for the counter point, leading to the phrase, "lies, damned lies, and statistics."
One of the big decisions with the NHS is balancing need to prevent disease spread with NHS staff being off work. Which is better - to have positive testing staff stay off work for 7 days and build a backlog of treatments, delays in emergency response, and a reduction in the quality of care, or have them back to work as soon as possible and spread omicron with whatever collateral damage that brings? I don't think the numbers can tell us that and maybe we should just be asking the people trying to do the job what they need based on their ad hoc assessment?
While I'm sure there are incidents that are independent, I wouldn't say a broken leg would necessarily be one, though perhaps not a strong correlation either. But with COVID comes a greater risk of blood clotting, and blood clotting is something that comes with immobility, or in this case, squeezing off your leg with a cast. Treatment is likely the same, but they'll probably prescribe some additional blood thinners possibly just in case, or if there is some form of incident that could iimpact the heart. The impact is not necessarily relevant if you're only looking at treatment though. It's really all encompassing, while we cannot prove it, but if you are suddenly more accident prone as a result of having covid, or you make poor judgement driving a car resulting in an accident. Those are all things that sort of fall under the umbrella of 'chance of being hospitalized given you are infected with covid'. We are likely to see higher accident numbers with drunkenness, or sleep deprivation, but I wouldn't say Omicron is necessarily as harmless as the cold. The cold is pretty much harmless.
We can run a lot of these data points together, but what tends to happen is that people want explainable models. So suddenly things like deep learning get significantly harder to explain. We do have explainable AI tools, in which you run say a random forest or XG boosted tree and then following you can see the decisions made by looking at the tree or looking at a SHAP graph. But if people are comfortable with just 'AI', we can use deep learning and get some better modelling in. Though in this case, most people will want explainable AI. Generally if your model is becoming undone by more data points, the model needs to be assessed again to whether it's really capable of still modelling what it set out to do. Things change and this is a normal process.
In the same fashion the Gross Domestic Product does not tell us how happy citizens are or their quality of life is, looking at response and treatment times have no bearing on how happy the medical staff is. That being said, if the performance of the medical staff is based on how they feel, how well rested they are etc etc, then we likely have close to 0 metrics on that. No AI modelling would work there, and we're really just running on the intuition of the people overseeing the management of the hospital. The reality is, the world is aligned to run on money and money alone. There are very few things we allow to exist that are a suck on money and generate no money in return; but these intangible things are exactly what keep people happy. In particular, the most important one, is time. Just giving back time to people.
I don't know what the right answer is, but medical staff across the world has been just brutally crushed for the last 2 years. I would sum it up likely as being harder than 2 years of pure 'crunch time' at a video game studio struggling to release their product before deadline. These folks have not had a break and more mistakes will be made.
Yesterday I went to Croatia on a microtrip. I entered a bar and I wasn't asked to provide any Covid certificate. The place was crowded, nobody wore a mask and everybody was smoking. On top of that, some people laughed at me because I was wearing a mask.
It felt like...
Another perspective from Indonesia, where a bunch of places already back to normal (no mask, super crowded) for months despite government regulations.
These are a few anecdotes of what people say.
- If got hit by covid, its taken care of by universal health care (not really an universal health care but basically you'll get treated for free)
- Covid is exaggerated. It's a ploy to make small businesses dies.
- Its all from God. If we got Covid and die or survive, it's God's will.
Surprisingly, hadn't got people IRL saying covid is fake.
Also insider info from the main hospital in my place. The current hospitalizations rate is way lower than delta wave. Now the hospital is still have enough capacity. But doctors raises concern with the wave after new year holidays
Here in the UK, secondary school kids are going to be required to wear masks in the classroom until the end of January at least. Rather makes a mockery of the many earlier claims from officials that Covid doesn't spread in schools, so masking not required!
Hospitalisation rates now at the level from the SAGE forecasts before Christmas (which were dismissed by the usual suspects) and we still haven't had the Christmas mixing cases hit these rates yet.
Thankfully, it seems that we've been lucky in that the numbers of cases of pneumonia are greatly reduced in comparison to previous variants and we'll hopefully not see any great increase as it spreads into older age groups. The sheer number of cases is likely to make things very ropey, however. Even if cases are less severe, hospital stays are shorter and so on, the sheer numbers who will need to be admitted for treatment and the staff absences expected means it will be incredibly difficult for the health service to cope.
I read an interesting thread from Chris Hopson (don't have the link to hand) which explained what the Nightingale hubs (i.e. big tents in hospital car parks) are going to be used for. Fundamentally, they will be there to house patients who are recovering and awaiting discharge. Those more seriously ill will still be treated in the hospital, but even with emergency staffing levels it will be touch and go. At least, that's the plan. Unfortunately, it is likely the pressure on staff and resources will lead to a lot of unnecessary deaths, many not caused by Covid, due to an unavoidable drop in standard of care. Should still be way below the numbers seen during the Alpha wave, however.
A very good time to avoid the necessity of visiting hospital at the moment, but you don't really have much choice as to when you're likely to have a heart attack or stroke.
Hospitalisation rates now at the level from the SAGE forecasts before Christmas (which were dismissed by the usual suspects) and we still haven't had the Christmas mixing cases hit these rates yet.
Thankfully, it seems that we've been lucky in that the numbers of cases of pneumonia are greatly reduced in comparison to previous variants and we'll hopefully not see any great increase as it spreads into older age groups. The sheer number of cases is likely to make things very ropey, however. Even if cases are less severe, hospital stays are shorter and so on, the sheer numbers who will need to be admitted for treatment and the staff absences expected means it will be incredibly difficult for the health service to cope.
I read an interesting thread from Chris Hopson (don't have the link to hand) which explained what the Nightingale hubs (i.e. big tents in hospital car parks) are going to be used for. Fundamentally, they will be there to house patients who are recovering and awaiting discharge. Those more seriously ill will still be treated in the hospital, but even with emergency staffing levels it will be touch and go. At least, that's the plan. Unfortunately, it is likely the pressure on staff and resources will lead to a lot of unnecessary deaths, many not caused by Covid, due to an unavoidable drop in standard of care. Should still be way below the numbers seen during the Alpha wave, however.
A very good time to avoid the necessity of visiting hospital at the moment, but you don't really have much choice as to when you're likely to have a heart attack or stroke.
Can anyone point me to a proper study showing how effective masks are?
To me it is ridiculous to expect that it does anything at all if you stay in the same room (office, classroom, church, home, etc) with a spreader for half a work day or longer ...
COVID is airborne and much smaller than any cloth mask can filter, even proper filter won't help as you are breathing about 80% of volume around the edges which are not sealed.
Please prove me wrong.
To me it is ridiculous to expect that it does anything at all if you stay in the same room (office, classroom, church, home, etc) with a spreader for half a work day or longer ...
COVID is airborne and much smaller than any cloth mask can filter, even proper filter won't help as you are breathing about 80% of volume around the edges which are not sealed.
Please prove me wrong.
I think they have done quite a few mask studies and they've found that mask use (cloth mask) is most effective in reducing the spray of the virus. It's not that useful in stopping the virus.
In layman terms, you wearing pants doesn't stop you from getting peed on. But it stops you from peeing on other people if you decide to wear pants while peeing. Keeping that spray contained to within a foot of your body, provided you are outdoors is a useful thing. If you are indoors and stuck with the subject for a prolonged period of time, it will get you unless you have a way to filter the virus out.
But when it comes to statistics around mask usage, there is performance (which is what you are asking) and then there is performance for a large population (how effectively does cloth mask wearing reduce the spread for a large scale population). Usually they make suggestions based on the latter and not the former. The former clearly has 0 ability to filter. The latter is statistically better than not wearing it. The obvious answer is for the population to all be wearing n95 masks etc, but it's way too costly.
DuckThor Evil
Legend
Masks are basically useless, there are only very weak studies supporting their usage and the actual infection curves and waves among regions of the earth pretty much tell that those things are totally useless. Just a safety blanket for people and weak insurance policy for the decision makers. If the masks weren't useless before they certainly are against the Omicron variant. Thankfully that's a great thing, as this less harmful variant will breeze past the population with minimal casualties and perhaps then people will finally calm the F down. Just gotta dodge this thing for a week or so to get a negative test result and fly to Thailand and hope people act somewhat normally over there.
Wrong it's not just the virus it has to be imbedded in a medium eg: a water droplet, If the weave of the mask was the same scale as a goal net
the the water droplet would be a block 3 vw golfs across, 3 golf's deep and 3 golf's high ie: 9 golfs
So how many deaths is the price of you not being annoyed ?
DuckThor Evil
Legend
Considering that Earth's population has increased with more than 150M people since the start of this pandemic lite, I guess we can lose a few more.