The tables in this report are quite hard to read due to bad labeling. First of all, what are we measuring? From the beginning of 1.1 Data, it seems to be “ PCR-confirmed SARS-CoV-2 cases in...
The tables in this report are quite hard to read due to bad labeling.
First of all, what are we measuring? From the beginning of 1.1 Data, it seems to be “ PCR-confirmed SARS-CoV-2 cases in England with no history of recent international travel.” The cutoff date is December 11, which is quite a long time ago at this point; this report has fairly old data.
There are two columns labeled S+ and S-. These are, roughly, “probably Delta” and “probably Omicron”. (This is using a test where the S component happens to be positive for Delta and negative for Omicron.)
There are two columns in table 1 for OR and log(OR) and you just have to know that “OR” means “odds ratio.” The next thing to figure out is: odds ratio of what? What are we comparing?
The next clue is that some columns have a log(OR) of 0 and OR of 1. That’s one side of the odds ratio and the rows below it are the other side that’s being compared. For example, comparing female to male, they arbitrarily choose female to be 1 and then male is 1.04. This tells us that males who get COVID are slightly more likely to have Omicron than Delta, relative to females who get COVID. (And yeah, no provision for other genders here.)
The columns in red are “statistically significant” and in black are not. This is a measure of whether they collected enough data for the odds ratio to be meaningful. The ones with OR of 1 are black because they’re being used as a baseline.
So, looking at hospitalizations, there have been 24 hospitalizations for “probably Omicron” and 1392 for “probably Delta”. They use “not hospitalized” as the baseline and the odds ratio is 0.95, but the range is (.61 to 1.47). This row is black, meaning “not significant.” A ratio of 1 would mean same severity as Delta, and what this is saying is that there is not enough data to tell.
Furthermore they warn that even if the odds ratio were significant, there are other reasons to think it wouldn’t be reliable:
“The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, with 18-29 year-olds, the London region, and those of African ethnicity having significantly higher rates of infection with Omicron relative to Delta. Hence the crude ratios of hospitalisations to cases shown give no information on severity on their own since risk of hospitalisation increases markedly with age.”
So, basically not enough data here to say much about severity. They summarize this by saying “Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta.”
It seems to me that the data says “no evidence either way” (there is a wide range of possibilities) but they are going beyond that to imply that if Omicron were more mild then they shouldn’t have seen 24 hospitalizations by December 11. But since the data is old we should probably look at newer data.
Unfortunately the media is bad at rounding towards uncertainty and they often rounded this off to “just as severe.”
There is a chart here for London hospital admissions. Looks like it’s about doubled. For England there’s a much less dramatic rise. Further down the page is “Patients is hospital.” This page has...
There is a chart here for London hospital admissions. Looks like it’s about doubled. For England there’s a much less dramatic rise. Further down the page is “Patients is hospital.”
This page has the latest Omicron stats for the UK, up to December 18. 129 hospitalizations and 14 deaths.
Figure 1 shows prevalence for different regions. SGTF means “not Delta, presumably Omicron” and London is at 90% (line, right axis). Figure 2 indicates that the UK as a whole is at about 70%
Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta.
and
Omicron was associated with a 5.41 (95% CI: 4.87-6.00) fold higher risk of reinfection compared with Delta. This suggests relatively low remaining levels of immunity from prior infection.
I don’t know why people keep highlighting that bit about hospitalizations because this report doesn’t have very much to say about them. (See my other post.) But yes, getting vaccinated and in...
I don’t know why people keep highlighting that bit about hospitalizations because this report doesn’t have very much to say about them. (See my other post.)
But yes, getting vaccinated and in particular getting a booster if possible is a good idea.
Quote from https://www.reuters.com/business/healthcare-pharmaceuticals/omicron-infections-appear-no-less-severe-than-delta-covid-19-lowers-sperm-count-2021-12-20/ which talks about the linked study.
Researchers at Imperial College London compared 11,329 people with confirmed or likely Omicron infections with nearly 200,000 people infected with other variants. So far, according to a report issued ahead of peer review and updated on Monday, they see "no evidence of Omicron having lower severity than Delta, judged by either the proportion of people testing positive who report symptoms, or by the proportion of cases seeking hospital care after infection."
The same team of researchers at Imperial College have put out a new report: Some reduction in hospitalisation for Omicron v Delta in England: early analysis
The same team of researchers at Imperial College have put out a new report:
Estimates suggest Omicron cases are 15% less likely to attend hospital, and 40% less likely to be hospitalised for a night or more, compared to Delta.
The researchers stress that these estimated reductions in severity must be balanced against the larger risk of infection with Omicron, due to the reduction in protection provided by both vaccination and natural infection. For example, at a population level, large numbers of infections could still lead to large numbers of hospitalisations. They say the estimates provided in this paper will assist in refining mathematical models of potential healthcare demand associated with the unfolding European Omicron wave.
The tables in this report are quite hard to read due to bad labeling.
First of all, what are we measuring? From the beginning of 1.1 Data, it seems to be “ PCR-confirmed SARS-CoV-2 cases in England with no history of recent international travel.” The cutoff date is December 11, which is quite a long time ago at this point; this report has fairly old data.
There are two columns labeled S+ and S-. These are, roughly, “probably Delta” and “probably Omicron”. (This is using a test where the S component happens to be positive for Delta and negative for Omicron.)
There are two columns in table 1 for OR and log(OR) and you just have to know that “OR” means “odds ratio.” The next thing to figure out is: odds ratio of what? What are we comparing?
The next clue is that some columns have a log(OR) of 0 and OR of 1. That’s one side of the odds ratio and the rows below it are the other side that’s being compared. For example, comparing female to male, they arbitrarily choose female to be 1 and then male is 1.04. This tells us that males who get COVID are slightly more likely to have Omicron than Delta, relative to females who get COVID. (And yeah, no provision for other genders here.)
The columns in red are “statistically significant” and in black are not. This is a measure of whether they collected enough data for the odds ratio to be meaningful. The ones with OR of 1 are black because they’re being used as a baseline.
So, looking at hospitalizations, there have been 24 hospitalizations for “probably Omicron” and 1392 for “probably Delta”. They use “not hospitalized” as the baseline and the odds ratio is 0.95, but the range is (.61 to 1.47). This row is black, meaning “not significant.” A ratio of 1 would mean same severity as Delta, and what this is saying is that there is not enough data to tell.
Furthermore they warn that even if the odds ratio were significant, there are other reasons to think it wouldn’t be reliable:
“The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, with 18-29 year-olds, the London region, and those of African ethnicity having significantly higher rates of infection with Omicron relative to Delta. Hence the crude ratios of hospitalisations to cases shown give no information on severity on their own since risk of hospitalisation increases markedly with age.”
So, basically not enough data here to say much about severity. They summarize this by saying “Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta.”
It seems to me that the data says “no evidence either way” (there is a wide range of possibilities) but they are going beyond that to imply that if Omicron were more mild then they shouldn’t have seen 24 hospitalizations by December 11. But since the data is old we should probably look at newer data.
Unfortunately the media is bad at rounding towards uncertainty and they often rounded this off to “just as severe.”
There is a chart here for London hospital admissions. Looks like it’s about doubled. For England there’s a much less dramatic rise. Further down the page is “Patients is hospital.”
This page has the latest Omicron stats for the UK, up to December 18. 129 hospitalizations and 14 deaths.
Figure 1 shows prevalence for different regions. SGTF means “not Delta, presumably Omicron” and London is at 90% (line, right axis). Figure 2 indicates that the UK as a whole is at about 70%
The highlights:
and
TL;DR: Get vaccinated.
I don’t know why people keep highlighting that bit about hospitalizations because this report doesn’t have very much to say about them. (See my other post.)
But yes, getting vaccinated and in particular getting a booster if possible is a good idea.
That's an excellent point. Thank you for digging further into the statistics.
Quote from https://www.reuters.com/business/healthcare-pharmaceuticals/omicron-infections-appear-no-less-severe-than-delta-covid-19-lowers-sperm-count-2021-12-20/ which talks about the linked study.
The same team of researchers at Imperial College have put out a new report:
Some reduction in hospitalisation for Omicron v Delta in England: early analysis