[搬运工]伦敦报告
第50期报告：英格兰Omicron变异株入院风险分析
https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2021-12-22-COVID19-Report-50.pdf
on the Imperial study on omicron severity, TL;DR:
-*intrinsic* omicron severity similar/bit lower to delta;
-*observed* severity lower due to omicron more likely to re-infect;
-vaccine efficacy against hosps maintained;
-growth rate likely to override impact of lower severity.
关于帝国理工学院这份Omicron变异株毒力预测报告，太长不看版总结：
- Omicron*内生的重症风险*和Delta相当，或略低一丢丢；
- Omicron*实际观测到的重症风险*比Delta低，原因是Omicron更有可能导致重复感染；
- 疫苗防入院的有效性勉强还在；
- Omicron高增长率带来的冲击有可能抵消重症风险比的差距。
Before I get into the rest, I want to re-emphasise that the overall impact of omicron will be determined by growth (exponential) and severity (linear) - even with lower severity, growth in itself will cause serious impact at population level, even if severity is moderately lower.
The Imperial study is a complex piece of analysis, and I have to commend the Imperial team for dealing with important confounders in the analysis.
I want to first separate out *intrinsic severity* of omicron relative to delta from *observed severity*. This distinction is important - because it separates the instrinsic properties of the virus from differences in severity because of who it infects.
By intrinsic severity, I mean if omicron was introduced into the same people as delta, what would the relative severity be?
By observed severity, I mean what is the observed (real-world) severity of omicron infections relative to delta infections?
在开始正式八卦之前，
我想再次强调一点：
Omicron对我们造成的影响，
主要取决于两个因素，
即感染人数增长率（呈指数增减）和重症风险比（呈线性增减）。
所以就算Omicron的重症风险比真的显著降低，
在人群层面上，
指数增长的感染人数也足以对我们造成严重冲击。
帝国理工学院这份报告太难搞，
所以咱翻译成人话的时候还不得不跟他们勾兑过，
确认了没搞错他们的言下之意。
另外还要明晰两个概念，
也就是所谓Omicron相对于Delta的“内生的重症风险比”和“实际观测的重症风险比”。
这两者的区别很重要，
前者是病毒的固有属性，
而后者则由被感染对象决定。
“内生的重症风险比”可以理解为，
假设Omicron和Delta感染同一个病例，
哪种的重症风险更高？
而“实际观测的重症风险比”则指的是，
我们在真实世界直接观察到的Omicron和Delta导致重症的风险差别。
What determines the severity of an infection?
- age - gender - ethnicity - socio-economic status (proxy for several other factors) - past infection - vaccination
So differences in severity between variants can be down to: - differences in ages/genders of those infected - differences in demographic factors (e.g. region/deprivation) - differences in vaccination status - previous infection status
This is vitally important to consider when comparing omicron to delta because delta & omicron infections are occurring in different groups.
e.g. For omicron 13% of cases have had previous infection >90 days ago (so are defined as re-infections),
compared to only 2.5% for delta.
This is of course consistent with significant immune escape of omicron relative to delta, which is clearly contributing to its advantage in growth over delta. But of course previous infection may also provide protection against severe disease reducing *observed severity*.
This is very likely at least a major part of the reason why the current wave in SA seems to be associated with a much lower hospitalisation rate than the 3rd wave - because many people were infected in the 3rd wave and much larger population had been exposed to infection before.
决定感染严重程度的风险因素包括：
- 年龄
- 性别
- 种族
- 社会经济地位（以及背后的其他多种因素）
- 既往感染史
- 疫苗接种史
因此，衡量不同变异株之间重症风险比需要考虑到：
- 病例的年龄/性别差异
- 病例的其他背景差异（所在地区、是否贫困等）
- 接种状态差异
- 以及，既往感染史的差异
以上因素在对比评估Omicron和Delta重症风险时显得尤为重要，
因为这两种变异株的感染对象差别非常大。
比如Omicron的感染者中有13%在90天之前发生过既往感染，
（也就是重复感染比例高达13%）
而对于Delta而言，这个比例只有2.5%。
以上重复感染比例的差别，
一方面与omicron相对于delta显著的免疫逃逸优势相吻合，
并且也显然有助于Omicron的增长率方面超过delta，
但同时，既往感染本身可以提供预防重症方面的保护力，
也就是*实际观测的重症风险*。
这一点，很可能是目前南非这波爆发的住院率显得比第三波更低的主要原因。
很多人在第三波时都被感染过，
还有更多的人在更早的几波被感染过。
The problem is we don't really have good data on previous infections. The total infections that have occurred are likely several times higher than those reported. Pillar 2 (community tests) show only 17% of the population was infected so far. True infection is likely much higher.
The analysis essentially compared hospitalisation risk between omicron and delta among people who tested PCR positive between 1st and 14th December 2021 - comparing hospitalisation rates between SGTF -ve (good proxy for omicron) and SGTF +ve (good proxy for delta cases).
It adjusted for age, sex, ethnicity, region & specimen date, and presented the risk of hospitalisation for omicron *relative to* delta by vaccination status, to try and understand *intrinsic severity* of omicron relative to delta, the authors tried to account for past infection as well. This is because past infection would make a big difference to estimates, given that omicron is associated with much higher re-infection that delta.
The problem as stated before in re-infection is likely hugely underestimated, simply because first infections are hugely underestimated (because only a small proportion test, and are reported overall). They assumed that only 1/3rd of all re-infections had been identified.
问题在于，
关于既往感染，
我们没有靠谱的数据。
我们推测，之前的感染总数可能比字面上的感染总数高出好几倍。
比如Ferguson老师报告里的“Pillar 2”一栏（即“社区检测阳性”）显示，
到目前为止，
英国只有17%的人口有既往感染史。
但真正的感染可能要高得多。
总之，第50期帝国理工学院报告主要比较了2021年12月1日至14日期间，
所有PCR检测呈阳性的人群中，
omicron感染者相对于Delta感染者的住院风险比。
注意他们用的是有没有出现SGTF来区分Omicron和Delta
（当然在当前，这种近似法相对还挺准确）
Ferguson老师的报告针对年龄、性别、种族、地区和PCR检测采样日期进行了调整，
并根据疫苗接种状态分别计算了Omicron感染者相对于Delta感染者的入院风险，
以试图厘清Omicron相对于Delta的 *内生重症风险比*。
Ferguson老师还试图根据既往感染史状态来分开计算以上风险比，
这是因为既往感染史和接种疫苗差不多，
也会显著影响重症预期，
而Omicron涉及的重复感染显然比Delta高很多。
而上面已经提到过，
英国的既往感染数量很有可能被大幅低估了，
（因为在以前，只有小部分人有机会做检测，检测阳性之后也不一定会上报）
Ferguson老师的处理办法是……
直接给既往感染比例乘以三~
With this assumption, they were able to then correct *observed* estimates (which would be affected by level of past infection & immunity) to get a less skewed estimate of *intrinsic severity*. The corrected estimates are more likely to give us an idea of intrinsic severity.
But these do depend on the assumptions made (about the level of underestimation of re-infection), so have to be taken with that caveat. Based on this, 40% of omicron cases were assumed to be re-infections, and ~8% of delta infections (3x observed percentages).
Assuming this, they found that omicron had only very slightly reduced risk of hospitalisation relative to delta -0-30% in different analysis, but protection from hospitalisation for re-infections was ~55-70% for omicron.
基于"既往感染直接翻三倍"的假设，
Ferguson老师他们就能够修正*实际观测的重症风险比*的估算值
（因为这个估算值受到既往感染史带来的免疫保护影响），
因此这个估算值跟*内生重症风险比*估算值的偏差就能缩小。
这样我们可以通过修正后的估算值来了解病毒内生的重症风险。
所以下面我们将看到的数字，
归根结底取决于Ferguson老师他们做出的“翻三倍”的假设。
根据这一假设，Omicron的重复感染比例提升到了差不多40%~
而Delta的重复感染比例也涨到了8%左右。
总之，根据以上假设，
Ferguson老师预测：
Omicron比Delta的内生重症风险略低一丢丢（0%~30%），
而重复感染史这一因素本身则可以降低大概55%~70%的重症风险。
Remember that while this means similar *intrinsic severity*, overall real observed severity is reduced compared to delta simply because omicron has 40% of cases that are re-infections (who are more protected than those that are 1st infection) compared with delta.
When we don't consider underestimation of re-infections then *intrinsic severity* is reduced by 15-20% and reinfection is estimated to be associated with approximately a 50-60% reduction in hospitalisations.
Overall, the findings are not hugely different regardless of assumptions. All suggesting that observed reduction in severity is very likely due to the fact that a much larger proportion of omicron cases are people with prior infection - so greater protection.
So not much difference due to the intrinsic properties of the virus - but rather who it's infecting. Remember the comparisons so far were adjusted for vaccine status, so were only comparing impact *within* compartments of different levels of vaccination, & averaged across these.
Ultimately what matters within the UK is probably going to be *observed severity* right now, because this is a combination of all factors- intrinsic severity of the virus + the protections/severity based on who it's infecting.
But intrinsic properties important to understand to generalise to future scenarios, and also other countries. As the authors say ultimately the impact will be determined by growth and severity.
There are also some indicators that hospitalisations with omicron may potentially be shorter duration compared with delta, but it's difficult to know from the current study as on average follow up of omicron cases was shorter.
Growth is rapid and exponential. And this will easily override even moderate reductions in severity. For a variant half as severe as delta, doubling in 2 days would mean the same level of overall hospitalisations just in 2 days due to the large numbers infected.
Ultimately, the growth rate means, despite moderate reductions in severity, hospitals could still be overwhelmed, and we still need to take urgent action to pre-empt this, while we understand more about this threat.
需要强调，
上述比Delta仅仅略低一丢丢的，
是Omicron的*内生重症风险*，
但与delta相比，我们整体实际观测到的重症风险确实明显降低了。
但这主要是因为，
与Delta相比，
Omicron有40%的病例属于重复感染
（所以病例受到了相对初次感染更多的免疫保护）。
如果我们完全不考虑重复感染比例可能存在的低估现象，
那么Omicron的*内生重症风险*可能还会降低15-20%左右，
或者说相当于重复感染足以降低约50-60%的入院风险。
所以总体而言，无论咱怎么假设，
其实结果都没有太大不同。
Ferguson老师他们的精彩分析表明了，
实际观测的重症风险之所以降低，
归根结底是因为Omicron病例中重复感染的比例更高，
因此有更足量的免疫保护。
因此，两种变异株之间的内生属性其实差别并不大，
差别主要体现在被感染的人群……
归根结底，对于当前英国来说，
最关键的可能是*实际观测的的重症风险*，
因为这是所有风险因素的打包组合：
既包括了病毒的内生重症风险，
也包括了来自被感染对象的变数。
但是病毒的内生属性将来的防疫规划很重要，
并且对其他国家也更有参考价值。
另外，正如Ferguson老师所说，
Omicron造成的冲击，
最终取决于增长率和重症风险两大因素。
病毒传播感染异常迅速，且呈指数级增长。
这一特性很容易完全抵消重症风险方面那一丢丢线性的下滑。
所以，就算Omcron的重症风险只有Delta的一半吧，
Omicron两天翻一倍的倍增时间意味着，
医疗机构被打爆的悲剧只会晚两天上演而已。
最后，正因为Omicron的高增长率，
所以哪怕重症风险比有所降低，
但医疗挤兑还是有可能发生，
所以我们仍然需要采取紧急行动来预防这种悲剧，
并抓紧时间对这种全新变异毒株进一步加深了解。
Gurdasani老师果然牛鼻……
虽然略喜欢说车轱辘话，
（估计是为了照顾平均智商较低的英国读者）
但纯靠文字就把Ferguson老师的专业报告解释的一清二楚。
当然了，Ferguson老师更是牛鼻轰轰，
各位有机会的话不妨去啃原文就能体会了~
最后，不得不感慨两句，
其实哪儿都有明白人~
Gurdasani老师和Ferguson老师都是英国众多明白人的出色代表，
但就算有这么些大佬天天熬夜赶工吧，
英国人民还是要遭重，
并且在之后的一两周遭得更重……
这到底是为了啥呢？
最后，今天的Omicron全球病例走势如下，
——请品鉴：
一共12.5万实锤Omicron病例~
但其实大伙儿都知道，
实际数字可能还要翻个几十倍吧~
以上。