- Thu Jul 09, 2020 6:20 am
#126351
At a time when rational interpretation of the Covid data indicates that we should be getting back to normal, we instead see an elaboration of arbitrary responses. These are invariably explained as being ‘guided by science’. In fact, they are doing something rather different: being guided by models, bad data and subjective opinion. Some of those claiming to be ‘following the science’ seem not to understand the meaning of the word.
Its fatality rate was estimated by the World Health Organisation at 3.4 per cent. Then from various sources, we heard 0.9 per cent, followed by 0.6 per cent. It could yet settle closer to 0.1 per cent — similar to seasonal flu — once we get a better understanding of milder, undetected cases and how many deaths it actually caused (rather than deaths where the virus was present).
In medical science there is a well-known classification of data quality known as ‘the hierarchy of evidence’. This seven-level system gives an idea of how much weight can be placed on any given study or recommendation. Near the top, at Level 2, we find randomised controlled trials (RCTs) where a new approach is tried on a group of patients and compared with (for example) a placebo. The results of such studies are pretty reliable, with little room for bias to creep in. A systematic review of several RCTs is the highest, most reliable form of medical evidence: Level 1.
Further down (Levels 5 and 6) comes evidence from much less compelling, descriptive-only studies looking for a pattern, without using controls. This is where we find virtually all evidence pertaining to Covid-19 policy: lockdown, social distancing, face masks, quarantine, R-numbers, second waves, you name it. And — to speed things up — most Covid research was not peer- reviewed.
Such is the quality of decision-making in the process generating our lockdown narrative. An early maintained but exaggerated belief in the lethality of the virus reinforced by modelling that was almost data-free, then amplified by further modelling with no proven predictive value. All summed up by recommendations from a committee based on qualitative data that hasn’t even been peer-reviewed.
Its fatality rate was estimated by the World Health Organisation at 3.4 per cent. Then from various sources, we heard 0.9 per cent, followed by 0.6 per cent. It could yet settle closer to 0.1 per cent — similar to seasonal flu — once we get a better understanding of milder, undetected cases and how many deaths it actually caused (rather than deaths where the virus was present).
In medical science there is a well-known classification of data quality known as ‘the hierarchy of evidence’. This seven-level system gives an idea of how much weight can be placed on any given study or recommendation. Near the top, at Level 2, we find randomised controlled trials (RCTs) where a new approach is tried on a group of patients and compared with (for example) a placebo. The results of such studies are pretty reliable, with little room for bias to creep in. A systematic review of several RCTs is the highest, most reliable form of medical evidence: Level 1.
Further down (Levels 5 and 6) comes evidence from much less compelling, descriptive-only studies looking for a pattern, without using controls. This is where we find virtually all evidence pertaining to Covid-19 policy: lockdown, social distancing, face masks, quarantine, R-numbers, second waves, you name it. And — to speed things up — most Covid research was not peer- reviewed.
Such is the quality of decision-making in the process generating our lockdown narrative. An early maintained but exaggerated belief in the lethality of the virus reinforced by modelling that was almost data-free, then amplified by further modelling with no proven predictive value. All summed up by recommendations from a committee based on qualitative data that hasn’t even been peer-reviewed.