COVID-19 is a very serious problem that should be taken very seriously by both government and the public, but there are ways in which we may be getting an inflated sense of the threat.
This story is an updated version of an article that was originally published on Foreign Policy Follies on March 23.
- Confirmation Bias: In general: Once a dominant narrative is formed (in this case: Covid-19 as huge threat) reporting will be more inclined to cover things that fit that narrative & ignore/dismiss things that seem to contradict it: The evidentiary standards for reporting that fits the narrative will be lower than for reporting that contradicts it.
- Expectations instead of Facts: Reporting focuses on *expected* problems rather than currently existing problems: Most hospital capacity reporting is about expected problems.
- Making the Normal Exceptional: Ordinary events are now portrayed as evidence for the threat, eg:a) Many hospitals run at near capacity in normal times and will routinely be over capacity but now this problem may be attributed to COVID-19. b) Rare cases (eg of young people suddenly getting violently ill & dying from COVID-19) that in normal times don’t make it into the newspaper (such rare deaths also happen with eg the flu and other viruses) now make the front page & are portrayed as more common than they are.
- Confusing Increase in Testing for Increase in Cases: A large increase in the number of cases sounds scary but becomes much less so when this is because of an increase in the number of tests rather than an increase in the number of cases.
- Other Causes: Death rates can seem very high when everybody who died from other causes but also had COVID-19 is counted as a COVID-19 death. And shockingly, counting people who tested positive for COVID-19 but who clearly died of other causes as ‘COVID-19 deaths’ is now routine practice.
- Flu or COVID? If people who died are tested for COVID-19 but not for the flu or the common cold, these deaths may be counted as COVID-19 deaths even though they could have also tested positive for eg the flu. The symptoms of the flu and of COVID-19 are pretty similar, so it could have been the flu, not COVID-19, that killed the person (or neither), but their deaths will now be attributed to COVID-19.
- No Positive Test Necessary: It is not uncommon for deaths to be classified as COVID-19 deaths even in the absence of a positive COVID-19 death. In the US and UK it is now accepted practice to count a death as a COVID-19 death even if there is no positive test result as long as the doctor makes a subjective judgment that it likely was COVID-19 that caused the death. There is a lot of room for subjectivity in that determination.
- Not Putting into Perspective: The extent of the COVID-19 problem is not put into context by comparing it to other problems. So while e.g. 500 COVID-19 deaths may sound very scary, if in that same period 10,000 people died from the flu it may seem less so.
- Exponential Growth: Exponential growth rates are assumed to continue at that rate instead of quickly levelling off.
- Bad Models: An excessive reliance on models that are only as good as their assumptions.
- Bad Prophets: Relying on experts whose past pandemic predictions were way off.
- Circular Reasoning: Governments taking enormously far reaching steps to fight the problem give rise to a “Well, they wouldn’t be taking such extreme measures if the threat wasn’t that grave” attitude.
- Ignoring Success Elsewhere: Other countries — such as South Korea, Taiwan, Sweden, Japan and Singapore — appear to have been quite successful in containing the pandemic without resorting to the kinds of draconian measures we see Western governments taking, so maybe the threat wasn’t as great as often portrayed.
- Financial Incentives: Some hospitals get paid more if patients are listed as COVID-19 and on ventilators, which creates incentives that on the margin may tend to lead doctors to categorize more patients as COVID-19 patients and put them on ventilators.
Note: There is also undercounting going on: For example, if people die at home of Covid they may never have been tested and doctors may not attribute these patients’ deaths to Covid.
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