What do we learn from comparing the response and experience of different countries to Covid? Nothing useful I would argue.

Perhaps when it’s all over we can start comparing and asking who made the best decisions, but this is not over; we aren’t even at half time.

Which countries’ leaders have made the best decisions? We can’t say yet. They were all groping in the dark and made their decisions based on poor information. How each country fares in the long run (as measured in total deaths per million) may have very little to do with the decisions their leaders made, but you can be sure that the ones who struck it lucky will claim that the end results were because of their decisions.

It’s a fact that political leaders always try to connect something they did to any good outcome. They tell the news that ‘this happened because I did this’, and the media then helpfully passes that onto the voter.

We have a problem with a poor understanding of the nature of the disease, its pathology, and its transmission, and as a result we have modelling that is very far from reliable, and practically useless. For instance, comparing Covid 19 to the 1918 flu epidemic (as a recent article in the medical journal JAMA reported) is just hard to justify, seeing as the relative mortality rates are 3% and less than 0.1% respectively (using the experience of Belgium). And that’s just one parameter.

So how should you compare the performance of different countries when every country has different conditions? In comparing responses and results between countries, the following factors must be considered

  • The demographic profile of the country: The median age of African countries is between 16 and 18. In most European countries and Japan this figure in the 40s. We know that Covid-19 strikes the elderly particularly hard, and left teenagers and children relatively unscathed.
  • What is the living arrangement of the elderly?: Do generations of families live together such as they do in Italy, or do the elderly generally live on their own or in nursing homes?
  • Vitamin D exposure: Are vitamin supplements regularly taken in the population? Do the residents of the Mumbai slums take vitamin supplements, or are they getting enough sunlight so that they don’t need it? Generally speaking slums are very poorly lit and often inhabitants suffer from vitamin D deficiency. We have also seen that black people in the Northern Hemisphere (who have higher levels of melanin) are more susceptible to Covid than their white fellow citizens. Is this because they are not getting Vitamin D?
  • What is the % black population in the country? Black people seem to have a 4 times higher death rate in the USA for instance. Yet, as recently noted, African countries seem to be spared the worst effects, at least to date.
  • Medical treatments: What is the prevalence of the use of the tri-combination of hydroxychloroquine azithromycin and zinc? Have all three been used together; have they administered it early or late in the treatment; or at all?
  • Are people social distancing?  One hugely interesting revelation in the past few weeks is that of the experience of those living in the congested slums of Mumbai in India. Antibody testing carried out in July suggested that more than half of the 6 million people living in the densely populated slum areas had been exposed to Covid-19 – yet showed little or no symptoms, resulting in a low fatality rate in these areas – one in 1,000 to one in 2,000 according to a BBC report

The survey has led to medical professionals in the region exploring the possibility that the city has achieved herd immunity. Did the lack of social distancing help build herd immunity? Did a young demographic in the slums help with that? These are all questions that need to be looked at in the context of the experience of each country.

  • Does the country have a culture of following rules? Sweden, who decided to minimise the disruption to their economy and society by chasing herd immunity, seems to have a trusting and compliant population who followed voluntary guidelines.
  • Do the citizens wear masks? How the prevalence of mask-wearing monitored?
  • The Island status of the country. If isolation is the primary tactic of shutdown, then the island status of a country would seem to be very important.
  • Is the country an international hub for travel?
  • What rights have citizens to privacy? That seems to be zero in China for instance where leaked videos showed work teams welding the doors shut on the apartments of infected people.
  • How good is contract tracing? Great in some countries, but not so great in the USA where doctors were told to stop asking people their contact history in blue states after the BLM riots.
  • Population densities. Belgium and New York have high population densities and they both suffered early spikes in cases and deaths (though it looks from the present data that they may both may have reached herd immunity)

If an analysis can’t take account of these factors (which is by no means a complete list) is it any good at all?

This has naturally led to public confusion when selective graphs and reports are used to bolster entirely opposite arguments on everything from mask-wearing to lifting the lockdown.

The mainstream media and political establishment will argue in their own interest of course, and claim they are playing a blinder, but what we have learned so far is that the predictive models can be hopelessly inadequate, and the data is often untrustworthy.

To use the sporting metaphor; the game is far from over, and today’s heroes might be tomorrow’s villains. Sweden might be the big winners and New Zealand might be the biggest losers when we look back on the Covid experience. Time will tell.

 


 

Lorcán Mac Mathúna