Covid-19: What you need to know today

Is the coronavirus disease seasonal? I remember suggesting earlier this year that it may be and that the Indian summer would prove the country’s most powerful weapon against the virus — I was wrong, of course — but it’s a question I was reminded of when, in response to a discussion on Twitter about Europe’s ongoing and India’s imminent second wave, a doctor mentioned the Hope-Simpson curve.

Robert Edgar Hope-Simpson — his father served in India till 1916 and he was born in 1908, so it is likely there’s an India connection there, although I can’t find any documentation of it — is the author of a book called The Transmission of Epidemic Influenza, published in 1992 after nearly six decades spent studying the disease. The book builds on an earlier paper by him in the Journal of Hygiene in 1981, The Role of Season in the Epidemiology of Influenza. Hope-Simpson was convinced that human or community transmission alone couldn’t explain the trajectory of influenza infections.

He was able to show, using years of data, that there was a correlation between influenza and season. He initially put this down to an unknown seasonal variable but later narrowed down on the identify of the variable — Vitamin D.

Covid-19 isn’t influenza — indeed, the two viruses aren’t even from the same family — but for some time earlier this year, it definitely looked as if the pandemic’s trajectory was following the famous Hope-Simpson curve — “a sinuous curve that runs parallel to the midsummer curve of vertical solar radiation, but lags about six months behind it”. (This is from the 1981 paper).

It is likely some of you have seen the same posts I have online — showing a perfect match between the coronavirus pandemic’s trajectory in some countries from the northern hemisphere, others from the southern hemisphere and their respective Hope-Simpson curves. Some experts even used this to criticise lockdowns — these didn’t matter, was the argument; season was the primary driving force behind infections.

But Covid-19 has been unpredictable. Sure, its trajectory in some countries matched Hope-Simpson’s sinusoidal curve, but that in some other countries did not.

India is a case in point. Infections in the country rose through the summer months. As in the US. Infections there rose through late winter, dipped a bit in spring, then gathered momentum again in one part of summer before dipping again in another, and are now rising again through autumn. Both India and the US are in the northern hemisphere.

But across most European countries (all in the northern hemisphere), the fall in cases coincided with the coming of warmer weather, and the current rise comes even as winter sets in.

And in South Africa, Argentina and Chile (all three countries in the southern hemisphere), Covid-19 did peak in the winter months.

It is likely that there are other factors at play as well.

One factor could be size and population, given that the two countries that are both exhibits in the case against seasonality (India and the US) are both large and populous, and many that are exhibits in the case for, (European countries) are neither large nor populous.

The Covid-19 numbers of Brazil (another large country and third in overall number of cases after the US and India) presents a challenge, although cases there did peak during the colder months.

Another factor could be exposure to other viruses, and lower levels of hygiene — things that some experts believe can explain Africa’s numbers (and perhaps that of some Indian states). Countries on the continent (with the exception of South Africa) have surprisingly few cases, and not many deaths.

I believe it is too soon to decide one way or the other. It’s possible that seasonality emerges as one factor driving Covid-19 infections, but this is something that can be established after years (perhaps even decades) of study. Remember Hope-Simpson and his obsession with influenza for decades.

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