Summary: In this post I point out examples from around the world that challenge the Susceptible-Infected-Recovered model used by governments around the world.
In my last post I said I’d provide evidence for the superspreader theory applied to covid.
To start my analysis I’ll choose one country with very low levels of covid infections — this is to try to isolate individual covid waves. Countries with endemic covid infections have more complex wave structures, and I’ll return to them later.
So, on to the wonderful country of New Zealand. Here’s a graph of infections in New Zealand since the start of 2020:
In that graph you can clearly see three mini covid waves. The one on the left is from spring 2020 and the biocontrol measures in New Zealand appear to have suppressed it fully. What I’m mainly interested in is the two mini-waves on the right. The progress of the two waves is very odd, and not at all compatible with the SIR model of covid infection, where each infected person infects a few others until the supply of susceptible people runs out. It is clear that the first wave dies out, as though there were no people left to infect, but then comes back almost as soon as the first wave looks as though it is stopping — it is clear that there were definitely more people left to infect. The delay from the peak of that mini-wave to the start of the main early winter wave appear to be approximately 35 days, and the time between the two peaks appears to be approximately 75 days.
Of course, it might be that the two waves were actually located in different parts of the country — but analysis of news reports from that time shows that both were in the vicinity of south Auckland.
So, we’ve got some interesting data in New Zealand, but is the same thing seen anywhere else? To start with, I’ll go to the next best place for low covid infections, Australia. Now, Australia is a very large country, so we’ll deal with it at state level — how about Victoria?
In the above figure I’ve plotted in the main chart cases in Victoria since the start of 2020, but zoomed in on the yellow shaded area in the inset graph. And there it is — a small spike in cases for a few weeks in mid to late July, with the main wave following about 6 weeks after that first peak, with peaks separated by approximately 77 days. Note the very small numbers in that initial mini-wave — is that the signature of a single superspreader? If it is, I note that there are approximately 200 cases in that initial mini-wave — is that the number that each superspreader typically infects?
Also of note in the data for Victoria is the two waves in 2020 — an initial smaller wave in spring, followed by a larger wave in summer. That initial wave had approximately 1,000 cases, the larger wave approximately 20,000 cases, and the two waves were separated by approximately 12 weeks. Was this 2020 twin peaks of covid also related to superspreaders, only with a longer period between the two waves?
Let’s see if we can find evidence elsewhere. What about Singapore?
There we have the same signal — a short spike in cases amounting to about a thousand in total which dies back before the main spike in cases arrives about 5 weeks later and with peaks separated by approximately 100 days. Once again, it is important to note that the standard disease model (SIR) can’t explain this mini wave before the main wave — if the situation was right for the infectious wave to start it would have done so, because it did exactly that only a few weeks later.
Also note the two waves in spring 2020 — their peaks are separated by approximately 95 days.
So far we’ve considered small isolated countries/states, either because they’re islands or because of sheer distances (Victoria, Australia). What about a more complex example, perhaps Croatia?
It looks like we see a series of smaller waves when covid came to Croatia in summer 2020, with an initial covid mini-wave of around 3,000 cases, a second mini-wave of around 10,000 cases starting approximately 4 weeks after the peak of the first, and then the third, major wave starting approximately 5 weeks after the peak of the second mini-wave.
Let’s put some of these timings on the graph — here we’re including days between each peak of the covid epidemic waves in Croatia:
First that initial wave in spring 2020; this appears at first glance to be an aborted wave, but its small size almost certainly reflects very low covid test capacity at the start of the covid pandemic and the true number of cases at this point in time was probably larger.
From summer 2020 we have a series of four waves, with the third and fourth overlapping slightly, and with between 44 and 55 days between each peak. Then a gap of 126 days to the next peak, then 155 days. Finally, there is an overlapping double peak in autumn/winter 2021 with peaks separated by about 53 days.
What about the UK?
Now we can start to see the pattern. A series of covid waves either separated by 40-80 days, or by a longer period of over 100 days.
Again, note that the spring 2020 wave is only small in size compared with the others because of limited test capability at that time. It would be useful if we could see this wave in more detail — ah, but we can! Remember we found a signal for this in the ambulance ‘cardiac and respiratory arrest’ data about a month ago:
Here I’ve highlighted the December 2019 signal in the data that we identified in the post last month — the peak of this wave occurred about 100 days before the peak of the main spring 2020 covid wave.
That’s rather a lot of data, and certainly enough for one day. I’ll finish for today with a summary and a prediction.
The standard model used for predicting covid waves around the world is SIR, that is individuals are susceptible, become infected and go on to infect others, and then become recovered and are resistant to reinfection (at least for some time). This SIR model cannot describe the wave features I had described in this document.
Instead, covid appears to intrinsically come in waves, with some waves feeding a new wave soon after (often around 40-80 days) and perhaps with each wave merging to some extent. Other times the delay between waves is much larger, with relatively low case numbers between each wave.
What’s more, covid has other aspects that are difficult to square with SIR theory, such as relatively low household transmission rates and the lack of evidence from human challenge trials.
One mechanism that could create this effect is via a relatively low number of people that are responsible for spreading the disease — the superspreaders:
Each covid wave starts with some of these individuals becoming activated; these then are responsible for the the vast majority of new cases.
Superspreaders remain active for a period of time, possibly around 2-3 weeks. It is important to note that this is a longer infectious period than assumed in the SIR model, which tends to be for only 4-7 days duration.
Each covid wave is formed by multiple superspreaders becoming activated — their activation period doesn’t align completely, resulting in covid waves of around 8 weeks in duration, with some potential for overlapping waves.
While there is some onwards transmission from non-superspreaders, this is relatively rare.
Superspreaders are created during a covid wave, but they do not become activated at the point of infection. Instead, they remain dormant for some time, usually between 40 and 80 days.
Once the supply of superspreaders has become exhausted the wave sequence ends.
Covid waves return when new superspreaders become available.
In my next post I’ll describe the immunological supporting evidence.
Finally, a theory is no good without a prediction — anyone can describe the past… I think New Zealand hasn’t finished a set of short-interval waves. The peak of the second wave was 75 days after the peak of the first; I predict a new wave is imminent, with a peak 50-75 days after the second peak — that is, around mid to late January. In order to peak by that time this predicted new wave will need to start in the next 10 days or so.
Very interesting analysis. I live in New Zealand. Our government enforces a brutal border restriction that sees New Zealand citizens forced to compete in a lottery in order to be able to re-enter their country. Our passports are better used for wine glass mats, because using them to enter New Zealand is practically impossible. Our government also controls all testing, all data, and all press coverage.
Very interesting, thanks for explaining it in this way. It'll be interesting to see if you're right about new zealand! 😄👍🏼 I wonder what makes someone a super spreader? It seems like some people are immune to covid. Super spreaders obviously have to incubate the virus, and they have to be social enough to contact various people.