We can identify the impact of seasonality on the spread of COVID by producing a correlation matrix between case rates of each state over a certain period. I’ve done this for summer/early autumn 2020 (Figure 1).
As we can see very clearly, Arizona, California, Florida, Georgia, Louisiana, Nevada, South Carolina, and Texas are all negatively correlated with the rest of the country but positively correlated with each other.
Ever since the days of Hope-Simpson
, seasonality has been known to have a significant influence on viral incidence so this should come as a surprise to no-one who hasn’t been duped by the world health authorities attempts to pervert decades of scientific discovery.Strangely, they appear to be completely disinterested in the abject lack of seasonality of COVID during the same period in 2021 (Figure 2).
But to take an interest would also mean you’d have to make an effort to explain such an incredible phenomenon.
If you are curious, I’ve done some analysis which reveals a likely cause* which I’ll share tomorrow.
*No prizes for guessing what it is!
https://en.wikipedia.org/wiki/Robert_Edgar_Hope-Simpson
The most blatant sign of what you're hinting at is Australia, which is having a completely out-of-season spike that wasn't present at all during the first year of the epidemic.
THANK YOU. I have been looking for some kind of formal analysis or visualisation of this. This is a big improvement on shouting 'it's the wrong fucking time of year!' at people, which has been my go-to approach on this point until now. Thank you Joel.