"we were world leading on multiple fronts (with NZ)
1) stopped China flights more or less first
2) stopped South Korea more or less first
3) stopped all incoming flights more or less firsr
4) have best testing regimen for a large country."
For starters, testing merely measures infection; it has no bearing on the rate of infection (especially when 99% of the population is not being tested);
Secondly, I don't think we were all that proactive when it comes to importing infected people. (Heck, the US closed its doors to flights from China in January; we went after that)
And we still had cruise ships offloading merrily until quite recently.
No more is there evidence of this slow response on the imported infection side than the fact that more than half of our infected cases are not locally-transmitted.
And, as I said in my previous post: we were still living normally and socialising in close quarters until quite recently.
"What you don’t seem to get, is that this is both HIGHLy contagious and quite lethal (somewhere between 0.5-2%), and all the places that did not act as quickly or decisively as us have it a lot worse. There is a lot of data (South Korea, Diamond Princess, Australia and Germany) all showing the same numbers , with extensive testing regimens."
You see, it is statements like that that have me asking questions of the data.
How do you know what the real infection rates or the true mortality rates are for any country, given we don't know how many citizens of those countries have actually been infected?
As case in point, the apparent mortality rate (calculated as [Fatalities / (Recoveries + Fatalities]) for Australia, Germany and South Korea are, respectively 4.6%, 4.9% and 2.7%.
But what about the unknown number of people in each of those countries that have been infected, but weren't tested? We are dealing with statistically open systems where the true size of the data set, in terms of total infections, is not known.
If actual infections is five times or ten times higher than the figures reported then the infection rates and mortality rates that we see in the media are wrong (and by definition, overstated) by several orders of magnitude.
The Diamond Princess is an interesting case study because it is the closest example of a closed data set that we have, which has a mortality rate of 1.7% (Fatalities / [Recoveries + Fatalities]).
But there were 3700 passengers on board, some of whom could have been infected and recovered without symptoms, or with merely moderate symptoms. So the mortality rate could easily have been lower than than the 1.7% observed figure.
But even then, this Diamond Princess data is not representative of country populations because it was over-represented in the 60-year and over age cohort.
And even that flies in the face with current WHO stats, which have mortality rates of the over 60s as follows:
>80 years : 14.8%
70-79 years: 8.0%
60.-69 years: 3.6%
Again, because those WHO figures do not capture everyone who has been infected, it stands to reason that the real mortality rates are a lot lower than that.
"I would even argue that Australia is superior to NZ as we have not forced everything to close but are having similar results- ie we have implemented the most effective strategies and not implemented dubious ones."
The New Zealand case serves to reinforce my argument about the trade-off between the misery spared by lockdown and the misery resulting from lockdown.
New Zealand have gone far harder than us, yet its per capita infection rate is on par with ours.
And, importantly, that is despite Australia doing about five times more per capita tests as New Zealand, so adjusted for the extra testing, NZ's per capita infection rate is a lot higher than ours. That's despite, as you pointed out, the extent of NZ's lockdown being more severe than Australia.
As more daily data gets published, the more all is not as it first seemed.
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