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> I believe your modelling may not be elaborate enough, and that any crude<br>
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<div class="PlainText">home approach is not very meaningful. Are details of the modelling<br>
method of those uni researchers available who advised the government?<br>
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> Your model ending with an infection rate of 97-99% does not seem<br>
plausible to me. Herd immunity should kick in before then.</div>
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Yes, their models are available, and they are vary widely. </div>
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<div class="PlainText">I made no attempt to get the numbers to model specifically NZ society and Covid-19. Instead I am interested in the stability of the modelling - how does changes in the inputs affect the outputs. <span style="font-family: "Segoe UI", "Segoe UI Web (West European)", "Segoe UI", -apple-system, BlinkMacSystemFont, Roboto, "Helvetica Neue", sans-serif;">What
I was really investigating was how plausible are the models.</span>
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It turns out herd immunity is VERY sensitive to the infectious behavior of the disease and society. As I change the probability of one contact passing on an infection from 3% to 20% the number of people protected by herd immunity plummets.<br>
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If this carries over to other models and to real life, you can see why getting the correct value P for Covid-19 could be important, and - given the variations in society and the presentation of the disease, probably impossible. <br>
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P %unexposed when all over</div>
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0.03 99%</div>
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0.06 29%</div>
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0.09 13%</div>
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0.12 7%</div>
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0.15 4%</div>
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0.18 2%</div>
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0.21 1%</div>
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<div class="PlainText">So the answer is - they are not much better than a wild ass guesses, which is why the different models have been making widely different projections, and why the same model being given new data is also making very different projections.<br>
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You might want to follow Carl Bergstrom on Twitter to see some of the discussion.</div>
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<div class="PlainText">/Bevin</div>
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