The estimated likelihood of eliminating the SARS-CoV-2 pandemic in Australia and New Zealand under current public health policy settings

On April 10th, I wrote about issues we had observed in public policy discussions regarding the possibility of eliminating COVID-19 from Australia. We asked (because we were perplexed), “Why is elimination of COVID-19 in Australia apparently off the table?” and came up with a small set of not very many good reasons.

On the 10th I also provided a preview of some earlier-stage modelling of ours at the Transport Health and Urban Design Research Hub at the University of Melbourne, that suggested if we stick to the current plan, we might eliminate COVID-19 by mid to late June (June 19th as an ‘average’ date with the start of August being an upper (95%) confidence interval estimate). Our primary goal with this work was to show that a ‘pattern’ of elimination was at least possible in Australia and I’m glad to see that with each day it appears to be becoming more likely. In fact, we might almost achieve it ‘accidentally’.

In the 2 weeks since that post, we have seen 3 things happen. Firstly, numbers of new infections have continued to decline – Great! What we are doing is working.

Secondly, discussion of elimination is back! Which is also heartening because it is a real possibility and we can be proud that Australia and New Zealand really are leading the way, internationally.

But thirdly, as case numbers dwindle, we are also seeing increasing pressure to begin lifting restrictions, which will only get louder the lower numbers drop. Recent Google trends data in Australia confirms this (in a pretty ropey way) by showing that searches for ‘lift restrictions’ and ‘ease restrictions’ are on the way up.

So, 1) cases going down, 2) pressure to lift restrictions going up and 3) actual restrictions also being loosened. This is potentially cause for concern. The problem is, we have no idea how much of a concern it really is – and we possibly won’t know until it goes wrong. And then what? Put the restrictions back in place? This is the on-again, off again ‘Goldilocks’ strategy which would be extremely difficult for any Government to communicate and manage well.

Restrictions on a variety of activities that have helped stem the spread of COVID-19 are being wound back.

To help answer this question, colleagues from Australia and New Zealand and I have drafted a paper with updated estimates from those previewed here on April 10th. Titled “The estimated likelihood of eliminating the SARS-CoV-2 pandemic in Australia and New Zealand under current public health policy settings” we attempt to show that despite our successes to date, Australia (and New Zealand) are still on a knife-edge when it comes to the elimination of COVID-19 from the population. We also show that dissolution of our current successful behavioural strategy over the 60 days post social distancing implementation could result in the dreaded ‘second-wave’ of infections, cause avoidable death and illness, and prolong the economic and social shutdown even longer. You can see a draft of the paper on Elsevier’s SSRN pre-print site here.

In this paper, we use an SEIR-inspired Agent-Based Model I have discussed previously under 2 scenarios. Scenario 1 locks-in the current social distancing policies both NZ and Australia put in place on March 26th and 28th, respectively, and doesn’t lift them until the virus is eliminated from the community (defined as no new cases and no current, non-recovered cases).

Scenario 2 implements the same policies on the same dates as above, but gradually eases off on the adherence to these policies in a non-linear way over 60 days, returning to baseline levels on May 26th/28th. Here’s a picture of the decay function we used – there are others that we and others also think could be realistic.

Here is a snapshot of our results.

Under Scenario 1 where no reduction of social distancing measures happens (e.g., no ‘easing restrictions’ during the 60 days), we estimate that the average date Australia and NZ might eliminate COVID-19 from the population is June 15th and June 17th, respectively, with a 95% confidence interval of between May 13th and July 30th for Australia and May 28th to August 7th for NZ.

Further, looking at thousands of trials of our model, we show that 90% of model runs acheived elimination on July 10th in Australia and 90% for NZ on July 14th.

So – 7 weeks from now, if we just sit tight and keep doing what we’re doing so well, we have a better than even chance of ridding COVID-19 from our shores. And 12 weeks from now, we have a 90% chance.

But what of Scenario 2 – where everyone starts to relax a bit; just ease off a little until the end of May, then – phew! Well, the answer is not good. Under this scenario, we estimate that Australia has only a 35% chance of elimination at all in the next 300 days, and New Zealand a similarly disappointing 36%. The pandemic drags on and on, well into next year and beyond. No social gatherings for you.

So what?

Our results highlight that in Australia and New Zealand, Government imposed public health responses and each country’s public adherence to these, has provided the potential to eliminate the COVID-19 infection from the community if these measures and levels of adherence are maintained.

However, reductions in adherence to physical distancing over the post-implementation period – even slightly, could lead to a resurgence in cases, and worse health, economic and social outcomes in the long-term – especially in the absence of effective and publicly accepted measures to improve contact tracing (e.g., contact tracing apps*) which we assess the benefits of here.

Now is not the time to ease off.

*At 6pm on Sunday 26th of April, the Australian Federal Government will make available a tracing app to augment existing state-based manual tracking and tracing. We have incorporated the uptake of this app and its effectiveness in boosting identification of cases into our work here.

A lot of people have also contacted me asking about the effect of schools re-opening – especially in NSW. You can see some example results of how this might work here.

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