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  • Writer's pictureStephen Grice

Questions arising from the modelling tool and the Hendy et al SEIR model published on 26 March 2020

There are many questions arise out of running simulations using the modelling tool. It is important to understand that it is a mathematical model and it is a tool. It isn't and doesn't have to be reality. Already we have seen deviations from the unmitigated course of the infection because of self-regulation and government regulation increasing social distance worldwide. The number of new tested infections is declining in New Zealand. It is important to highlight tested which is referenced in the last line of the discussion below and will be the subject of a future post.

In the meantime, it is worthwhile to consider the important conclusions from the Hendy et al paper which is available in full here but an extract which is the final discussion section of the paper is copied below.


Mitigation strategies, which aim to allow the epidemic to go ahead at a controlled rate, keep demand on healthcare systems under capacity, and deliver herd immunity, are a tempting approach for the control of Covid-19. However, model results show that for these to be successful requires the ability to reduce transmission to a level where the effective reproduction number Rc is close to or below 1. It remains unknown whether this will be achievable in practice in New Zealand. There is no evidence that it has yet been achieved in comparable, western democracies, including those that have instigated major lockdowns such as Italy. The only regimes that have conclusively achieved this level of control are China and South Korea. In these countries, this has been achieved by extremely intensive measures, including mandatory and strictly enforced quarantine, huge amounts of resources devoted to contact tracing, electronic surveillance of citizens’ movements, etc. In addition, successful mitigation requires periods of these intensive control measures to be continued for up to 2.5 years before the population acquires a sufficient level of herd immunity. This could be an underestimate as these models do not include population turnover via birth-death, which will become significant over this time frame and may act to reduce the build-up of herd immunity. Furthermore, correct timing of strong control measures is crucial to successfully keeping healthcare systems from being overloaded. Small uncertainties in case trajectories could lead to drastically overshooting hospital and ICU capacity. If hospitalisation and/or ICU admission rates are in reality higher than assumed here, e.g. closer to the CDC (2020) estimates (Table 1), then mitigation strategies aimed at keeping ICU load under become even more difficult. Expanding New Zealand’s ICU capacity would alleviate this somewhat, and would be a sensible precaution in any case.

Suppression strategies aim to keep the number infections to a minimum for as long as possible, by early instigation of control measures. This alone cannot prevent an epidemic from taking place indefinitely because there is no acquisition of herd immunity. Once control is lifted, a serious outbreak is likely to take place. If control measures are lifted altogether, the eventual outbreak could be as serious as a completely uncontrolled epidemic, leading to population-wide mortality rates of around 2%. This mortality rate could be even higher if severe cases that cannot be treated because of hospital overload experience a significantly higher CFR.

A major advantage of suppression strategies as opposed to mitigation is that early suppression buys time. This has two key benefits: (1) it may be possible to delay the epidemic for long enough that a vaccine and/or effective treatment become widely available in NZ; and (2) it allows NZ to learn from rapidly unfolding events in other countries. This could include learning which mitigation strategies are most successful, and how to ensure timing of control interventions is robust to uncertainty.

The simulations in this study were initialised with 20 seed infections and assumed no subsequent arrivals of new infections from overseas. Significant numbers of imported infections could accelerate the spread in the early stages of epidemic. This could have important consequences for the timing of control interventions. A separate, forthcoming study will investigate the effects of restricting international and domestic flights one the epidemic trajectory.

If strong suppression is successful in reducing the number of cases close to zero, it is possible that some control measures could be lifted. This would require: (i) continued widespread testing and contact tracing to ensure there are no undetected case clusters; and (ii) strong border measures to remain in place to ensure no fresh infections are imported. This approach is similar in principle to the on-off strategy shown in Fig. 4, but with the crucial difference that it aims to keep cases close to zero (as opposed to merely under ICU capacity). As long as (i) and (ii) are in place and we are confident that there are no undetected cases, this could allow periods when schools, businesses and services can operate and many aspects of day-to-day life to continue.


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