Prof Nick Wilson, Dr Jennifer Summers, Dr Amanda Kvalsvig, Prof Michael Baker*
In this blog we summarise the results of modelling for an Omicron variant outbreak of Covid-19 in NZ by the Institute of Health Metrics and Evaluation. This work suggests that in an outbreak that begins in January, the number of cases in hospital might peak at 2,790 (95%CI: 120 to 9,070) in early March 2022. Cumulative additional deaths might be 400 by 1 May, near the end of the outbreak (peaking at 10 deaths per day [95%CI: 0 to 50]). While there are various limitations and uncertainties with all such modelling, our impression is that this work is of high quality and should be considered by NZ policy-makers. But other factors, such as the social and economic disruption from such an Omicron outbreak, should also be important considerations in guiding preparations and preventive measures.
Blog syndicated with permission from “The Pursuit” at Melbourne University, Australia
By Professor Tony Blakely, Dr Tim Wilson and Associate Professor Vijaya Sundararajan, University of Melbourne
As Australia looks toward opening its international borders, new virus modelling provides scenarios that can help us decide what’s the right risk to tolerate.
Prof Nick Wilson, Prof Michael Baker, Prof Martin Eichner*
In this blog we detailed our just published modelling work on estimating the risk of COVID-19 outbreaks associated with air travel to NZ. We find that the risks are typically very low for travel from Australia (a “green zone” country with small occasional outbreaks from border system failures). But these risks go up if there are larger outbreaks in Australia and especially for travel from other countries (e.g., from an “amber zone” country like Japan or a “red zone” country as per the US during 2020) where rigorous border controls including 14-day quarantine are still required. With the spread of more infectious SARS-CoV-2 variants it is critical that very rigorous ongoing scientific risk assessment is used for NZ and all aspects of border control are optimised for the differing risk posed by green, amber and red zone countries.