Modelling the dynamics of infection, waning of immunity and re-infection with the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand

Vattiatio, Giorgia; Lustig, Audrey; Maclaren, Oliver J.; Plank, Michael J.

doi:10.1016/j.epidem.2022.100657

Cited by 16 publications

(15 citation statements)

References 33 publications

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“…The model was also updated by introducing a dynamic vaccination coverage, waning of vaccine-derived and infection-derived immunity, and time-dependent behavioural changes. All these changes and the corresponding results were described in [ 24 ]. In addition, a later model update allowed us to infer the time-varying transmission coefficient from real-life case data using an approximate Bayesian computation approach [ 25 ].…”

Section: Discussionmentioning

confidence: 99%

Modelling Aotearoa New Zealand's COVID-19 protection framework and the transition away from the elimination strategy

Vattiato

Lustig²,

Maclaren

et al. 2023

R. Soc. open sci.

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For the first 18 months of the COVID-19 pandemic, New Zealand used an elimination strategy to suppress community transmission of SARS-CoV-2 to zero or very low levels. In late 2021, high vaccine coverage enabled the country to transition away from the elimination strategy to a mitigation strategy. However, given negligible levels of immunity from prior infection, this required careful planning and an effective public health response to avoid uncontrolled outbreaks and unmanageable health impacts. Here, we develop an age-structured model for the Delta variant of SARS-CoV-2 including the effects of vaccination, case isolation, contact tracing, border controls and population-wide control measures. We use this model to investigate how epidemic trajectories may respond to different control strategies, and to explore trade-offs between restrictions in the community and restrictions at the border. We find that a low case tolerance strategy, with a quick change to stricter public health measures in response to increasing cases, reduced the health burden by a factor of three relative to a high tolerance strategy, but almost tripled the time spent in national lockdowns. Increasing the number of border arrivals was found to have a negligible effect on health burden once high vaccination rates were achieved and community transmission was widespread.

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Section: Discussionmentioning

confidence: 99%

Modelling Aotearoa New Zealand's COVID-19 protection framework and the transition away from the elimination strategy

Vattiato

Lustig²,

Maclaren

et al. 2023

R. Soc. open sci.

Self Cite

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“…The value of R EI ( t ) was assumed to increase linearly from R EI,1 to R EI,2 starting around 10 March 2022 and over a window of 35–75 days (see electronic supplementary material, table S1). The contact matrix M was initially set to the matrix in the study by Vattiato et al [36], denoted M 0 , to provide a reasonable match with the observed age distribution of cases in the first part of the simulated time period. The contact matrix M was assumed to change to a modified matrix (1 − α M ) M 0 + α M M 1 , where M 1 is the matrix estimated from pre-pandemic data [25,37] and α M ∈ [0, 1] is fitted to data (see electronic supplementary material, figure S1).…”

Section: Methodsmentioning

confidence: 99%

Modelling the impact of the Omicron BA.5 subvariant in New Zealand

Lustig¹,

Vattiato

Maclaren

et al. 2023

J. R. Soc. Interface.

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New Zealand experienced a wave of the Omicron variant of SARS-CoV-2 in early 2022, which occurred against a backdrop of high two-dose vaccination rates, ongoing roll-out of boosters and paediatric doses, and negligible levels of prior infection. New Omicron subvariants have subsequently emerged with a significant growth advantage over the previously dominant BA.2. We investigated a mathematical model that included waning of vaccine-derived and infection-derived immunity, as well as the impact of the BA.5 subvariant which began spreading in New Zealand in May 2022. The model was used to provide scenarios to the New Zealand Government with differing levels of BA.5 growth advantage, helping to inform policy response and healthcare system preparedness during the winter period. In all scenarios investigated, the projected peak in new infections during the BA.5 wave was smaller than in the first Omicron wave in March 2022. However, results indicated that the peak hospital occupancy was likely to be higher than in March 2022, primarily due to a shift in the age distribution of infections to older groups. We compare model results with subsequent epidemiological data and show that the model provided a good projection of cases, hospitalizations and deaths during the BA.5 wave.

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“…These results were incorporated into dashboards for government policymakers and District Health Board planners. Scenarios were updated periodically as the model was refined to account for relaxation of social distancing behaviours, changing age-structured contact rates and reinfections [85].…”

Section: Modelling Tools Used In Australia and New Zealandmentioning

confidence: 99%

The Role of the Mathematical Sciences in Supporting the Covid-19 Response in Australia and New Zealand

MCCAW,

PLANK

2022

ANZIAM J.

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Mathematical modelling has been used to support the response to the COVID-19 pandemic in countries around the world including Australia and New Zealand. Both these countries have followed similar pandemic response strategies, using a combination of strict border measures and community interventions to minimize infection rates until high vaccine coverage was achieved. This required a different set of modelling tools to those used in countries that experienced much higher levels of prevalence throughout the pandemic. In this article, we provide an overview of some of the mathematical modelling and data analytics work that has helped to inform the policy response to the pandemic in Australia and New Zealand. This is a reflection on our experiences working at the modelling–policy interface and the impact this has had on the pandemic response. We outline the various types of model outputs, from short-term forecasts to longer-term scenario models, that have been used in different contexts. We discuss issues relating to communication between mathematical modellers and stakeholders such as health officials and policymakers. We conclude with some future challenges and opportunities in this area.

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Modelling the dynamics of infection, waning of immunity and re-infection with the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand

Cited by 16 publications

References 33 publications

Modelling Aotearoa New Zealand's COVID-19 protection framework and the transition away from the elimination strategy

Modelling Aotearoa New Zealand's COVID-19 protection framework and the transition away from the elimination strategy

Modelling the impact of the Omicron BA.5 subvariant in New Zealand

The Role of the Mathematical Sciences in Supporting the Covid-19 Response in Australia and New Zealand

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