Elsevier

Epidemics

Volume 41, December 2022, 100657
Epidemics

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

https://doi.org/10.1016/j.epidem.2022.100657Get rights and content
Under a Creative Commons license
open access

Highlights

  • A mathematical model of SARS-CoV-2 including waning of vaccine-derived and infection-derived immunity.

  • Analysis of scenarios for a second Omicron wave in New Zealand in April-September 2022.

  • Results were used to inform policy response and healthcare system preparedness.

  • Comparison of scenarios with subsequent data.

Abstract

Aotearoa New Zealand experienced a wave of the Omicron variant of SARS-CoV-2 in 2022 with around 200 confirmed cases per 1000 people between January and May. Waning of infection-derived immunity means people become increasingly susceptible to re-infection with SARS-CoV-2 over time. We investigated a model that included waning of vaccine-derived and infection-derived immunity under scenarios representing different levels of behavioural change relative to the first Omicron wave. Because the durability of infection-derived immunity is a key uncertainty in epidemiological models, we investigated outcomes under different assumptions about the speed of waning. The model was used to provide scenarios to the New Zealand Government, helping to inform policy response and healthcare system preparedness ahead of the winter respiratory illness season. In all scenarios investigated, a second Omicron wave was projected to occur in the second half of 2022. The timing of the peak depended primarily on the speed of waning and was typically between August and November. The peak number of daily infections in the second Omicron wave was smaller than in the first Omicron wave. Peak hospital occupancy was also generally lower than in the first wave but was sensitive to the age distribution of infections. A scenario with increased contact rates in older groups had higher peak hospital occupancy than the first wave. Scenarios with relatively high transmission, whether a result of relaxation of control measures or voluntary behaviour change, did not necessarily lead to higher peaks. However, they generally resulted in more sustained healthcare demand (>250 hospital beds throughout the winter period). The estimated health burden of Covid-19 in the medium term is sensitive to the strength and durability of infection-derived and hybrid immunity against reinfection and severe illness, which are uncertain.

Keywords

COVID-19
Mathematical model
Modelling-policy interface
Vaccination
Endemicity

Data Availability

Matlab code to run the model is available at https://github.com/Giorgia93/NZ-COVID19-reinfectionModel.

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