Simulating the impact of vaccination rates on the initial stages of a COVID-19 outbreak in New Zealand (Aotearoa) with a stochastic model

Abstract

AimThe August 2021 COVID-19 outbreak in Auckland has caused the New Zealand government to transition from an elimination strategy to suppression, which relies heavily on high vaccination rates in the population. As restrictions are eased and as COVID-19 leaks through the Auckland boundary, there is a need to understand how different levels of vaccination will impact the initial stages of COVID-19 outbreaks that are seeded around the country.MethodA stochastic branching process model is used to simulate the initial spread of a COVID-19 outbreak for different vaccination rates.ResultsHigh vaccination rates are effective at minimizing the number of infections and hospitalizations. Increasing vaccination rates from 20% (approximate value at the start of the August 2021 outbreak) to 80% (approximate proposed target) of the total population can reduce the median number of infections that occur within the first four weeks of an outbreak from 1011 to 14 (25th and 75th quantiles of 545-1602 and 2-32 for V=20% and V=80%, respectively). As the vaccination rate increases, the number of breakthrough infections (infections in fully vaccinated individuals) and hospitalizations of vaccinated individuals increases. Unvaccinated individuals, however, are 3.3x more likely to be infected with COVID-19 and 25x more likely to be hospitalized.ConclusionThis work demonstrates the importance of vaccination in protecting individuals from COVID-19, preventing high caseloads, and minimizing the number of hospitalizations and hence limiting the pressure on the healthcare system.

Attitudes towards the mixing of COVID-19 vaccinated and unvaccinated patients in multi-bed hospital rooms

“…This suggests that separating patients by vaccination status may reduce the spread of an outbreak before diagnosis has taken place. A recently published New Zealand paper by Watson et al 16 found that despite a large number of breakthrough infections among the vaccinated, unvaccinated individuals are 3.3 times more likely to be infected and 20 times more likely to be hospitalised, hence they have a greater risk of bringing COVID-19 into hospital even if they are admitted for other reasons. 16 In terms of the implementation of separate rooms for vaccinated and unvaccinated patients, some patients and most staff did not see it as practically and/or ethically possible and thought that current practices to reduce risk were adequate.…”

Likelihood of infecting or getting infected with COVID-19 as a function of vaccination status, as investigated with a stochastic model for New Zealand (Aotearoa) for Delta and Omicron variants

“…The model tracks the number of infections and the vaccination status of the infecting and infected individuals. The stochastic model used here is the same as presented in [4], which focused on the Delta variant, with the pertinent details summarized below.…”

“…15 It is unclear how testing rates will change in a highly vaccinated public; vaccinated and boosted individuals may feel less need to get tested while unvaccinated individuals may not want to get tested. Therefore, I focus purely on the impact of vaccination rates, particularly on the early stages of an outbreak when cases may be circulating undetected, and following the approach of [4], do not consider testing, contact tracing, or isolation of cases.…”

“…The model described above, originally developed in [4], was focused on the Delta variant. Given the rapid emergence and spread of Omicron in the community, I also apply the model to the Omicron variant with the following modifications.…”

“…Here, I use the stochastic model developed in [4] to estimate the likely number of infections caused by an outbreak seeded by an unvaccinated versus vaccinated/boosted individual. This information can help inform reopening decisions and restrictions on travel (e.g., requiring vaccination or a negative test prior to travel).…”