Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand.

Background: Timely and informed public health responses to infectious diseases such as COVID-19 necessitate reliable information about infection dynamics. The case ascertainment rate (CAR), the proportion of infections that are reported as cases, is typically much less than one and varies with testing practices and behaviours, making reported cases unreliable as the sole source of data. The concentration of viral RNA in wastewater samples provides an alternate measure of infection prevalence that is not affected by clinical testing, healthcare-seeking behaviour or access to care.

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

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.

Infrasonic gliding reflects a rising magma column at Mount Etna (Italy).

Infrasound is increasing applied as a tool to investigate magma dynamics at active volcanoes, especially at open-vent volcanoes, such as Mt. Etna (Italy), which are prodigious sources of infrasound. Harmonic infrasound signals have been used to constrain crater dimensions and track the movement of magma within the shallow plumbing system.

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

Aim: The New Zealand Government has transitioned from the Alert Level framework, which relied on Government action and population level controls, to the COVID-19 Protection Framework, which relies on vaccination rates and allows for greater freedoms (for the vaccinated). Under the COVID-19 Protection Framework with and current widespread community transmission of Omicron, there is significant interest in understanding the relative risk of spreading COVID-19 posed by unvaccinated, vaccinated, and boosted individuals.

Methods: A stochastic branching process model is used to simulate the spread of COVID-19 for outbreaks seeded by unvaccinated, vaccinated, or boosted individuals.

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

Aim: The August 2021 COVID-19 outbreak in Auckland 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 ease and as COVID-19 spreads throughout New Zealand, 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.

Method: A stochastic branching process model is used to simulate the initial spread of a COVID-19 outbreak for different vaccination rates.