Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia

Projection of healthcare demand in Germany and Switzerland urged by Omicron wave (January-March 2022)

In January 2022, after the implementation of broad vaccination programs, the Omicron wave was propagating across Europe. There was an urgent need to understand how population immunity affects the dynamics of the COVID-19 pandemic when the loss of vaccine protection was concurrent with the emergence of a new variant of concern. In particular, assessing the risk of saturation of the healthcare systems was crucial to manage the pandemic and allow a transition towards the endemic course of SARS-CoV-2 by implementing more refined mitigation strategies that shield the most vulnerable groups and protect the healthcare systems. We investigated the epidemic dynamics by means of compartmental models that describe the age-stratified social-mixing and consider vaccination status, type, and waning of the efficacy. In response to the acute situation, our model aimed at (i) providing insight into the plausible scenarios that were likely to occur in Switzerland and Germany in the midst of the Omicron wave, (ii) informing public health authorities, and (iii) helping take informed decisions to minimize negative consequences of the pandemic. Despite the unprecedented numbers of new positive cases, our results suggested that, in all plausible scenarios, the wave was unlikely to create an overwhelming healthcare demand; due to the lower hospitalization rate and the effectiveness of the vaccines in preventing a severe course of the disease. This prediction came true and the healthcare systems in Switzerland and Germany were not pushed to the limit, despite the unprecedentedly large number of infections. By retrospective comparison of the model predictions with the official reported data of the epidemic dynamic, we demonstrate the ability of the model to capture the main features of the epidemic dynamic and the corresponding healthcare demand. In a broader context, our framework can be applied also to endemic scenarios, offering quantitative support for refined public health interventions in response to recurring waves of COVID-19 or other infectious diseases.

Modelling COVID-19 transmission using IDSIM, an epidemiological-modelling desktop app with multi-level immunization capabilities

Background

: The coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented demands on local public health units in Ontario, Canada, one of which was the need for in-house epidemiological modelling capabilities. The objective of this study is to develop a native Windows desktop app for epidemiological modelling, to be used by public health unit epidemiologists to predict COVID-19 transmission in Durham Region.

Methods

: The developed app is an implementation of a multi-stratified compartmental epidemiological model that can accommodate multiple virus variants and levels of vaccination, as well as public health measures such as physical distancing, contact tracing followed by quarantine and testing followed by isolation. It was used to investigate the effects of different factors on COVID-19 transmission, including vaccination coverage, vaccine effectiveness, waning of vaccine-induced immunity and the advent of the Omicron variant. The simulation start date was November 22, 2021.

Results

: For the Delta variant, at least 90% of the population would need to be vaccinated to achieve herd immunity. A Delta-variant-only epidemiological curve would be flattened from the start in the absence of immunity waning and within six months in the presence of immunity waning. The percentage of infections caused by the Omicron variant was forecast to increase from 1% to 97% in the first month of the simulation. Total Omicron infections were forecasted to be reduced, respectively, by 26% or 41% if 3,000 or 5,000 booster doses were administered per day.

Conclusion

: For the Delta variant, both natural and vaccination-induced immunity are necessary to achieve herd immunity, and waning of vaccine-induced immunity lengthens the time necessary to reach herd immunity. In the absence of additional public health measures, a wave driven by the Omicron variant was predicted to pose significant public health challenges with infections predicted to peak in 2-3 months from the start of the simulation, depending on the rate of administration of booster doses.