The impact of re-opening the international border on COVID-19 hospitalisations in Australia: a modelling study.
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ABSTRACT: Objective
To estimate the numbers of COVID-19-related hospitalisations in Australia after re-opening the international border.Design
Population-level deterministic compartmental epidemic modelling of eight scenarios applying various assumptions regarding SARS-CoV-2 transmissibility (baseline R0 = 3.5 or 7.0), vaccine rollout speed (slow or fast), and scale of border re-opening (mean of 2500 or 13 000 overseas arrivals per day).Setting
Simulation population size, age structure, and age-based contact rates based on recent estimates for the Australian population. We assumed that 80% vaccination coverage of people aged 16 years or more was reached in mid-October 2021 (fast rollout) or early January 2022 (slow rollout).Main outcome measures
Numbers of people admitted to hospital with COVID-19, December 2021 - December 2022.Results
In scenarios assuming a highly transmissible SARS-CoV-2 variant (R0 = 7.0), opening the international border on either scale was followed by surges in both infections and hospitalisations that would require public health measures beyond mask wearing and social distancing to avoid overwhelming the health system. Reducing the number of hospitalisations to manageable levels required several cycles of additional social and mobility restrictions.Conclusions
If highly transmissible SARS-CoV-2 variants are circulating locally or overseas, large and disruptive COVID-19 outbreaks will still be possible in Australia after 80% of people aged 16 years or more have been vaccinated. Continuing public health measures to restrict the spread of disease are likely to be necessary throughout 2022.
SUBMITTER: Hanly MJ
PROVIDER: S-EPMC8662022 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:There is a continuing debate on relative benefits of various mitigation and suppression strategies aimed to control the spread of COVID-19. Here we report the results of agent-based modelling using a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to match key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, with this fraction for children found to be one-fifth of such fraction for adults. We apply the model to compare several intervention strategies, including restrictions on international air travel, case isolation, home quarantine, social distancing with varying levels of compliance, and school closures. School closures are not found to bring decisive benefits unless coupled with high level of social distancing compliance. We report several trade-offs, and an important transition across the levels of social distancing compliance, in the range between 70% and 80% levels, with compliance at the 90% level found to control the disease within 13-14 weeks, when coupled with effective case isolation and international travel restrictions.
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Project description:BackgroundPolicy responses to COVID-19 in Victoria, Australia over 2020-2021 have been supported by evidence generated through mathematical modelling. This study describes the design, key findings, and process for policy translation of a series of modelling studies conducted for the Victorian Department of Health COVID-19 response team during this period.MethodsAn agent-based model, Covasim, was used to simulate the impact of policy interventions on COVID-19 outbreaks and epidemic waves. The model was continually adapted to enable scenario analysis of settings or policies being considered at the time (e.g. elimination of community transmission versus disease control). Model scenarios were co-designed with government, to fill evidence gaps prior to key decisions.ResultsUnderstanding outbreak risk following incursions was critical to eliminating community COVID-19 transmission. Analyses showed risk depended on whether the first detected case was the index case, a primary contact of the index case, or a 'mystery case'. There were benefits of early lockdown on first case detection and gradual easing of restrictions to minimise resurgence risk from undetected cases. As vaccination coverage increased and the focus shifted to controlling rather than eliminating community transmission, understanding health system demand was critical. Analyses showed that vaccines alone could not protect health systems and need to be complemented with other public health measures.ConclusionsModel evidence offered the greatest value when decisions needed to be made pre-emptively, or for questions that could not be answered with empiric data and data analysis alone. Co-designing scenarios with policy-makers ensured relevance and increased policy translation.
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