Modelling transmission and control of the COVID-19 pandemic in Australia

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.Comment: 45 pages, 19 figure

Delaying the COVID‐19 epidemic in Australia: evaluating the effectiveness of international travel bans

Objective: Following the outbreak of novel Severe Acute Respiratory Syndrome Coronavirus‐2 (SARS‐CoV‐2), and the disease named COVID‐19, in Wuhan, China in late 2019, countries have implemented different interventions such as travel bans to slow the spread of this novel virus. This brief report evaluates the effect of travel bans imposed to prevent COVID‐19 importation in the Australian context. Methods: We developed a stochastic meta‐population model to capture the global dynamics and spread of COVID‐19. By adjusting our model to capture the travel bans imposed globally and in Australia, the predicted COVID‐19 cases imported to Australia were evaluated in comparison to observed imported cases. Results: Our modelling results closely aligned with observed cases in Australia and elsewhere. We observed a 79% reduction in COVID‐19 importation and a delay of the COVID‐19 outbreak in Australia by approximately one month. Further projection of COVID‐19 to May 2020 showed spread patterns depending on the basic reproduction number. Conclusion: Imposing the travel ban was effective in delaying widespread transmission of COVID‐19. However, strengthening of the domestic control measures is needed to prevent Australia from becoming another epicentre. Implications for public health: This report has shown the importance of border closure to pandemic control

A Review of COVID-19 Modelling Strategies in Three Countries to Develop a Research Framework for Regional Areas

At the end of December 2019, an outbreak of COVID-19 occurred in Wuhan city, China. Modelling plays a crucial role in developing a strategy to prevent a disease outbreak from spreading around the globe. Models have contributed to the perspicacity of epidemiological variations between and within nations and the planning of desired control strategies. In this paper, a literature review was conducted to summarise knowledge about COVID-19 disease modelling in three countries-China, the UK and Australia-to develop a robust research framework for the regional areas that are urban and rural health districts of New South Wales, Australia. In different aspects of modelling, summarising disease and intervention strategies can help policymakers control the outbreak of COVID-19 and may motivate modelling disease-related research at a finer level of regional geospatial scales in the future

Key lessons from the COVID-19 public health response in Australia

Australia avoided the worst effects of the COVID-19 pandemic, but still experienced many negative impacts. Reflecting on lessons from Australia's public health response, an Australian expert panel composed of relevant discipline experts identified the following key lessons: 1) movement restrictions were effective, but their implementation requires careful consideration of adverse impacts, 2) disease modelling was valuable, but its limitations should be acknowledged, 3) the absence of timely national data requires re-assessment of national surveillance structures, 4) the utility of advanced pathogen genomics and novel vaccine technology was clearly demonstrated, 5) decision-making that is evidence informed and consultative is essential to maintain trust, 6) major system weaknesses in the residential aged-care sector require fixing, 7) adequate infection prevention and control frameworks are critically important, 8) the interests and needs of young people should not be compromised, 9) epidemics should be recognised as a ‘standing threat’, 10) regional and global solidarity is important. It should be acknowledged that we were unable to capture all relevant nuances and context specific differences. However, the intent of this review of Australia's public health response is to critically reflect on key lessons learnt and to encourage constructive national discussion in countries across the Western Pacific Region

Persistence of the Omicron variant of SARS-CoV-2 in Australia: The impact of fluctuating social distancing

We modelled emergence and spread of the Omicron variant of SARS-CoV-2 in Australia between December 2021 and June 2022. This pandemic stage exhibited a diverse epidemiological profile with emergence of co-circulating sub-lineages of Omicron, further complicated by differences in social distancing behaviour which varied over time. Our study delineated distinct phases of the Omicron-associated pandemic stage, and retrospectively quantified the adoption of social distancing measures, fluctuating over different time periods in response to the observable incidence dynamics. We also modelled the corresponding disease burden, in terms of hospitalisations, intensive care unit occupancy, and mortality. Supported by good agreement between simulated and actual health data, our study revealed that the nonlinear dynamics observed in the daily incidence and disease burden were determined not only by introduction of sub-lineages of Omicron, but also by the fluctuating adoption of social distancing measures. Our high-resolution model can be used in design and evaluation of public health interventions during future crises.Comment: 30 pages, 12 figures, source code: https://doi.org/10.5281/zenodo.732567