COVASIM: Modelling COVID-19

Figure 1: Impact of policy changes.

COVASIM – an individual-based model assessing the impact of easing COVID-19 restrictions.

When COVID-19 first reached Australia, Federal and State Governments implemented a series of behavioural control measures, including physical distancing and isolation/quarantine to reduce virus transmission. This approach has been highly successful.

As control measures are relaxed across Australia, care and vigilance is needed to limit the real risk that COVID-19 cases could rapidly rise again.

Hence it is vital that governments have high quality precise information about the likely impact of relaxing various control measures, and the time required to monitor the impact of relaxing these measures. It is also important to understand the likely impact of interventions on reducing transmission in the community.

More about COVASIM

Projected epidemic outcomes for COVID-19 strains against different vaccine rollouts | 11 June 2021

Estimating impacts of a COVID-19 outbreak without public health interventions, after vaccines have been administered

Authors: Dr Romesh Abeysuriya, Professor Margaret Hellard AM, Dr Nick Scott.

COVASIM modelling vaccine rollout

Click to view a larger version of the graph.

Model scenarios have been run, calibrated to Victoria, Australia, to help answer the question: What is the impact of different levels of vaccine coverage, if public health control measures were stopped and the virus was allowed to spread through the community?

Burnet Institute has developed an Excel-based tool that summarises thousands of simulations of different scenarios. In each scenario, new infections (one per day) begin to be introduced to the Victorian community at some point following the commencement of vaccine rollout. The vaccine rollout is assumed to continue at a fixed rate with increasing coverage every week.

The tool can compare outcomes when different COVID-19 strains are introduced, and vaccine efficacy assumptions are varied. Before using the tool or interpreting outcomes it is critical that the following key points and examples are read and understood. For additional information, or advice in interpretations, please contact the authors.

Critical points for understanding these projections:

  • The scenarios assume a user-defined vaccine rollout speed of either 150,000 or 250,000 doses per week in Victoria (75,000 or 125,000 vaccinated people per week, due to second doses). The results are different if the rate of vaccine rollout is different.
  • The scenarios do not currently include any major public health response to gain control of outbreaks. On detection of the first case, the model assumes symptomatic testing increases (isolation of positive cases continues), masks become recommended but not mandatory, and contact tracing continues but only up to 250 diagnoses per day. Hence the projections represent hypothetical near-worst-case scenarios.
  • The results are based on a collection of model assumptions about the contacts of individuals and disease transmission dynamics . If these best-estimate assumptions are optimistic or pessimistic, then compared with these projections actual epidemic outcomes will be more optimistic or pessimistic respectively.

One scenario created by Burnet Institute Head of Modelling, Dr Nick Scott and colleagues assumed a 50 per cent vaccine efficacy in preventing infections and a 93 per cent efficacy at preventing deaths among people who did become infected; a virus which was 1.5 times as infectious as the one in Victoria in June-November 2020; and where 80 per cent of people aged over 60 and 70 per cent of people younger than 60 years of age were eventually vaccinated.

“We found that if the virus enters the community when 60 per cent vaccine coverage has been reached and is left unchecked, we could see 4,885 deaths in Victoria within a year if no public health responses are introduced,” Dr Scott said.

“If we get peak vaccination coverage up to 95 per cent, the number of deaths reduces to 1346.”

Conclusions and Recommendations

  • Vaccine hesitancy and the emergence of new COVID-19 variants mean Australia is unlikely to achieve herd immunity
  • Public health initiatives remain vital in controlling COVID-19, even in vaccinated populations. Without public health measures, thousands of Victorians would be hospitalised and die if an initially small outbreak was left to spread through the community unchecked
  • Australia requires higher vaccine coverage to return to normal life.

COVID-19 Mathematical Modelling of resurgence risk: | 26 Sept 2020

Estimating risks associated with early reopening in Victoria

Authors: Dr Romesh Abeysuriya, Dominic Delport, Professor Margaret Hellard AM, Dr Nick Scott. Funding: Commissioned by the Victorian Department of Health and Human Services.

Following the introduction of Stage 4 restrictions in Melbourne, daily new detected cases of COVID-19 have been declining. Accordingly, a roadmap detailing possible sequences of policy relaxations has been proposed to return to a “COVID normal”, together with criteria for triggering each step. Due to the high social and economic impact of the restrictions currently in place, it is important that restrictions are relaxed as quickly as possible. However, relaxing too quickly increases the risk of a resurgence in infections, which may then require a reintroduction of restrictions to contain.

In this study, we use COVASIM to estimate the risk of Victoria experiencing a third COVID-19 epidemic wave if Stage 4 restrictions were eased on the 14th September 2020 or two weeks later on the 28th September.

In both scenarios, restrictions were eased to a level of restrictions similar to Victoria in early June (pre-Stage 3), approximately the “final step” in the Victorian government roadmap or NSW in September. Specifically we modelled:

  • Schools, childcare and workplaces reopen
  • Cafes, restaurants, pubs, bars, entertainment venues, and places of worship all open with a four square metre distancing rule
  • Community sport and small social gatherings are allowed
  • Test results take 24 hours to become available
  • Contact tracing takes an additional 24 hours following test results, and includes use of the COVIDSafe app
  • The number of tests per day is increased to maximum capacity observed in June upon easing
  • Large events are banned and mandatory masks are maintained.

While there are a wide range of options for incremental relaxation, in this study we sought to specifically examine the impact of timing, to examine the relationship between the degree of containment prior to relaxation and resurgence risk.

Conclusions and recommendations

Overall, our results suggest that Victoria would not have been able to safely return to NSW-level restrictions on 14th September, and there would be a high risk associated with lifting all restrictions at once on the 28th September.

Download the COVASIM Modelling of resurgence risk.


The Burnet Institute and the Institute for Disease Modelling in the USA has developed a unique individual-based COVID-19 model (COVASIM) that can assess the impact and risk associated with relaxing various physical distancing policies on the resurgence of COVID-19.

It has already been applied to a number of high, middle and low-income settings, including a number of states in the USA and countries across Africa. The individual-based simulation model can be applied to all Australian jurisdictions.

It provides governments with more specific and precise data to inform their COVID-19 responses.


N Scott, A Palmer, D Delport, R Abeysuriya, R Stuart, C Kerr, D Mistry, D Klein, R Sacks-Davis, K Heath, S Hainsworth, A Pedrana, M Stoove, D Wilson, M Hellard.
Modelling the impact of reducing control measures on the COVID-19 pandemic in a low transmission setting (In press – MJA) Accepted September 2020. Online 2 Sept.

The COVASIM model assessed the impact and risk associated with relaxing various physical distancing policies in Victoria, Australia at the end of the first COVID-19 wave. A key finding of that work was that relaxing restrictions too quickly could lead a considerable resurgence of COVID-19 in the community if there was failure to detect early clusters of infection.

Visit the Know-C19 Hub for more policy briefs and reports from the Know-C19 team.

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