COVID-19 epidemic modelling for policy decision support in Victoria, Australia 2020-2021

Abstract

Background: Policy 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.

Methods: An 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.

Results: Understanding 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.

Conclusions: Model 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.

Keywords: COVID-19; Disease control; Mathematical model; Outbreak analysis.

Fig. 1

Victorian COVID-19 timeline. New daily cases and vaccine coverage are shown over time, contextualising the overall strategic phase (elimination or suppression) and the dominant scenario type being run at different stages of the pandemic (vertical shaded regions)

Fig. 2

Wild-type epidemic wave in Victoria in 2020, in the context of an elimination COVID-19 strategy, with scenarios considering resurgence risk if restrictions were eased on 14 Sep (red) or 28 Sep (blue). Model simulations were started with random infected seed cases and randomly sampled transmission parameters, and were retained if they were within sufficient bounds of the observed data. Throughout the simulations ‘Stage 3’, masks and ‘Stage 4’ restrictions were imposed, with their impact derived through model calibration (see [8])

Fig. 3

Outbreak analysis in Victoria in 2021, in the context of pursuing an elimination strategy. Simulations were run starting from zero cases and a randomly infected seed case. Table shows the proportion of simulations where an outbreak occurred (defined as reaching a 7-day average of > 30 diagnoses/day within 90 days), according to which infection generation was detected, the infectiousness of the virus (baseline = wild type; 50% more infectious ~ Alpha variant) and what responses were implemented on detection of the first case (light = masks and limits on social gatherings; moderate = light + density limits; heavy = lockdown)

Fig. 4

Outbreak time to containment. Following an outbreak, the time required in lockdown to return to < 5 diagnoses per day, according to the delay in implementing restrictions. Lines show median and inter-quartile range (error bars) across 1000 simulations. Based on the wild type variant

Fig. 5

Outbreak analysis in Victoria in 2021, when an outbreak has been detected but limited information is known, pursuing an elimination strategy. Top: Simulations were run starting from zero cases and a randomly infected seed case. Simulations were only retained if they produced, through stochastic variation, approximately the same initial outbreaks as occurred. In this example it was 43–65 diagnoses within 7 days of the first diagnosis, and 53–80 diagnoses within 12 days of the first diagnosis. This is against a background of masks and work from home if possible being implemented on day 1, and lockdown being implemented on day 3. Bottom: From the retained simulations, scenarios compared whether the lockdown was maintained, or after 14 days either schools were reopened, venues were opened with density limits, small social gatherings were also allowed, or a return to masks and working from home only

Fig. 6

Outbreak analysis in Victoria in 2021, over 90 days starting from a single case and different levels of population vaccine coverage. Left: AstraZeneca type vaccine, with assumed protection against infection of 50%, and protection against symptomatic disease of 65%. Right: Pfizer type vaccines, with assumed protection against infection of 80%, and protection against symptomatic disease of 90%. TPOD = total protection against disease; POI = protection against infection. Note that vaccine efficacy estimates were based on best available data as at March 2021

Fig. 7

Projected COVID-19 deaths in Victoria over a 12-month period under different outbreak response scenarios, triggered by case numbers (left), and average time spent under restrictions (right). Top: Grey bars show the projected number of deaths on a log scale, with the lighter shading indicating the proportion that are among the vaccinated population. Scenarios are based on 95%/70%/70% vaccine coverage being achieved among people aged 60+/12–59/<12 years, the vaccine having an assumed 80% protection against infection and 92% protection against death, and 5 cases per day were seeded into the community through reduced quarantine measures. Light restrictions = mandatory masks, density limits and work from home if possible; medium restriction = light restrictions + additional limits on gathering sizes; lockdown = mandatory masks, work from home, schools closed, retail closed, hospitality take-away only, social gatherings up to two outdoors only. Bottom: example time series output from one simulation, where increasing restrictions are triggered with increased hospital number thresholds, to maintain disease control

Fig. 8

2021 roadmap with reduced testing for people vaccinated (blue), maintained testing for people vaccinated (red), and an additional 15% reduction in non-household transmission (green). Scenarios include schools returning to in person learning throughout October; childcare returning and mobility restrictions easing in October; limited outdoor gatherings at 70% two-dose vaccine coverage among people 16 + years; indoor gathering with density limits at 80% two-dose coverage among people 16 + years and mandatory vaccine requirements. Dashed vertical lines represent estimated dates of reaching 70% and 80% two-dose coverage among people 16 + years