A model-based assessment of social isolation practices for COVID-19 outbreak response in residential care facilities (preprint)

We apply a computational modelling approach to investigate the relative effectiveness of general isolation practices for mitigation of COVID-19 outbreaks in residential care facilities. Our study focuses on policies intended to reduce contact between residents, without regard to confirmed infection status. Despite the ubiquity of such policies, and their controversial association with adverse physical and mental health outcomes, little evidence exists evaluating their effectiveness at mitigating outbreaks. Through detailed simulations of COVID-19 outbreaks in residential care facilities, our results demonstrate that general isolation of residents provides little additional impact beyond what is achievable through isolation of confirmed cases and deployment of personal protective equipment.

Key challenges for the surveillance of respiratory viruses: transitioning out of the acute phase of the SARS-CoV-2 pandemic (preprint)

To support the ongoing management of viral respiratory diseases, many countries are moving towards an integrated model of surveillance for SARS-CoV-2, influenza, and other respiratory pathogens. While many surveillance approaches catalysed by the COVID-19 pandemic provide novel epidemiological insight, continuing them as implemented during the pandemic is unlikely to be feasible for non-emergency surveillance, and many have already been scaled back. Furthermore, given anticipated co-circulation of SARS-CoV-2 and influenza, surveillance activities in place prior to the pandemic require review and adjustment to ensure their ongoing value for public health. In this perspective, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies, their contribution to epidemiological assessment, forecasting, and public health decision making.

Estimating the impact of test-trace-isolate-quarantine systems on SARS-CoV-2 transmission in Australia (preprint)

We report on an analysis of Australian COVID-19 case data to estimate the impact of TTIQ systems on SARS-CoV-2 transmission in 2020-21. We estimate that in a low prevalence period in the state of New South Wales (tens of cases per day), TTIQ contributed to a 54% reduction in transmission. In a higher prevalence period in the state of Victoria (hundreds of cases per day), TTIQ contributed to a 42% reduction in transmission. Our results also suggest that case-initiated contact tracing can support timely quarantine in times of system stress. Contact tracing systems for COVID-19 in Australia were highly effective and adaptable in supporting the national suppression strategy through 2020 and 2021.

Estimating measures to reduce the transmission of SARS-CoV-2 in Australia to guide a 'National Plan' to reopening (preprint)

BackgroundIn mid-2021, widespread availability of COVID-19 vaccines with demonstrated impacts on transmission promised relief from the strict public health and social measures (PHSMs) imposed in many countries to limit spread and burden. We were asked to define vaccine coverage thresholds for transition through the stages of Australias National Plan to easing restrictions and reopening international borders. MethodsUsing available evidence of vaccine effectiveness against the then-circulating Delta variant, we used a mathematical model to determine vaccine coverage targets. The absence of any COVID-19 infections in many sub-national jurisdictions in Australia posed particular methodological challenges for modelling in this setting. We used a novel metric called Transmission Potential (TP) as a proxy measure of the population-level effective reproduction number. We estimated TP of the Delta variant under a range of PHSMs, test-trace-isolate-quarantine (TTIQ) efficiencies, vaccination coverage thresholds, and age-based vaccine allocation strategies. FindingsWe found that high coverage of vaccination across all age groups ([≤] 70%) combined with ongoing TTIQ and minimal PHSMs was sufficient to avoid strict lockdowns. At lesser coverage ([≤] 60%) rapid case escalation risked overwhelming of the health sector and would prompt a need to reimpose strict restrictions, with substantive economic impacts in order to achieve the goals of the National Plan. Maintaining low case numbers was the most beneficial strategy for health and the economy, and at higher coverage levels ([≥] 80%) further easing of restrictions was deemed possible. InterpretationThese results reinforced recommendations from other modelling groups that some level of PHSMs should be continued to minimise the burden of the Delta variant following achievement of high population vaccine coverage. They directly informed easing of COVID-19 restrictions in Australia. FundingThis study was supported by the Australian Government Department of Health and Ageing, and the National Health and Medical Research Councils Centre of Research Excellence scheme (GNT1170960).

COVID-19 vaccine coverage targets to inform reopening plans in a low incidence setting (preprint)

Since the emergence of SARS-CoV-2 in 2019 through to mid-2021, much of the Australian population lived in a COVID-19 free environment. This followed the broadly successful implementation of a strong suppression strategy, including international border closures. With the availability of COVID-19 vaccines in early 2021, the national government sought to transition from a state of minimal incidence and strong suppression activities to one of high vaccine coverage and reduced restrictions but with still-manageable transmission. This transition is articulated in the national ``re-opening" plan released in July 2021. Here we report on the dynamic modelling study that directly informed policies within the national re-opening plan including the identification of priority age groups for vaccination, target vaccine coverage thresholds and the anticipated requirements for continued public health measures --- assuming circulation of the Delta SARS-CoV-2 variant. Our findings demonstrated that adult vaccine coverage needed to be at least 70% to minimise public health and clinical impacts following the establishment of community transmission. They also supported the need for continued application of test-trace-isolate-quarantine and social measures during the vaccine roll-out phase and beyond.

Forecasting COVID-19 activity in Australia to support pandemic response: May to October 2020 (preprint)

As of January 2021, Australia had effectively controlled local transmission of COVID-19 despite a steady influx of imported cases and several local, but contained, outbreaks in 2020. Throughout 2020, state and territory public health responses were informed by weekly situational reports that included an ensemble forecast for each jurisdiction. We present here an analysis of one forecasting model included in this ensemble across the variety of scenarios experienced by each jurisdiction from May to October 2020. We examine how successfully the forecasts characterised future case incidence, subject to variations in data timeliness and completeness, showcase how we adapted these forecasts to support decisions of public health priority in rapidly-evolving situations, evaluate the impact of key model features on forecast skill, and demonstrate how to assess forecast skill in real-time before the ground truth is known. Conditioning the model on the most recent, but incomplete, data improved the forecast skill, emphasising the importance of developing strong quantitative models of surveillance system characteristics, such as ascertainment delay distributions. Forecast skill was highest when there were at least 10 reported cases per day, the circumstances in which authorities were most in need of forecasts to aid in planning and response.

Hospital length of stay in a mixed Omicron and Delta epidemic in New South Wales, Australia (preprint)

Aim: To estimate the length of stay distributions of hospitalised COVID-19 cases during a mixed Omicron-Delta epidemic in New South Wales, Australia (16 Dec 2021 -- 7 Feb 2022), and compare these to estimates produced over a Delta-only epidemic in the same population (1 Jul 2021 -- 15 Dec 2022). Background: The distribution of the duration that clinical cases of COVID-19 occupy hospital beds (the `length of stay') is a key factor in determining how incident caseloads translate into health system burden as measured through ward and ICU occupancy. Results: Using data on the hospital stays of 19,574 individuals, we performed a competing-risk survival analysis of COVID-19 clinical progression. During the mixed Omicron-Delta epidemic, we found that the mean length of stay for individuals who were discharged directly from ward without an ICU stay was, for age groups 0-39, 40-69 and 70+ respectively, 2.16 (95\% CI: 2.12--2.21), 3.93 (95\% CI: 3.78--4.07) and 7.61 days (95\% CI: 7.31--8.01), compared to 3.60 (95\% CI: 3.48--3.81), 5.78 (95\% CI: 5.59--5.99) and 12.31 days (95\% CI: 11.75--12.95) across the preceding Delta epidemic (15 Jul 2021 -- 15 Dec 2021). We also considered data on the stays of individuals within the Hunter New England Local Health District, where it was reported that Omicron was the only circulating variant, and found mean ward-to-discharge length of stays of 2.05 (95\% CI: 1.80--2.30), 2.92 (95\% CI: 2.50--3.67) and 6.02 days (95\% CI: 4.91--7.01) for the same age groups.

Estimating the transmissibility of SARS-CoV-2 during periods of high, low and zero case incidence (preprint)

Against a backdrop of widespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 under control and maintained near-elimination status. A key element of epidemic response is the tracking of disease transmissibility in near real-time. During major outbreaks, the reproduction rate can be estimated from a time-series of case, hospitalisation or death counts. In low or zero incidence settings, knowing the potential for the virus to spread is a response priority. Absence of case data means that this potential cannot be estimated directly. We present a semi-mechanistic modelling framework that draws on time-series of both behavioural data and case data (when disease activity is present) to estimate the transmissibility of SARS-CoV-2 from periods of high to low -- or zero -- case incidence, with a coherent transition in interpretation across the changing epidemiological situations. Of note, during periods of epidemic activity, our analysis recovers the effective reproduction number, while during periods of low -- or zero -- case incidence, it provides an estimate of transmission risk. This enables tracking and planning of progress towards the control of large outbreaks, maintenance of virus suppression, and monitoring the risk posed by re-introduction of the virus. We demonstrate the value of our methods by reporting on their use throughout 2020 in Australia, where they have become a central component of the national COVID-19 response.

COVID-19 in low-tolerance border quarantine systems: impact of the Delta variant of SARS-CoV-2 (preprint)

In controlling transmission of COVID-19, the effectiveness of border quarantine strategies is a key concern for jurisdictions in which the local prevalence of disease and immunity is low. In settings like this such as China, Australia, and New Zealand, rare outbreak events can lead to escalating epidemics and trigger the imposition of large scale lockdown policies. Here, we examine to what degree vaccination status of incoming arrivals and the quarantine workforce can allow relaxation of quarantine requirements. To do so, we develop and apply a detailed model of COVID-19 disease progression and transmission taking into account nuanced timing factors. Key among these are disease incubation periods and the progression of infection detectability during incubation. Using the disease characteristics associated with the ancestral lineage of SARS-CoV-2 to benchmark the level of acceptable risk, we examine the performance of the border quarantine system for vaccinated arrivals. We examine disease transmission and vaccine efficacy parameters over a wide range, covering plausible values for the Delta variant currently circulating globally. Our results indicate a threshold in outbreak potential as a function of vaccine efficacy, with the time until an outbreak increasing by up to two orders of magnitude as vaccine efficacy against transmission increases from 70% to 90%. For parameters corresponding to the Delta variant, vaccination is able to maintain the capacity of quarantine systems to reduce case importation and outbreak risk, by counteracting the pathogen's increased infectiousness. To prevent outbreaks, heightened vaccination in border quarantine systems must be combined with mass vaccination. The ultimate success of these programs will depend sensitively on the efficacy of vaccines against viral transmission.

From climate change to pandemics: decision science can help scientists have impact (preprint)

Scientific knowledge and advances are a cornerstone of modern society. They improve our understanding of the world we live in and help us navigate global challenges including emerging infectious diseases, climate change and the biodiversity crisis. For any scientist, whether they work primarily in fundamental knowledge generation or in the applied sciences, it is important to understand how science fits into a decision-making framework. Decision science is a field that aims to pinpoint evidence-based management strategies. It provides a framework for scientists to directly impact decisions or to understand how their work will fit into a decision process. Decision science is more than undertaking targeted and relevant scientific research or providing tools to assist policy makers; it is an approach to problem formulation, bringing together mathematical modelling, stakeholder values and logistical constraints to support decision making. In this paper we describe decision science, its use in different contexts, and highlight current gaps in methodology and application. The COVID-19 pandemic has thrust mathematical models into the public spotlight, but it is one of innumerable examples in which modelling informs decision making. Other examples include models of storm systems (eg. cyclones, hurricanes) and climate change. Although the decision timescale in these examples differs enormously (from hours to decades), the underlying decision science approach is common across all problems. Bridging communication gaps between different groups is one of the greatest challenges for scientists. However, by better understanding and engaging with the decision-making processes, scientists will have greater impact and make stronger contributions to important societal problems.

Early analysis of the Australian COVID-19 epidemic (preprint)

As of 18 April 2020, there had been 6,533 confirmed cases of COVID-19 in Australia. Of these, 67 had died from the disease. The daily count of new confirmed cases was declining. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis - for now. Analysing factors, such as the intensity and timing public health interventions, that contribute to individual country experiences of COVID-19 will assist in the next stage of response planning globally. Using data from the Australian national COVID-19 database, we describe how the epidemic and public health response unfolded in Australia up to 13 April 2020. We estimate that the effective reproduction number was likely below 1 (the threshold value for control) in each Australian state since mid-March and forecast that hospital ward and intensive care unit occupancy will remain below capacity thresholds over the next two weeks.