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.

Cost-effective boosting allocations in the post-Omicron era of COVID-19 management (preprint)

BackgroundFollowing widespread exposure to Omicron variants, COVID-19 has transitioned to endemic circulation. Populations now have diverse infection and vaccination histories, resulting in heterogeneous immune landscapes. Careful consideration of vaccination is required through the post-Omicron phase of COVID-19 management to minimise disease burden. We assess the impact and cost-effectiveness of targeted COVID-19 vaccination strategies to support global vaccination recommendations. MethodsWe integrated immunological, transmission, clinical and cost-effectiveness models, and simulated populations with different characteristics and immune landscapes. We calculated the expected number of infections, hospitalisations and deaths for different vaccine scenarios. Costs (from a healthcare perspective) were estimated for exemplar country income level groupings in the Western Pacific Region. Results are reported as incremental costs and disability-adjusted life years averted compared to no additional vaccination. Parameter and stochastic uncertainty were captured through scenario and sensitivity analysis. FindingsAcross different population demographics and income levels, we consistently found that annual elder-targeted boosting strategies are most likely to be cost-effective or cost-saving, while paediatric programs are unlikely to be cost-effective. Results remained consistent while accounting for uncertainties in the epidemiological and economic models. Half-yearly boosting may only be cost-effective in higher income settings with older population demographics and higher cost-effectiveness thresholds. InterpretationThe seresults demonstrate the value of continued booster vaccinations to protect against severe COVID-19 disease outcomes across high and middle-income settings and show that the biggest health gains relative to vaccine costs are achieved by targeting older age-groups. FundingFunded by the World Health Organization. O_TEXTBOXResearch in context Evidence before this studyWith COVID-19 now globally endemic, populations exhibit varying levels of natural and vaccine-acquired immunity to SARS-CoV-2. With widespread, if variable, immunity resulting in reduced severity of COVID-19 disease, re-evaluation of the ongoing value of vaccination is required. COVID-19 vaccination strategies must consider the cost-effectiveness of gains from vaccination given prior immunity, and in the context of income and health system capacity to manage COVID-19 alongside other pressing concerns. Few articles examine cost-effectiveness of COVID-19 vaccination strategies in populations with diverse characteristics and waning hybrid immunity, though there is a large body of literature that considers some combination of these elements or focus on one particular country. Consensus is that allocating vaccine doses to older age groups and those at higher risk of severe disease is most beneficial, albeit assuming either only past natural immunity or no waning immunity. These studies have either not included a cost-effectiveness analysis or, where present, have typically assumed a base case zero-vaccination scenario. Added value of this studyWe consider the contemporary situation where populations have varying degrees of hybrid immunity resulting from both prior infection and vaccination, and where the relevant cost-effectiveness analysis considers only future primary and booster doses in the population. We describe multiple demographics, using exemplar older and younger populations, in conjunction with low to high past vaccination coverage, low to high past natural infection incidence, and low to high income levels. Under these settings, we determine the cost-effectiveness of a range of targeted boosting strategies (who, when, what). Implications of all the available evidenceOur study highlights how future COVID-19 booster doses targeted towards older age groups at risk of severe outcomes can be cost-effective or cost-saving in high-income settings with populations that have a higher proportion of individuals at risk. In younger, lower-resourced settings, annual boosting of older age groups may still be cost-effective or cost-saving in some scenarios. We consistently find that pediatric vaccination is not cost-effective. Given the benefits of vaccination, especially to reduce severe disease, we show the importance of ongoing global efforts to provide and equitably distribute vaccines and strengthen adult immunisation programs. C_TEXTBOX

Individual level analysis of digital proximity tracing for COVID-19 in Belgium highlights major bottlenecks (preprint)

To complement labour-intensive conventional contact tracing, digital proximity tracing was implemented widely during the COVID-19 pandemic. However, the privacy-centred design of the dominant Google-Apple exposure notification framework has hindered assessment of its effectiveness. Between October 2021 and January 2022, we systematically collected app use and notification receipt data within a test and trace programme for university students in Leuven, Belgium. Due to low success rates in each studied step of the digital notification cascade, only 4.3% of exposed contacts (CI: 2.8-6.1%) received such notifications, resulting in 10 times more cases detected through conventional contact tracing. Moreover, the infection risk of digitally traced contacts (5.0%; CI: 3.0-7.7%) was lower than that of conventionally traced non-app users (9.8%; CI: 8.8-10.7%; p=0.002). Contrary to common perception as near instantaneous, there was a 1.2-day delay (CI: 0.6-2.2) between case PCR result and digital contact notifications. These results highlight major limitations of the dominant digital proximity tracing framework.

Modelling the impact of hybrid immunity on future COVID-19 epidemic waves (preprint)

Since the emergence of SARS-CoV-2 (COVID-19), there have been multiple waves of infection and multiple rounds of vaccination rollouts. Both prior infection and vaccination can prevent future infection and reduce severity of outcomes, combining to form hybrid immunity against COVID-19 at the individual and population level. Here, we explore how different combinations of hybrid immunity affect the size and severity of near-future Omicron waves. To investigate the role of hybrid immunity, we use an agent-based model of COVID-19 transmission with waning immunity to simulate outbreaks in populations with varied past attack rates and past vaccine coverages, basing the demographics and past histories on the World Health Organization (WHO) Western Pacific Region (WPR). We find that if the past infection immunity is high but vaccination levels are low, then the secondary outbreak with the same variant can occur within a few months after the first outbreak; meanwhile, high vaccination levels can suppress near-term outbreaks and delay the second wave. Additionally, hybrid immunity has limited impact on future COVID-19 waves with immune-escape variants. Enhanced understanding of the interplay between infection and vaccine exposure can aid anticipation of future epidemic activity due to current and emergent variants, including the likely impact of responsive vaccine interventions.

Rapid prototyping of models for COVID-19 outbreak detection in workplaces (preprint)

Early case detection is critical to preventing onward transmission of COVID-19 by enabling prompt isolation of index infections, and identification and quarantining of contacts. Timeliness and completeness of ascertainment depend on the surveillance strategy employed. We use rapid prototype modelling to quickly investigate the effectiveness of testing strategies, to aid decision making. Models are developed with a focus on providing relevant results to policy makers, and these models are continually updated and improved as new questions are posed. The implementation of testing strategies in high risk settings in Australia was supported using models to explore the effects of test frequency and sensitivity on outbreak detection. An exponential growth model is firstly used to demonstrate how outbreak detection changes with varying growth rate, test frequency and sensitivity. From this model we see that low sensitivity tests can be compensated for by high frequency testing. This model is then updated to an Agent Based Model, which was used to test the robustness of the results from the exponential model, and to extend it to include intermittent workplace scheduling. These models help our fundamental understanding of disease detectability through routine surveillance in workplaces and evaluate the impact of testing strategies and workplace characteristics on the effectiveness of surveillance. This analysis highlights the risks of particular work patterns while also identifying key testing strategies to best improve outbreak detection in high risk workplaces.

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.

Virology and immune dynamics reveal high household transmission of ancestral SARS-CoV-2 strain (preprint)

Background: Household studies are crucial for understanding the transmission of SARS-CoV-2 infection, which may be underestimated from PCR testing of respiratory samples alone. We aim to combine assessment of household mitigation measures; nasopharyngeal, saliva and stool PCR testing; along with mucosal and systemic SARS-CoV-2 specific antibodies, to comprehensively characterise SARS-CoV-2 infection and transmission in households. Methods: Between March and September 2020, we obtained samples from 92 participants in 26 households in Melbourne, Australia, in a 4-week period following onset of infection with ancestral SARS-CoV-2 variants. Results: The secondary attack rate was 36% (24/66) when using nasopharyngeal swab (NPS) PCR positivity alone. However, when respiratory and non-respiratory samples were combined with antibody responses in blood and saliva, the secondary attack rate was 76% (50/66). SARS-CoV-2 viral load of the index case and household isolation measures were key factors that determine secondary transmission. In 27% (7/26) of households, all family members tested positive by NPS for SARS-CoV-2 and were characterised by lower respiratory Ct-values than low transmission families (Median 22.62 vs 32.91; IQR 17.06 to 28.67 vs 30.37 to 34.24). High transmission families were associated with enhanced plasma antibody responses to multiple SARS-CoV-2 antigens and the presence of neutralising antibodies. Three distinguishing saliva SARS-CoV-2 antibody features were identified according to age (IgA1 to Spike 1, IgA1 to nucleocapsid protein (NP), suggesting that adults and children generate distinct mucosal antibody responses during the acute phase of infection. Conclusion: Utilising respiratory and non-respiratory PCR testing, along with measurement of SARS-CoV-2 specific local and systemic antibodies, provides a more accurate assessment of infection within households and highlights some of the immunological differences in response between children and adults.

Transmission of SARS-CoV-2 in standardised First Few X cases and household transmission investigations: a systematic review and meta-analysis (preprint)

First Few X cases (FFX) investigations and Household transmission investigations (HHTI) are essential epidemiological tools for early characterisation of novel infectious pathogens and their variants. We aimed to estimate the household secondary infection attack rate (hSAR) of SARS-CoV-2 in investigations aligned with the WHO Unity Studies HHTI protocol. We conducted a systematic review and meta-analysis according to PRISMA 2020 guidelines (PROSPERO registration: CRD42021260065). We searched Medline, Embase, Web of Science, Scopus and medRxiv/bioRxiv for Unity-aligned FFX and HHTI published between 1 December 2019 and 26 July 2021. Standardised early results were shared by WHO Unity Studies Collaborators (to 1 October 2021). We used a bespoke tool to assess investigation methodological quality. Values for hSAR and 95% confidence intervals (CIs) were extracted or calculated from crude data. Heterogeneity was assessed by visually inspecting overlap of CIs on forest plots and quantified in meta-analyses. Of 9988 records retrieved, 80 articles (64 from databases; 16 provided by WHO Unity Studies collaborators) were retained in the systematic review and 62 were included in the primary meta-analysis. hSAR point estimates ranged from 2%-90% (95% prediction interval: 3%-71%; I2 = 99.7%); I2 values remained >99% in subgroup analyses, indicating high, unexplained heterogeneity and leading to a decision not to report pooled hSAR estimates. The large, unexplained variance in hSAR estimates emphasises the need for improved standardisation in planning, conduct and analysis, and for clear and comprehensive reporting of FFX and HHTIs, to guide evidence-based pandemic preparedness and response efforts for SARS-CoV-2, influenza and future novel respiratory viruses.

Learnings from the Australian First Few X Household Transmission Project for COVID-19 (preprint)

Background: First Few "X" (FFX) studies provide a platform to collect the required epidemiological, clinical and virological data to help address emerging information needs about the COVID-19 pandemic. Methods: We adapted the WHO FFX protocol for COVID-19 to understand severity and household transmission dynamics in the early stages of the pandemic in Australia. Implementation strategies were developed for participating sites; all household members provided baseline epidemiological data and were followed for 14 days from case identification. Household contacts completed symptom diaries and had respiratory swabs taken at baseline, day 7 and day 14, and day 28 where applicable. We modelled the spread of COVID-19 within households using a susceptible-exposed-infectious-recovered-type model, and calculated the household secondary attack rate and key epidemiological parameters. Findings: 96 households with 101 cases and 286 household contacts were recruited into the study between April-October 2020. Forty household contacts tested positive for SARS-CoV-2 in the study follow-up period. Our model estimated the household secondary attack rate to be 15% (95% CI 8-25%), which scaled up with increasing household size. Children were less infectious than their adult counterparts but were also more susceptible to infection. Interpretation: Our study provides important baseline data characterising the transmission of early SARS-CoV-2 strains from children and adults in Australia, against which properties of variants of concern can be benchmarked. We encountered many challenges with respect to logistics, ethics, governance and data management that may have led to biases in our study. Continued efforts to invest in preparedness research will help to test, refine and further develop Australian FFX study protocols in advance of future outbreaks.

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.

Optimal allocation of PCR tests to minimise disease transmission through contact tracing and quarantine (preprint)

PCR testing is a crucial capability for managing disease outbreaks, but it is also a limited resource and must be used carefully to ensure the information gain from testing is valuable. Testing has two broad uses, namely to track epidemic dynamics and to reduce transmission by identifying and managing cases. In this work we develop a modelling framework to examine the effects of test allocation in an epidemic, with a focus on using testing to minimise transmission. Using the COVID-19 pandemic as an example, we examine how the number of tests conducted per day relates to reduction in disease transmission, in the context of logistical constraints on the testing system. We show that if daily testing is above the routine capacity of a testing system, which can cause delays, then those delays can undermine efforts to reduce transmission through contact tracing and quarantine. This work highlights that the two goals of aiming to reduce transmission and aiming to identify all cases are different, and it is possible that focusing on one may undermine achieving the other. To develop an effective strategy, the goals must be clear and performance metrics must match the goals of the testing strategy. If metrics do not match the objectives of the strategy, then those metrics may incentivise actions that undermine achieving the objectives.

Modelling testing and response strategies for COVID-19 outbreaks in remote Australian Aboriginal communities (preprint)

BackgroundRemote Australian Aboriginal and Torres Strait Islander communities have potential to be severely impacted by COVID-19, with multiple factors predisposing to increased transmission and disease severity. Our modelling aims to inform optimal public health responses. MethodsAn individual-based simulation model represented communities ranging from 100 to 3,500 people, comprised of large interconnected households. A range of strategies for case finding, quarantining of contacts, testing, and lockdown were examined, following the silent introduction of a case.ResultsMultiple secondary infections are likely present by the time the first case is identified. Quarantine of close contacts, defined by extended household membership, can reduce peak infection prevalence from 60-70% to around 10%, but subsequent waves may occur when community mixing resumes. Exit testing significantly reduces ongoing transmission. Concurrent lockdown of non-quarantined households for 14 days is highly effective for epidemic control and reduces overall testing requirements; peak prevalence of the initial outbreak can be constrained to less than 5%, and the final community attack rate to less than 10% in modelled scenarios. Lockdown also mitigates the effect of a delay in the initial response. Compliance with lockdown must be at least 80-90%, however, or epidemic control will be lost.ConclusionsA SARS-CoV-2 outbreak will spread rapidly in remote communities. Prompt case detection with quarantining of extended-household contacts and a 14-day lockdown for all other residents, combined with exit testing for all, is the most effective strategy for rapid containment. Compliance is crucial, underscoring the need for community supported, culturally sensitive responses.  

Modelling testing and response strategies for COVID-19 outbreaks in remote Australian Aboriginal communities (preprint)

Background Remote Australian Aboriginal and Torres Strait Islander communities have potential to be severely impacted by COVID-19, with multiple factors predisposing to increased transmission and disease severity. Our modelling aims to inform optimal public health responses. Methods An individual-based simulation model represented communities ranging from 100 to 3,500 people, comprised of large interconnected households. A range of strategies for case finding, quarantining of contacts, testing, and lockdown were examined, following the silent introduction of a case. Results Multiple secondary infections are likely present by the time the first case is identified. Quarantine of close contacts, defined by extended household membership, can reduce peak infection prevalence from 60-70% to around 10%, but subsequent waves may occur when community mixing resumes. Exit testing significantly reduces ongoing transmission. Concurrent lockdown of non-quarantined households for 14 days is highly effective for epidemic control and reduces overall testing requirements; peak prevalence of the initial outbreak can be constrained to less than 5%, and the final community attack rate to less than 10% in modelled scenarios. Lockdown also mitigates the effect of a delay in the initial response. Compliance with lockdown must be at least 80-90%, however, or epidemic control will be lost. Conclusions A SARS-CoV-2 outbreak will spread rapidly in remote communities. Prompt case detection with quarantining of extended-household contacts and a 14-day lockdown for all other residents, combined with exit testing for all, is the most effective strategy for rapid containment. Compliance is crucial, underscoring the need for community supported, culturally sensitive responses.

INFERRED RESOLUTION THROUGH HERD IMMMUNITY OF FIRST COVID-19 WAVE IN MANAUS, BRAZILIAN AMAZON (preprint)

As in many other settings, peak excess mortality preceded the officially reported `first wave' peak of the COVID-19 epidemic in Manaus, Brazil, reflecting delayed case recognition and limited initial access to diagnostic testing. To avoid early information bias, we used detailed age and gender stratified death certificate and hospitalisation data to evaluate the epidemic's trajectory and infer the cause of its decline using a stochastic model. Our results are consistent with heterogenous transmission reducing over time due to the development of herd immunity. Relative to a baseline model that assumed homogenous mixing across Manaus, a model that permitted a small, self-isolated population fraction raised the estimated herd-immunity threshold from 28% to 30% and reduced the final attack rate from 86% to 65%. In the latter scenario, a substantial proportion of vulnerable, older individuals remained susceptible to infection. Given uncertainties regarding the distancing behaviours of population subgroups with different social and economic characteristics, and the duration of sterilising or transmission-modifying immunity in exposed individuals, we conclude that the potential for epidemic outbreaks remains, but that future waves of infection are likely to be much less pronounced than that already experienced.

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.