Statistics

Objective: To assess the association between having a serious mental illness and surgical outcomes for adults, including in‐hospital and 30‐day mortality, post‐operative complications, and hospital length of stay. Study design: Systematic review and meta‐analysis of publications in English to 30 July 2018 of studies that examined associations between having a serious mental illness and surgical outcomes for adults who underwent elective surgery. Primary outcomes were in‐hospital and 30‐day mortality, post‐operative complications, and length of hospital stay. Risk of bias was assessed with the Quality in Prognosis Studies (QUIPS) tool. Studies were grouped by serious mental illness diagnosis and outcome measures. Odds ratios (ORs) or mean differences (MDs), with 95% confidence intervals (CIs), were calculated in random effects models to provide pooled effect estimates. Data sources: MEDLINE, EMBASE, PsychINFO, and the Cochrane Library. Data synthesis: Of the 3824 publications identified by our search, 26 (including 6 129 806 unique patients) were included in our analysis. The associations between having any serious mental illness diagnosis and having any post‐operative complication (ten studies, 125 624 patients; pooled effect: OR, 1.44; 95% CI, 1.15–1.79) and a longer stay in hospital (ten studies, 5 385 970 patients; MD, 2.6 days; 95% CI, 0.8–4.4 days) were statistically significant, but not those for in‐hospital mortality (three studies, 42 926 patients; OR, 1.21; 95% CI, 0.69–2.12) or 30‐day mortality (six studies, 83 013 patients; OR, 1.85; 95% CI, 0.86–3.99). Conclusions: Having a serious mental illness is associated with higher rates of post‐operative complications and longer stays in hospital, but not with higher in‐hospital or 30‐day mortality. Targeted pre‐operative interventions may improve surgical outcomes for these vulnerable patients. Systematic review registration: PROSPERO, CRD42018080114 (prospective).

Kate E McBride · Michael J Solomon · Paul G Bannon · Nicholas Glozier · Daniel Steffens

Objective: To evaluate the efficacy and safety of paracetamol as an analgesic medication in a range of painful conditions. Study design: Systematic review of systematic reviews of the analgesic effects of paracetamol in randomised, placebo‐controlled trials. Conduct of systematic reviews was assessed with AMSTAR‐2; confidence in effect estimates (quality of evidence) was assessed with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria. Data sources: MEDLINE, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews; systematic reviews published 1 January 2010 – 30 April 2020. Data synthesis: We extracted pain and adverse events outcomes from 36 systematic reviews that assessed the efficacy of paracetamol in 44 painful conditions. Continuous pain outcomes were expressed as mean differences (MDs; standardised 0–10‐point scale); dichotomous outcomes were expressed as risk ratios (RRs). There is high quality evidence that paracetamol provides modest pain relief for people with knee or hip osteoarthritis (MD, –0.3 points; 95% CI, –0.6 to –0.1 points) and after craniotomy (MD, –0.8 points; 95% CI, –1.4 to –0.2 points); there is moderate quality evidence for its efficacy in tension‐type headache (pain‐free at 2 hours: RR, 1.3; 95% CI, 1.1–1.4) and perineal pain soon after childbirth (patients experiencing 50% pain relief: RR, 2.4; 95% CI, 1.5–3.8). There is high quality evidence that paracetamol is not effective for relieving acute low back pain (MD, 0.2 points; 95% CI, –0.1 to 0.4 points). Evidence regarding efficacy in other conditions was of low or very low quality. Frequency of adverse events was generally similar for people receiving placebo or paracetamol, except that transient elevation of blood liver enzyme levels was more frequent during repeated administration of paracetamol to patients with spinal pain (RR, 3.8; 95% CI, 1.9–7.4). Conclusions: For most conditions, evidence regarding the effectiveness of paracetamol is insufficient for drawing firm conclusions. Evidence for its efficacy in four conditions was moderate to strong, and there is strong evidence that paracetamol is not effective for reducing acute low back pain. Investigations that evaluate more typical dosing regimens are required. PROSPERO registration: CRD42015029282 (prospective).

Christina Abdel Shaheed · Giovanni E Ferreira · Alissa Dmitritchenko · Andrew J McLachlan · Richard O Day · Bruno Saragiotto · Christine Lin · Vicki Langendyk · Fiona Stanaway · Jane Latimer · Steven Kamper · Hanan McLachlan · Harbeer Ahedi · Christopher G Maher

To the Editor: This retrospective population‐based study aimed to determine the incidence of type 2 diabetes from 2012 to 2019 in Western Australian youth aged under 16 years, and to examine temporal trends between 2000 and 2019, using data from the Western Australian Children’s Diabetes Database (WACDD).1 The data extracted for eligible patients diagnosed with type 2 diabetes, according to standard criteria,2 included diagnosis year, age, sex and self‐reported Aboriginal or Torres Strait Islander status. Poisson regression was used to determine incidence rates and trends by calendar year, sex, and Aboriginal or Torres Strait Islander status. This study received ethics approval from the Western Australian Child and Adolescent Health Service Human Research Ethics Committee (RGS0000002386). To ensure the validity of our findings, a secondary aim was to estimate completeness of the WACDD for type 2 diabetes diagnosed in patients aged under 16 years from 1999 to 2016. For this purpose, we used the capture–recapture method with two independent sources: the primary source was WACDD, and the secondary source was the National Diabetes Services Scheme (NDSS) database.3 We identified 224 eligible cases from WACDD (2000–2019), of which 129 (58%) were girls and 128 (57%) were Aboriginal or Torres Strait Islander children. The mean age at diagnosis of type 2 diabetes was 13.2 years (standard deviation, 2.0 years), with no differences observed by sex or Aboriginal or Torres Strait Islander status. The overall mean incidence was 2.3/100 000 (95% CI, 2.1–2.7), with an average annual increase of 5.2% (95% CI, 2.8–7.8%). No differences were observed in the mean incidence or incidence rate trends between boys and girls. The mean incidence in Aboriginal or Torres Strait Islander children was 18‐fold higher (incidence rate ratio, 18.31; 95% CI, 14.05–23.86) than in non‐Aboriginal or Torres Strait Islander children (Box). In addition, the incidence increased by an annual average of 6.2% (95% CI, 2.8–9.6%) in Aboriginal or Torres Strait Islander children compared with 3.9% (95% CI, 0.3–7.6%) in non‐Aboriginal or Torres Strait Islander children (Box). Of the 170 eligible cases identified in the WACDD, 107 were ascertained from both WACDD and NDSS, 40 from NDSS only, and 63 from WACDD only. Using the capture–recapture method,3 the WACDD was estimated as 73% complete. This study provides further evidence for the growing incidence of type 2 diabetes in Australian children and highlights the urgent need for community, public health providers, and government to address this disease and its significant burden in young people.4,5 Box – Case numbers, person years of observation, mean incidence (95% CI) and average annual increase in incidence (95% CI) by Aboriginal or Torres Strait Islander status for youth aged under 16 years diagnosed with type 2 diabetes in Western Australia (2000–2019) Non‐Aboriginal or Torres Strait Islander Aboriginal or Torres Strait Islander Combined Cases 96 (43%) 128 (57%) 224 (100%) Sex, female 54 (56%) 75 (59%) 139 (58%) Mean age at diagnosis (SD), years 13.6 (1.8) 13.0 (2.1) 13.2 (1.9) Age range at diagnosis, years 6.9–15.9 6.8–15.9 6.8–15.9 Total person years 8 884 383 644 157 9 528 540 Mean annual incidence (95% CI) per 100 000 person years 1.1 (0.9–1.3) 19.9 (16.6–23.6) 2.3 (2.1–2.7) Average annual increase in incidence (95% CI) 3.9% (0.3–7.6%) 6.2% (2.8–9.6%) 5.2% (2.8–7.8%) CI = confidence interval; SD = standard deviation.

Aveni Haynes · Jacqueline A Curran · Elizabeth A Davis

A multilayered action plan is needed for a substantial, timely and sustained investment in dementia prevention In 2012, the Australian Government declared dementia as the ninth National Health Priority Area. Eight years later, dementia is the greatest cause of disability in Australians aged over 65 years, the second leading cause of mortality, and the highest in women.1 Today, more than 459 000 Australians live with dementia, and this number is expected to exceed one million by 2056.2 The societal, economic and health care burden of dementia is unprecedented, with significant impacts on individuals, caregivers and families. In addition to therapeutic advances, improved and timely diagnosis and coordinated person‐centred care, dementia prevention and risk‐factor management are our best chance to make a difference.3 How do we tackle dementia prevention cost‐effectively in the post‐pandemic era? Between 40% and 48% of dementia risk is considered modifiable.4,5 In Australia, the population‐attributable risk of dementia risk factors, in descending order, are physical inactivity (17.9%), mid‐life obesity (17.0%), low educational attainment in early life (14.7%), mid‐life hypertension (13.7%), depression (8.0%), smoking (4.3%), and diabetes mellitus (2.4%).5 In addition, the 2020 Lancet Commission report on dementia prevention, intervention and care4 includes hearing loss, traumatic brain injury, alcohol use, social isolation, and air pollution as risk factors. Emerging research suggests that a suboptimal diet,6 cognitive inactivity7 and sleep–wake disturbance8 also influence the modifiable dementia risk. We urge substantial, timely, and sustained investment in dementia prevention via a multilayered action plan with eight recommendations (Box). 1. Create public health and clinical practice guidelines for dementia prevention across the lifespan for the Australian setting. In 2019, the World Health Organization released dementia risk‐reduction guidelines stating that “the existence of potentially modifiable risk factors means that prevention of dementia is possible through a public health approach”.9 These guidelines focus on “interventions that delay or slow cognitive decline or dementia,” with the strongest recommendations being applied to addressing physical inactivity, tobacco cessation, hypertension and diabetes mellitus.9 Yet, in Australia, we do not have dementia prevention guidelines, with the clinical practice guidelines for dementia from the National Health and Medical Research Council (NHMRC) and the Australian Cognitive Decline Partnership Centre (CDPC) focusing on diagnosis and management.10 Since then, Australia has made significant progress by including dementia prevention guidelines for general practitioners in the CDPC’s Care guide for general practice.11 We recommend extending guidelines beyond primary care, including secondary prevention in memory clinics, prioritising educational attainment in early life, and developing occupational and environmental policy to reduce hearing loss, traumatic brain injury, and air pollution. 2. Equip and resource primary care providers to be the clinical spearheads for dementia prevention throughout life. Primary care is the usual entry point and key coordinator of care within the health care system and is well positioned to spearhead dementia prevention throughout life. The Medicare Benefits Schedule should increase focus on dementia prevention, enabling primary care, specialists, and allied health professionals more time, resources and team care. This could be achieved through new Medicare Benefits Schedule item numbers and modification of existing items, such as the 45–49‐year‐old health check for individuals at risk of chronic conditions. Private health insurers could complement this by expanding the scope of preventive health services to target dementia risk factors and rewarding individuals who participate with lower insurance premiums or greater rebates for health services. 3. Support multidisciplinary memory clinics and specialists to implement secondary prevention programs for those at high risk. Memory clinics and specialists should focus on secondary prevention for people at higher risk, such as those with mild cognitive impairment.12 The Australian Dementia Network (ADNeT) aims to unite and build the network of memory clinics, establish practice guidelines, harmonise assessments, and implement dementia prevention tools and strategies. ADNeT will also facilitate access to clinical trials, improve diagnostic accuracy to aid secondary prevention approaches and introduce a Clinical Quality Registry. 4. Fund research for evidence‐based interventions for modifiable risk factors for dementia across the life cycle to reduce the evidence‐to‐practice gap. While there has been increasing funding for dementia prevention research and the establishment of the International Research Network on Dementia Prevention as part of the Australian Government’s commitment to the World Dementia Council,13 urgent funding is still required to address critical evidence‐to‐practice gaps. The current evidence base includes observational studies and intervention trials that have generally focused on cognitive outcomes, rather than dementia incidence, given the long time frames needed. We need to strengthen the evidence base on managing risk factors across different phases of the lifespan, such as the most effective doses and forms of interventions in large‐scale trials. Rigorously evaluated multidomain prevention trials that simultaneously target multiple risk factors may present the best value for money if shown to be effective and sustainable, particularly as they address risk factors that have an established evidence base for preventing other conditions. A number of these trials are already underway in Australia. 5. Implement findings from dementia risk reduction and implementation research through translation into health promotion programs. Implementation research will be key to translating the increasing evidence base for dementia risk reduction interventions into effective health promotion programs. The science of behaviour change will be critical given the evidence‐to‐practice gap. This emphasises the importance of co‐design to empower individuals to modify their risk. For health professionals, education and training on dementia risk factors and skills in motivational interviewing and behaviour change principles should be prioritised. 6. Strengthen dementia prevention public health campaigns embracing Australians’ diversity, particularly Aboriginal and Torres Strait Islander Australians. Australian‐specific dementia prevention guidelines that inform public health campaigns need to appeal to all Australians, embracing geographic, socio‐economic, cultural, linguistic, social, ethnic, age, gender, and sexual diversity. This is particularly important for Aboriginal and Torres Strait Islander people, for whom dementia prevalence is three to five times higher than the general population. These measures need to be equitable and not disadvantage vulnerable groups that may already have reduced access to resources. 7. Resource and coordinate a whole‐of-community approach including government, public and private health care, community services and education sectors to operationalise guidelines and multifaceted dementia prevention programs throughout life. Dementia prevention is everyone’s business. Successful public health and disease prevention campaigns have required a coordinated effort across all levels of the health sector, government, policy makers, non‐government organisations, research, education, industry and the community. Yet, many Australians do not believe that dementia risk can be reduced.14 Dementia prevention is complex due to stigma, literacy, and multifactor risks throughout life. The success of widely known public health campaigns in Australia (eg, Quit for Life and Slip, Slop, Slap) is attributable to their focus on behaviour change using a single behaviour or risk factor, informed by knowledge of barriers and enablers. The Dementia Australia Your Brain Matters campaign was targeted at raising public awareness for dementia, but this was not sustained beyond the funding period (2012–2015). The report from the Lancet Commission identifies educational attainment in early life as an impactful risk factor4 and this should be prioritised given its broader socio‐economic benefits. There are specific mid‐life (hearing loss, traumatic brain injury, hypertension, alcohol intake, obesity) and late‐life factors (smoking, depression, social isolation, physical inactivity, diabetes, air pollution) which offer opportunities for risk reduction across the lifespan.4 From a practical perspective, as many dementia risk factors are shared with other chronic conditions, particularly vascular risk factors, these may present the best opportunity for greatest impact. 8. Mobilise peak health advocacy bodies to promote and coordinate public health messaging on dementia risk factors that cut across chronic conditions. How do we ensure value for money and sustainability of dementia prevention public health campaigns? A unified approach with clear messaging communicated through media, community organisations, and health professionals promoting shared responsibility is crucial. An initial focus on risk factors with the highest population‐attributable risk (physical inactivity and midlife obesity) is recommended to improve wellbeing and reduce risk for multiple chronic conditions. They are also ideal for integrated programs given their overlap with vascular risk factors and successful campaigns (eg, smoking cessation). A key step is the coordination and pooling of resources between peak advocacy bodies such as Dementia Australia, Diabetes Australia, and the Heart Foundation, with clear messaging focusing on single risk factors that have multiple benefits. In clinical practice, this facilitates approaches that are tailored to an individual’s experiences and motivation. For example, motivation for increasing physical activity for one individual may arise from receiving a result of impaired glucose tolerance, while for another it may be the experience of having a family member living with heart disease or dementia. Australia has excellent health infrastructure and an international reputation for dementia prevention due to our depth of clinical, research, and knowledge translation expertise. If we are committed to achieving the ambitious targets of reduced dementia prevalence and incidence, we must shine a spotlight on dementia prevention across all levels of society. To achieve this, the National Health and Medical Research Council National Institute for Dementia Research (NNIDR) Dementia Prevention Special Interest Group proposes this Dementia Prevention Action Plan for Australia. It is time for a call to action in the fight against dementia: dementia prevention needs to be the next international public health area of focus, with Australia playing a leading role. Box – Dementia Prevention Action Plan

For the NHMRC National Institute for Dementia Research, Dementia Prevention Special Interest Group*

To the Editor: Influenza vaccination of residents and staff in aged care homes is recommended by national guidelines1 and has been demonstrated to decrease transmission and burden of infection.2 During the current coronavirus disease 2019 pandemic, influenza vaccination of both groups potentially also reduces the risk of mortality associated with influenza virus and severe acute respiratory syndrome coronavirus 2 co‐infection. We sought to evaluate uptake of influenza vaccination by residents and staff in public sector residential aged care services in Victoria, where non‐mandatory vaccination programs are currently used. There are 178 public sector residential aged care services in Victoria, with the majority located in rural communities. In 2018 and 2019, infection prevention staff in public sector residential aged care services were requested to complete a point prevalence survey of all residents on a set date and a period prevalence survey of all staff employed during the influenza season, in order to estimate vaccine uptake. A standardised data collection tool was used, with online submission of summary data via a secure portal hosted by the Victorian Healthcare Associated Infections Surveillance System Coordinating Centre. Consistent with quality assurance activities defined according to National Health and Medical Research Council recommendations, non‐identifiable aggregate data were collated by participating public sector residential aged care services to support quality improvement initiatives. Ethics approval was therefore not required.3 Of surveyed residents, 87% were vaccinated in both 2018 and 2019. Small proportions of residents declined vaccination or had unknown status. In 2018, 87% of surveyed staff were vaccinated, with 8% and 6% reported as declining vaccination or having unknown status, respectively. In 2019, 88% of surveyed staff were vaccinated, with 9% and 4% declining vaccination or having unknown status, respectively (Box). Public sector residential aged care services provide services for older people with complex care needs, representing a population at high risk for poorer clinical outcomes in the setting of influenza infection. Reassuringly, we observed high uptake of vaccination among surveyed residents, comparable to recently reported uptake in New South Wales aged care homes.4 Review of successful vaccination strategies would be beneficial to improve and sustain future programs in individual aged care homes. Our findings also reflect high uptake of vaccination by aged care staff. Looking ahead, mandatory vaccination of staff employed in Victorian hospitals and public sector residential aged care services is planned,5 and this will likely result in additional uptake.6 While we observed low proportions of staff to have unknown status or to decline vaccination, implementation of the new policy will require an ethical and legal focus on these groups, including reasons for acceptable declination and required workforce planning (eg, redeployment). Box – Influenza vaccination uptake by residents and staff in Victorian public sector residential aged care services, 2018–2019 Target population Year No. of facilities surveyed No. of residents or staff surveyed Vaccinated Declined Unknown Residents 2018 177 5162 4482 (87%) 357 (7%) 323 (6%) 2019 178 5082 4427 (87%) 302 (6%) 353 (7%) Staff 2018 177 12536 10894 (87%) 948 (8%) 694 (6%) 2019 175 13844 12181 (88%) 1179 (9%) 484 (4%)

Noleen J Bennett · Alex Hoskins · Leon J Worth

We must consider how we can support communities hosting vaccine efficacy trials

George S Heriot · Euzebiusz Jamrozik

Introduction: The 2001 Recommendations for clinical care guidelines on the management of otitis media in Aboriginal and Torres Islander populations were revised in 2010. This 2020 update by the Centre of Research Excellence in Ear and Hearing Health of Aboriginal and Torres Strait Islander Children used for the first time the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Main recommendations: We performed systematic reviews of evidence across prevention, diagnosis, prognosis and management. We report ten algorithms to guide diagnosis and clinical management of all forms of otitis media. The guidelines include 14 prevention and 37 treatment strategies addressing 191 questions. Changes in management as a result of the guidelines: A GRADE approach is used. Targeted recommendations for both high and low risk children. New tympanostomy tube otorrhoea section. New Priority 5 for health services: annual and catch‐up ear health checks for at‐risk children. Antibiotics are strongly recommended for persistent otitis media with effusion in high risk children. Azithromycin is strongly recommended for acute otitis media where adherence is difficult or there is no access to refrigeration. Concurrent audiology and surgical referrals are recommended where delays are likely. Surgical referral is recommended for chronic suppurative otitis media at the time of diagnosis. The use of autoinflation devices is recommended for some children with persistent otitis media with effusion. Definitions for mild (21–30 dB) and moderate (> 30 dB) hearing impairment have been updated. New “OMapp” enables free fast access to the guidelines, plus images, animations, and multiple Aboriginal and Torres Strait Islander language audio translations to aid communication with families.

Amanda J Leach · Peter S Morris · Harvey LC Coates · Sandra Nelson · Stephen J O'Leary · Peter C Richmond · Hasantha Gunasekera · Samantha Harkus · Kelvin Kong · Christopher G Brennan‐Jones · Sam Brophy‐Williams · Kathy Currie · Sumon K Das · David Isaacs · Katherine Jarosz · Deborah Lehmann · Jarod Pak · Hemi Patel · Chris Perry · Jennifer S Reath · Jessica Sommer · Paul J Torzillo

Early control of transmission was successful, but efforts to reduce further transmission remain important

Heather F Gidding · Dorothy A Machalek · Alexandra J Hendry · Helen E Quinn · Kaitlyn Vette · Frank H Beard · Hannah S Shilling · Rena Hirani · Iain B Gosbell · David O Irving · Linda Hueston · Marnie Downes · John B Carlin · Matthew VN O'Sullivan · Dominic E Dwyer · John M Kaldor · Kristine Macartney

Medicare Benefits Schedule (MBS) data indicated that there were 37% fewer screening procedures for breast cancers and 55% fewer for colorectal cancers in April than in March 2020.1 We examined the temporal relationship between coronavirus disease 2019 (COVID‐19)‐related restrictions in Victoria during 1 April – 15 October 2020 and cancer pathology notifications to the Victorian Cancer Registry (VCR), to estimate their impact on cancer diagnoses. Victorian legislation requires pathology services to notify reportable cancer diagnoses to the VCR.2 The E‐Path system, installed in all Victorian pathology services during 2013–2018,3 automatically transmits notifications to the VCR together with pathologist report authorisations. During 2019, 97 313 of 104 025 cancer pathology notifications to the VCR (94%) were received via E‐Path (data supplied by author LB). Changes to the E‐Path system during 2019 meant that we were unable to directly compare notification numbers for 2019 and 2020. We therefore modelled cancer incidence during 2014–2018 by Poisson regression. A spline function was fitted to VCR cancer incidence data for weeks 1–52, adjusted for day type (working or non‐working day/public holiday) and year, and the fitted curve used to predict daily incidence during 7 January – 15 October 2020. Predicted incidence was re‐scaled to estimate expected notification numbers; the scale factor was the number of notifications during the baseline period — 1 February – 16 March 2020, allowing a two‐week washout period before restrictions were formally announced — divided by the predicted incidence during this period. Observed and predicted notification numbers were compared using Poisson regression, with the expected number as an offset term, enabling estimation of relative reductions with 95% confidence intervals (CIs). Differences between predicted and actual notification numbers were estimated, both overall and for specific groups (eg, by tumour or age group), based on the pertinent incidence data. As a single cancer diagnosis can be associated with several pathology notifications, the number of undiagnosed cancers was estimated by multiplying the difference in notification numbers by the ratio of newly diagnosed tumours to pathology notifications in 2018 (Supporting Information, table 1). The confidence interval for the number of undiagnosed cases was based on the Poisson model, keeping the ratio of newly diagnosed tumours to pathology notifications constant. In sensitivity analyses, data were fitted to polynomial models, different baseline periods were used, or data were restricted to reportable cancer diagnoses. The study was exempted from formal ethics review by the human research ethics committee of Cancer Council Victoria. During 1 April – 15 October 2020, there were 5446 fewer notifications of new cancer diagnoses than predicted by our primary model (predicted, 54 609 v observed, 49 163; relative reduction, –10.0%; 95% CI, –10.8% to –9.2%) (Supporting Information, figure 1); we estimated that there were 2530 undiagnosed cancers (95% CI, 2327–2731). The relative reduction was greatest during 1 April – 4 May 2020 (Box 1). By tumour group, the relative reductions were most marked for prostate cancer, head and neck tumours, melanoma, and breast cancer; they were greater for men, people aged 50 years or more, and for people in areas of higher socio‐economic position (Box 2). The pattern of difference in notifications varied between tumour groups (Supporting Information, figure 2). The 6.5‐month period of COVID‐19‐related restrictions in Victoria was accompanied by a 10% reduction in cancer pathology notifications; we estimated that about 2530 cancer diagnoses were either delayed or missed. The impact of delayed diagnosis is greatest for patients with aggressive cancers. Changes in care delivery during the restrictions, including suspension of screening services and outpatient clinics and postponed surveillance of existing cancers, may have affected notification numbers for some tumour groups and consequently the estimated number of delayed diagnoses. Planning for a possible surge in cancer diagnoses over the coming 6–12 months, and media campaigns encouraging people to not further delay seeking medical attention, may ameliorate any negative impact of delayed cancer diagnosis. Box 1 – Cancer pathology notifications to the Victorian Cancer Registry, January–October 2020: observed (red) and predicted numbers (green), by day type LOESS = locally estimated scatterplot smoothing. The grey area marks the baseline period, the vertical dotted lines the analysis period for predicted notifications. A state of emergency was declared in Victoria on 16 March 2020. Stage 3 movement restrictions were applied from 30 March, eased on 13 May, and re‐applied from 8 July. The state of emergency was renewed on 2 August, together with application of stage 4 restrictions to metropolitan Melbourne until their easing from 19 October. For further details, see the footnote to figure 2 in the online Supporting Information. Box 2 – Cancer pathology notifications and estimated numbers of undiagnosed reportable cancers, 1 April – 15 October 2020* table#t2 tbody td:nth-child(n+2) P. Pleft { text-align: center; } Notifications Relative difference (95% CI) Absolute difference (a) Tumour to notification ratio (b) Estimated number of undiagnosed tumours (a*b) Characteristic Predicted Observed All notifications 54 609 49 163 –10.0% (–10.8% to –9.2%) –5446 0.465 2530 Sex† Males 15 458 14 190 –8.2% (–9.7% to –6.7%) –1268 0.427 541 Females 10 408 10 367 –0.4% (–2.3% to 1.5%) –41 0.434 18 Age at diagnosis (years) < 50 9981 9674 –3.1% (–5.0% to –1.1%) –307 0.454 139 50–74 30 949 27 555 –11.0% (–12.0% to –9.9%) –3394 0.447 1516 ≥ 75 13 697 11 934 –12.9% (–14.4% to –11.3%) –1763 0.514 906 Tumour group Breast 7923 7130 –10.0% (–12.1% to –7.9%) –793 0.380 301 Colorectal 5063 4838 –4.4% (–7.1% to –1.7%) –225 0.501 113 Haematologic 10 011 9321 –6.9% (–8.8% to –5.0%) –690 0.234 162 Melanoma 7168 6217 –13.3% (–15.4% to –11.1%) –951 0.538 511 Lung 2967 3062 3.2% (–0.4% to 6.9%) 95 0.483 –46 Head and neck 1363 1155 –15.3% (–20.0% to –10.3%) –208 0.504 105 Bladder 2159 2009 –6.9% (–10.9% to –2.8%) –150 0.370 56 Prostate 6417 4770 –25.7% (–27.8% to –23.5%) –1647 0.560 922 All other 11 931 10 661 –10.6% (–12.3% to –8.9%) –1270 0.546 693 Socio‐economic position (quintile)‡ 1 (most disadvantaged) 10 334 9789 –5.3% (–7.1% to –3.4%) –545 0.453 247 2 10 378 9447 –9.0% (–10.8% to –7.1%) –931 0.456 425 3 10 192 9624 –5.6% (–7.4% to –3.7%) –568 0.488 277 4 10 925 9463 –13.4% (–15.1% to –11.6%) –1462 0.455 665 5 (least disadvantaged) 11 385 9714 –14.7% (–16.4% to –13.0%) –1671 0.460 769 Remoteness¶ Major cities 37 506 33 753 –10.0% (–11.0% to –9.0%) –3753 0.461 1731 Inner regional 13 414 12 031 –10.3% (–11.9% to –8.7%) –1383 0.472 652 Outer regional/remote 2553 2457 –3.8% (–7.5% to 0.1%) –96 0.472 45 CI = confidence interval. * Poisson regression (spline function, adjusted for day type [working day or non‐working day/public holiday] and year; baseline period: 1 February – 16 March 2020). † For cancers common in both sexes (melanoma, colorectal cancer, lung, head and neck cancers, haematological malignancies). ‡ Based on residential address, using the Google Geocoding API (https://developers.google.com/maps/documentation/geocoding/overview), spatially joined to Australian Bureau of Statistics Statistical Area 1 (SA1) polygons.4 Area‐based socio‐economic quintiles were based on 2016 Australian Bureau of Statistics census data.5 ¶ Accessibility and Remoteness Index of Australia.6

Luc te Marvelde · Rory Wolfe · Grant McArthur · Louis A Blake · Sue M Evans

Investigator‐initiated trials run by clinical trial networks provide net economic benefits to health systems Delivery of optimal health care relies on evidence from randomised clinical trials, among other factors, to inform best practice. While the generation of such evidence requires resources, both national and international assessments of health and economic benefits resulting from medical research indicate large returns on investment.1,2,3 In Australia, during the decade 2006–2015, more than 10 000 clinical trials were conducted through Australian clinical trials networks (CTNs), including more than 5 million participants, ranking Australia in the top tier of clinical trial activity.4 Industry‐funded clinical trials accounted for an estimated $930 million of the total $1.1 billion spent annually on clinical trials, with National Health and Medical Research Council (NHMRC) funding accounting for about $164 million annually.4 While the proportion of funding for non‐industry‐sponsored investigator‐initiated clinical trials (IITs) is relatively small, these studies account for more than half of Australia’s clinical trial activity.4 This study funding balance is similar to what is reported elsewhere.5 In Australia, IITs conducted by Australasian CTNs have had a major impact on the improvement of health care quality and outcomes around the world.6,7 IITs are designed and conducted by independent clinicians and academic researchers to generate clinical evidence to improve health care. Benefits are multilayered and not restricted to the discovery of new therapies. Much of the benefit comes from identifying and addressing uncertainty in existing practices; evaluating a range of treatment options that address key unanswered questions free of commercial imperatives, identifying alternative and potentially more efficient diagnostic strategies; and identifying more effective models of care or expensive interventions that are no more active than the lower cost alternative. Australasia has large, geographically dispersed CTNs across multiple clinical areas,8 with many more having been launched since the original report (personal communication Australian Clinical Trials Alliance [ACTA]). Between one‐quarter and one‐third of all Australian Government‐funded NHMRC support for clinical trials between 2004 and 2014 was awarded to IITs conducted by an established CTN.8 CTNs ensure clinically important, high priority and relevant research questions are appropriately conducted and provide efficiency through established infrastructure. Within Australasia, CTNs are widely regarded as key drivers of innovation and represent good value for public investment.8 Although the Australian Government invests in IITs and the CTNs that coordinate them, their value has not been well characterised. Governments are increasingly looking to systematically integrate activities that generate high quality evidence (such as IITs) with other aspects of the health care system (such as measurement of health outcomes or development of safety and quality policies) to build self‐improving, sustainable systems (Box). Understanding the potential return on investment is therefore paramount. In 2015, ACTA and the NHMRC profiled 37 established CTNs in Australia.8 Subsequently, a cost–benefit analysis for the profiled networks was calculated for those that i) were operational for more than 10 years; ii) had conducted more than five high impact peer‐reviewed IITs where an influence (or potential influence) on clinical practice and/or policy were identified (maturity); iii) received a significant proportion of funding from Australian funders (local investment); and iv) were available to participate (feasibility) in this analysis.9 Three CTNs that had conducted a total of 25 IITs were included in the analysis: the Australasian Stroke Trials Network (ASTN), the Interdisciplinary Maternal Perinatal Australasian Collaborative Trials (IMPACT) Network, and the Australian and New Zealand Intensive Care Society Clinical Trials Group (ANZICS CTG). Gross economic benefits across these CTNs were almost $2 billion, with the majority due to improvements in patient health outcomes ($1.4 billion), and 30% due to avoided health service costs — $453 million from the difference in outcomes and $127 million from differences in service costs. Gross costs, which included the cost of running the CTN, coordinating centre costs and the cost of running the entire IIT program in each CTN, were about $335 million, with most of those costs being for the IIT program itself (accounting for 73% of total costs). The benefit to cost ratio was 5.8:1 if findings from the 25 IITs were implemented in 65% of the eligible Australian population for one year.9 Similar findings have been reported internationally, with studies in the United States reporting a benefit to cost ratio of 4.2:1 over 10 years.3 In the United Kingdom, randomised clinical trials funded under the National Institute for Health Research health technology assessment program were expected to have a net benefit of £3 billion, with just 12% of this benefit required to cover the costs for all research undertaken.10 In the Australian analysis, funding provided to run a portfolio of IITs did not cover the total costs within either a CTN or at an individual IIT level, and in‐kind support was relied upon to make up the shortfall. The NHMRC funding received by all Australasian CTNs between 2004 and 2014 was represented by just 9% of the $2 billion gross benefit.9 The magnitude of avoided health care costs appears large, reflecting the size of health care expenditure. The Australian analysis highlighted the importance of in‐kind support within CTNs not only to sustain the viability of the CTNs but for their ability to conduct individual IITs.9 The total quantum of site level, in‐kind support could not be quantified accurately during the study. However, this support was described as being finite, at capacity in many instances, and at risk of exhaustion. From a sustainability perspective, the reliance on in‐kind support is concerning, and undermines the timeliness, volume and international competitiveness of clinical research in Australasia. Anecdotal evidence from interviews suggested that site level in‐kind support represents up to a 50% increase in trial funding. Late‐phase IITs conducted by CTNs deliver better health outcomes and health service value through a variety of mechanisms. Importantly, IITs play a critical role in addressing clinically significant questions, influencing guidelines, and identifying ways to improve safety and quality and opportunities for more efficient resource use. As stated in a scoping review, IITs “can also yield a substantial knowledge return on investment for hospitals and institutions that actively engage in trials, including the following: more skilled clinicians and increased research capacity, improved patient outcomes, and better health system performance. Also, the difference in cost of care for trial and non‐trial patients can be negligible”.11 Large increases in the benefit to cost ratio could be realised through relatively small increases in implementation rates. Research to identify the barriers and enablers of trial implementation should allow IITs to be translated more effectively into frontline health care delivery. But, intuitively, the conduct of potentially practice‐changing IITs through CTNs is likely to enhance implementation rates, as these virtual, nationwide consortia of clinicians are likely to involve a majority of the relevant clinical community. Hence, the reasonable assumption that clinicians who participate in IITs are more likely to implement trial results in their own practice and to translate new knowledge to their clinical colleagues. What we do not yet know is the extent to which IITs translate into routine practice. This is rarely measured or monitored in Australia. Measures of implementation should be incorporated routinely into IIT design, particularly for randomised clinical trials that are arguably more likely to result in clinically significant and potentially practice‐changing findings. Notwithstanding the clear economic benefit demonstrated for the 25 trials conducted by the selected group of three CTNs, it might be possible to reduce trial costs further. The overall cost of trials is a complex, multilayered issue, particularly as small pilot studies are often required to demonstrate the feasibility of recruitment. But combined with the push to answer key questions more quickly especially for the seriously or critically ill patients, such considerations have been drivers in implementing newer adaptive trial designs, which have flexible sample sizes that might reasonably be expected to reduce clinical trial costs.12 The analysis conducted of the three selected CTNs represents the first such analysis conducted of the role of CTNs in the Australian health sector. Despite the limitations of the analysis, it is clear further investment in existing CTNs, as well as therapeutic areas for which there are no CTNs at present, is warranted. This needs to be done in a manner that seeks operational efficiencies, including consolidation of infrastructure and the means to ensure engagement with geographically dispersed health services to improve patient access to trials across communities.11 In conclusion, there is potentially enormous, and arguably untapped, value in investing in IITs conducted by CTNs, as they provide net benefits to health care systems. However, the exact return on investment is contingent on the level of implementation. Further work in this regard is warranted. So, where to from here? High quality health systems are reliant on a strong clinical trials sector. In particular, the role of IITs run by CTNs is paramount in order to address clinically important questions, especially those that relate to health care variation. Clinical trial infrastructure needs to be strengthened, and we must endeavour to reduce reliance on in‐kind funding to ensure that the sector remains viable. Finally, we must strive to maximise implementation of trial findings to optimise current investment in the sector. Box – A self‐improving, sustainable health care system

The joint ACTA/ACSQHC Working Group

Is the current genetics and insurance moratorium an effective long term regulatory solution for Australia? Genetic discrimination in life insurance is a longstanding issue in Australia,1,2 and has been the subject of two government inquiries.3,4 The use of genetic test results in underwriting continues to be self‐regulated by the life insurance industry.5 In 2019, following Parliamentary Joint Committee recommendations,4 the industry voluntarily introduced a moratorium restricting the use of genetic test results in life insurance underwriting for polices worth up to AU$500 000. Although the moratorium is an important step, concerns remain around the financial limits, public awareness, lack of government oversight and compliance monitoring. The impact and effectiveness of the moratorium needs evaluation to inform the planned 2022 review. A new research project has been funded by the Australian Government’s Genomic Health Futures Mission to serve that important function. Genomic testing has the potential to improve disease prevention and public health. For example, predictive testing of BRCA1/2 genes can identify women at high risk of developing breast and ovarian cancer, where risk can be mitigated through preventive surgery and/or screening. As genomic testing becomes more widespread, patients, general practitioners and other health professionals will increasingly be required to address issues related to privacy, data security, genetic discrimination and insurance.2,6 Although health insurance is community‐rated in Australia and therefore not subject to genetic discrimination,1 the use of genetic test results in life insurance is allowed under the Disability Discrimination Act 1992 (Cth). This means that life insurance companies can legally refuse coverage or increase premiums based on genetic test results. A number of ethical, social and medical implications arise when genetic test results are permitted to be used in insurance underwriting, especially predictive testing in otherwise healthy people.1,7 Previous studies show that fear of insurance discrimination deters individuals from taking clinically indicated genetic tests and participating in genetic research.1 In a study where predictive genetic testing for Lynch syndrome (which causes an increased risk of colorectal and other cancers) was offered, the proportion of people who declined testing when informed of the insurance implications was more than double the proportion who declined without knowledge of insurance implications.8 There are different concerns from the insurance industry perspective, including the possible actuarial implications of adding genomic information to risk models. Genomic test results can not only reveal risk (positive results), but also indicate reduced risk (negative results), potentially changing the dynamics of actuarial calculations. The notion of adverse selection, whereby individuals at high genetic risk may be more likely to take out insurance policies, is also raised by insurers. It is critical for the optimisation of genomic medicine that individuals can make informed choices about genetic testing and research participation without fear of insurance implications. Further, moral implications regarding the use of genetic information for insurance underwriting extend beyond actuarial fairness to include consideration of public interests such as justice, beneficence, autonomy and public health.7 Several governments internationally have therefore banned or restricted the use of genetic test results in risk‐rated insurance, including Canada, the United Kingdom and Europe, using various legal mechanisms.9 The National Health Genomics Policy Framework and Implementation Plan 2018–20216 is a strategic policy of the Council of Australian Governments, which recognises the potential of genomics for public health while acknowledging the need for ethical mechanisms for its delivery. Developing a national approach to issues including genetic discrimination was listed as a strategic priority for action in the Framework and listed as the first short term national priority in the implementation plan,6 making it one of the most significant ethical, legal and social issues facing genomic medicine in Australia. However, debate remains regarding the most effective mechanism of regulation. Following previous examination of these issues by the Australian Law Reform Commission and Australian Health Ethics Committee,3 a recent inquiry of the Parliamentary Joint Committee on Corporations and Financial Services into the life insurance industry considered the use of genetic test results in life insurance.4 The report expressed strong concerns about insurer access to genetic information and recommended that: a moratorium be implemented to “prohibit any life insurers from using the outcomes of predictive genetic tests at least in the medium term … as a matter of some urgency and [in] a form similar to the United Kingdom’s Moratorium”;4 the Financial Services Council (FSC), together with the Australian Genetic Non‐Discrimination Working Group (of which the authors are members), assess the consumer impact of a moratorium; and the federal government monitor the implementation of, and adherence to, such a moratorium, and if needed, implement legislation on the issue. The Australian Government has not yet responded to the Parliamentary Joint Committee recommendations. However, the FSC, Australia’s peak national body for life insurers, introduced an industry‐led moratorium in July 2019. Under the moratorium, Australian consumers need no longer disclose their genetic test results when applying for policies up to $500 000 for death/total permanent disability, $200 000 for trauma/critical illness, and $4000/month for income protection cover.10 The moratorium applies to all genetic test results, including research results and results obtained from internet‐based direct‐to‐consumer tests, which are increasingly resulting in clinical referrals.11 Above these financial limits (which are cumulative across multiple policies), life insurers can still ask for, and use, any existing genetic test result, which can lead to refused or delayed cover, exclusions or increased premiums. However, insurers must not require applicants to undergo a genetic test. Applicants can choose to disclose a favourable genetic test result (showing that an individual with a family history of a genetic condition does not have the familial genetic variant) to offset the effects on underwriting of an adverse family history. The FSC moratorium is a self‐regulated industry standard which is not legally enforceable — insurance companies’ legal right to discriminate on the basis of genetic test results remains. By contrast, the UK moratorium (which commenced in 2001) is an agreement between the UK government and the Association of British Insurers. It applies to all life insurance policies without any financial limits, with only one exception for Huntington disease, a progressive, neurodegenerative genetic disorder. Predictive genetic test results for Huntington disease must be disclosed by individuals in the UK only when applying for cover worth over £500 000 (about AU$900 000).12 All other individuals can make informed decisions about whether to have genetic testing or participate in genomic research without concerns about insurance implications. The FSC moratorium is an important step towards consumer protection, but concerns remain around its financial limits, interpretation of its terms, and lack of compliance monitoring. The FSC moratorium has no government or independent regulatory oversight, and as recommended by the Parliamentary Joint Committee, there is a critical need to monitor its implementation and effectiveness. The FSC will review the moratorium and its terms in 2022, to consider amendment and/or extension beyond its current 2024 end date.10 Currently, there are no mechanisms in place to collect independent evidence from different stakeholder perspectives to inform this review and the Australian Government has not indicated any intention to do so directly. A new research project, funded by the first competitive round of the Genomic Health Futures Mission, part of the Australian Government’s Medical Research Future Fund,13 has now commenced to serve that critical function until 2023. The A‐GLIMMER (Australian Genetics and Life Insurance Moratorium: Monitoring the Effectiveness and Response) project brings together leading researchers, clinicians, patient groups, and policy experts in Australia to answer the question of whether the FSC moratorium is an adequate and effective long term regulatory solution for Australia. The project aims to address this question by collecting a range of quantitative and qualitative data after the implementation of the moratorium, from different stakeholders including consumers, health care professionals, researchers and the insurance industry. In some cases, the data collected will be directly comparable to similar data collected and published before the moratorium.14,15 The project has widespread support across the community. More than 20 project partners, including the FSC, and other supporting bodies have provided written support and pledged resources towards the study. The project is endorsed by the Victorian Department of Health and Human Services, the Human Genetics Society of Australasia and Australian Genomics, a collaborative national network of clinical, research, academic and community organisations dedicated to implementation of genomics for health and the development of appropriate genomics policy. The overarching aim of A-GLIMMER is to ensure sufficient evidence is collected in the coming years to inform government and the 2022 FSC review, to help determine the effectiveness of the FSC moratorium as a long term regulatory solution in Australia. See the Box for a summary of project aims. A‐GLIMMER is divided into four work streams, which will collect data from consumers, health professionals, research studies and the insurance industry. A final report will be compiled at the conclusion of the project, and will be provided to the federal government to assist with future policy decisions. Although the project will not conclude until 2023, its findings will help inform the proposed FSC review in 2022. Achieving an adequate policy solution to this issue in Australia is essential for ensuring optimal integration of genomics into Australian health care, engendering public trust and consumer participation in genomics, and paving the way to realise the many benefits of genomic medicine for Australia. Box – Aims of A‐GLIMMER (Australian Genetics and Life Insurance Moratorium: Monitoring the Effectiveness and Response) A‐GLIMMER will: assess dissemination and awareness of the Financial Services Council moratorium following its implementation describe the impact of the moratorium on consumers, health care, research and financial services evaluate the effectiveness of the self‐regulated Financial Services Council moratorium as a long term regulatory solution

Jane Tiller · Ingrid Winship · Margaret FA Otlowski · Paul A Lacaze

Objectives: To determine the age‐standardised prevalence of inflammatory bowel disease (IBD) in a metropolitan area of Sydney, with a focus on its prevalence among older people. Design, setting: Population‐based epidemiological study of people with IBD in the City of Canada Bay, a local government area in the inner west of Sydney, during 1 March 2016 – 10 November 2016. Participants: Patients diagnosed with confirmed IBD according to the Copenhagen or revised Porto criteria. Main outcome measures: Crude prevalence of IBD, including Crohn disease and ulcerative colitis; age‐standardised prevalence of IBD, based on the World Health Organization standard population; prevalence rates among people aged 65 years or more. Results: The median age of 364 people with IBD was 47 years (IQR, 34–62 years); 185 were women (50.8%). The crude IBD prevalence rate was 414 cases (95% CI, 371–456 cases) per 100 000 population; the age‐standardised rate was 348 cases (95% CI, 312–385 cases) per 100 000 population. The age‐standardised rate for Crohn disease was 166 cases (95% CI, 141–192 cases) per 100 000 population; for ulcerative colitis, 148 cases (95% CI, 124–171 cases) per 100 000 population. The IBD prevalence rate in people aged 65 years or more was 612 cases (95% CI, 564–660 cases) per 100 000, and for those aged 85 years or more, 891 cases (95% CI, 833–949 cases) per 100 000; for people under 65, the rate was 380 cases (95% CI, 342–418 cases) per 100 000. Conclusions: We found that the prevalence of confirmed IBD in a metropolitan sample was highest among older people. Challenges for managing older patients with IBD include higher rates of comorbid conditions, polypharmacy, and cognitive decline, and the immunosuppressive nature of standard therapies for IBD.

Aviv Pudipeddi · Jeffrey Liu · Viraj Kariyawasam · Thomas J Borody · James L Cowlishaw · Charles McDonald · Peter Katelaris · Grace Chapman · Crispin Corte · Daniel A Lemberg · Cheng H Lee · Anil Keshava · John Napoli · Robert Clancy · Webber Chan · Sudarshan Paramsothy · Rupert Leong

Current Good Clinical Practice guidelines are bureaucratic and should align with less burdensome examples of international trial policy

Tanya Symons · Steve Webb · John R Zalcberg

If we had a test that was both 100% sensitive and 100% specific for COVID-19, we would have no false-positive and no false-negative results

Katy JL Bell · Fiona F Stanaway · Les M Irwig · Andrea R Horvath · Armando Teixeira‐Pinto · Clement Loy

Models must be supported by a range of qualitative and quantitative assessments and tools to translate their projections into policy

Allen C Cheng

The consequences of removing some restrictions may not be apparent for more than two months

Nick Scott · Anna Palmer · Dominic Delport · Romesh Abeysuriya · Robyn M Stuart · Cliff C Kerr · Dina Mistry · Daniel J Klein · Rachel Sacks‐Davis · Katie Heath · Samuel W Hainsworth · Alisa Pedrana · Mark Stoove · David Wilson · Margaret E Hellard

To the Editor: Pandemic responses across the world have been highly reactive. However, there remain only three strategic options to managing coronavirus disease 2019 (COVID‐19): mitigation, suppression and elimination (Box).2 With the promise of efficacious new vaccines, mitigation is appropriately not considered as part of Australia’s national strategy. However, our stated goal of achieving “no community transmission” remains poorly defined and risks missing important distinctions between elimination and suppression.3 Effective elimination is dependent both on getting to zero local cases and then staying there, with any new transmission chains immediately halted. All jurisdictions of Australia have now achieved elimination over significant periods, even without articulating this as their strategy. By comparison to suppression, greater relaxation of restrictions may well be allowable under an elimination approach if vigilance is maintained, as New Zealand has demonstrated.4 Although the challenges of ensuring quarantine of returning travellers are well recognised, this is an essential aspect of maintaining elimination and increases in importance as distancing restrictions are eased. Australia’s current strategy appears to imply suppression, with some virus circulating but with case numbers at manageable levels. Whether suppression has been achieved can be monitored by maintaining an effective reproduction number of no greater than one, or equivalently by ensuring the epidemic curve of new community cases is not upsloping. Importantly, the reproduction number and the rate of new cases at any point in time are unrelated — we could have effective suppression and a reproduction number of one with daily case rates of five, ten or 50. Our definition of no community transmission appears to imply complete identification of transmission chains with no “mystery cases”, regardless of the number of new cases. These considerations are important in determining whether we have full visibility of the epidemic and effective contact tracing but do not determine the reproduction number. The rapid spread of the virus necessitates a public health strategy that is clear, robust and agile. Improved control combined with the increasingly clear seasonality of the virus5 suggest that control can be maintained throughout the summer. However, if vaccination has not been widely distributed before winter 2021 and we do not make clear choices, further major outbreaks remain likely. Box – Characteristics of coronavirus disease 2019 (COVID‐19) epidemic response strategies (Trauer et al) Elimination Suppression Mitigation Our definition No cases or transmission, except in quarantined arrivals Very low community case rates; limited transmission Higher case rates, but within health service capacity Key metric of success No locally acquired cases Effective reproduction number not exceeding one,* or a horizontal sloping epidemic curve of locally acquired cases Hospital and ICU occupancy within (expanded) capacity Accrual of significant population‐level immunity No No1 Yes, likely to take many months, with considerable morbidity and mortality Need for mobility restrictions and hygiene measures Mobility may return to near normal while cases and transmission remain at zero; vigilance essential; likely need for episodic restrictions if quarantine escape occurs Continuous need for high levels of restrictions; strong possibility of disruptive lockdowns given that community transmission persists Unpredictable Need for restrictions on international arrivals Extremely high, and increases as distancing restrictions are eased Moderate Less important Current appropriateness for Australian jurisdictions† Reasonable Reasonable Not under consideration ICU = intensive care unit. * The effective reproduction number becomes more difficult to quantify precisely as numbers fall. † Given an effective vaccine appears likely.

James M Trauer · Ben J Marais · Romain Ragonnet · Julian Savulescu · Emma S McBryde

Objectives: To investigate causes of death of people with cancer alive five years after diagnosis, and to compare mortality rates for this group with those of the general population. Design, setting, participants: Retrospective cohort study; analysis of South Australian Cancer Registry data for all people diagnosed with cancer during 1990–1999 and alive five years after diagnosis, with follow‐up to 31 December 2016. Main outcome measures: All‐cause and cancer cause‐specific mortality, by cancer diagnosis; standardised mortality ratios (study group v SA general population) by sex, age at diagnosis, follow‐up period, and index cancer. Results: Of 32 646 people with cancer alive five years after diagnosis, 30 309 were of European background (93%) and 16 400 were males (50%); the mean age at diagnosis was 60.3 years (SD, 15.7 years). The median follow‐up time was 17 years (IQR, 11–21 years); 17 268 deaths were recorded (53% of patients; mean age, 80.6 years; SD, 11.4 years): 7845 attributed to cancer (45% of deaths) and 9423 attributed to non‐cancer causes (55%). Ischaemic heart disease was the leading cause of death (2393 deaths), followed by prostate cancer (1424), cerebrovascular disease (1175), and breast cancer (1118). The overall standardised mortality ratio (adjusted for age, sex, and year of diagnosis) was 1.24 (95% CI, 1.22–1.25). The cumulative number of cardiovascular deaths exceeded that of cancer cause‐specific deaths from 13 years after cancer diagnosis. Conclusions: Mortality among people with cancer who are alive at least five years after diagnosis was higher than for the general population, particularly cardiovascular disease‐related mortality. Survivorship care should include early recognition and management of risk factors for cardiovascular disease.

Bogda Koczwara · Rosie Meng · Michelle D Miller · Robyn A Clark · Billingsley Kaambwa · Tania Marin · Raechel A Damarell · David M Roder

In Australia, colorectal cancer is the second most frequently diagnosed cancer and one of the most common causes of cancer‐related death.1 Evidence that bowel cancer screening reduces mortality through early detection and treatment2 led to the introduction in 2006 of the Australian National Bowel Cancer Screening Program (NBCSP), offering faecal occult blood testing. The NBCSP has been progressively rolled out, from covering those aged 55 or 65 years in 2006 to screening every two years for all Australians aged 50–74 years by 2020.3 During 2016–17, 41% of people invited to participate in screening did so.4 A recent review of the NBCSP found that the risk of death from colorectal cancer was lower for invitees, and that those who had cancer were diagnosed at an earlier stage of disease.5 In Australia, jurisdictional cancer registries do not collect data on surgery‐related morbidity. However, the Binational Colorectal Cancer Audit (BCCA) (https://www.bowelcanceraudit.com) has collected information since 2007 on the diagnosis, management, and outcomes of surgically managed Australian and New Zealand patients with colorectal cancer, as well as whether patients were identified by the NBCSP. BCCA data are voluntarily collected by 435 registered surgeons at 138 participating hospitals across Australia and New Zealand, covering about 24% of newly diagnosed cases of colorectal cancer in 2019.6 We sought to determine whether patients with surgically managed colorectal cancer diagnosed through the NBCSP have better post‐operative outcomes than those diagnosed in other pathways. We undertook a cross‐sectional analysis of de‐identified BCCA data for patients aged 18 years or over who underwent surgery in Australia for colorectal cancer during January 2007 – December 2018. Outcome measures were inpatient and 30‐day mortality; surgical complications; medical complications; return to theatre; and hospital length of stay. We undertook binary logistic regression to assess associations between screening and binary outcomes. The association with length of stay was assessed in ordinary least squares linear regression models. The Monash University Human Research Ethics Committee (project, 19327) and the BCCA Operations Committee provided ethics approval for our study. Of 23 310 cases of colorectal cancer in the database, we could include 15 630 cases with data on cancer type and screening status in our comparison of demographic and clinical characteristics. A larger proportion of patients identified by the NBSCP than of otherwise identified patients were men (58% v 54%); their mean age (64 years, standard deviation [SD], 7 years v 69 years; SD, 14 years) was lower, and larger proportions had American Society of Anesthesiologists (ASA) scores in the low risk range (77% v 59%), were from lower socio‐economic status areas, had presented for elective surgery (96% v 85%), had less advanced cancer stage disease (stages 0–II: 69% v 63%), and underwent minimally invasive surgery (80% v 66%) (Box 1). Data on adjusting variables and outcomes were available for the 11 366 cases included in our logistic regression models. NBSCP‐detected patients were less likely to have post‐operative surgical (adjusted odds ratio [aOR], 0.83; 95% confidence interval [CI], 0.69–0.99) or medical complications (aOR, 0.75; 95% CI, 0.59–0.94); their length of stay was also briefer (adjusted mean difference, –1.56 days; 95% CI, –2.06 to –1.06 days). Post‐operative mortality and return to theatre rates were similar for screened and other patients (Box 2). Our analysis of BCCA data indicates that, in addition to the lower long term mortality associated with the NBCSP,5 short term post‐operative benefits are also evident that should be taken into account when promoting the program. Our study reinforces calls to improve participation rates in the national screening program by eligible participants to optimise the value of this critically important initiative. Box 1 – Demographic and clinical features of 15 730 patients who underwent surgery for colorectal cancer in Australia, 2007–2018, by diagnostic pathway Identification of patients Characteristic Total NBSCP Other P Number of patients 15 730 1357 14 373 Age at surgery (years) Mean (SD) 69 (13) 64 (7) 69 (14) < 0.001 Range 18–100 50–75 18–100 50 or under* 1556 (10%) 77 (6%) 1479 (10%) 51–60 2433 (15%) 385 (28%) 2048 (14%) 61–70 4192 (27%) 651 (48%) 3541 (25%) 71–80 4473 (28%) 244 (18%) 4229 (29%) over 80 3073 (20%) 0 3073 (21%) Missing data 3 0 3 Sex 0.003 Women 7142 (45%) 563 (42%) 6579 (46%) Men 8586 (55%) 792 (58%) 7794 (54%) Missing data 2 2 0 American Society of Anesthesiologists score < 0.001 1–2 (low risk) 9205 (60%) 1000 (77%) 8205 (59%) 3–5 (high risk) 6033 (40%) 294 (23%) 5739 (41%) Missing data 492 63 429 Socio‐economic status (IRSD quintile) < 0.001 1 (most disadvantaged) 2470 (16%) 224 (17%) 2246 (16%) 2 2385 (16%) 221 (17%) 2164 (16%) 3 2957 (20%) 278 (22%) 2679 (19%) 4 3107 (21%) 288 (22%) 2819 (20%) 5 (least disadvantaged) 4153 (28%) 282 (22%) 3871 (28%) Missing data 658 64 594 Cancer type 0.50 Colon 11 287 (72%) 963 (71%) 10 324 (72%) Rectal 4443 (28%) 394 (29%) 4049 (28%) Operative urgency < 0.001 Elective 13 457 (86%) 1310 (96%) 12 147 (85%) Emergency 999 (6%) 11 (1%) 988 (7%) Urgent 1248 (8%) 36 (2%) 1212 (8%) Missing data 26 0 26 Cancer stage < 0.001 0 (cancer in situ) 699 (5%) 92 (7%) 607 (4%) I (local disease) 3728 (24%) 535 (41%) 3193 (23%) II (local disease) 4689 (31%) 278 (21%) 4411 (32%) III (nodal spread) 4437 (29%) 347 (26%) 4090 (29%) IV (metastatic disease) 1625 (11%) 42 (3%) 1583 (11%) X (not identifiable) 121 (1%) 16 (1%) 105 (1%) Missing data 431 47 384 Operative approach < 0.001 Minimally invasive surgery† 10 498 (67%) 1082 (80%) 9416 (66%) Open 5140 (33%) 269 (20%) 4871 (34%) Missing data 92 6 86 IRSD = Index of Relative Socioeconomic Disadvantage (Australian Bureau of Statistics); NBSCP = National Bowel Cancer Screening Program; SD = standard deviation. * National screening program participants are aged 50 years or more. † Laparoscopic, hybrid, conversion of laparoscopic, robotic and transanal total mesorectal excision. table#t1 tbody td:nth-child(n+2) P. Pleft { text-align: center; } table#t2 tbody td:nth-child(n+2) P. Pleft { text-align: center; } Box 2 – Logistic and linear regression analysis of the association between screening and outcomes for 11 366 patients with colorectal cancer, Australia, 2007–2018 Identification of patients NBSCP v other Outcome NBSCP Other Univariate regression: OR (95% CI) Multivariate regression: aOR* (95% CI) Number of patients 843 10 523 30‐day mortality† 2 175 0.14 (0.02–0.44) 0.31 (0.05–1.01) Surgical complications‡ 171 2494 0.82 (0.69–0.97) 0.83 (0.69–0.99) Medical complications§ 89 1889 0.54 (0.43–0.67) 0.75 (0.59–0.94) Returned to theatre 52 658 0.99 (0.73–1.31) 1.02 (0.75–1.37) Mean difference (95% CI) Adjusted mean difference* (95% CI) Length of stay (days), mean (SD) 7.27 (6.17) 9.62 (8.02) –2.34 (–2.90 to –1.79) –1.56 (–2.06 to –1.06) aOR = adjusted odds ratio; CI = confidence interval; NBSCP = National Bowel Cancer Screening Program; OR = odds ratio; SD = standard deviation. * Adjusted for age, sex, socio‐economic status, screen category, cancer type, American Society of Anesthesiologists score. † Within 30 days of surgery. ‡ Abdominal/pelvic collection, anastomotic leak, entero‐cutaneous fistula, wound dehiscence, wound infection, sepsis, ileus, small bowel obstruction, urinary retention, ureteric injury, splenectomy, post‐operative haemorrhage. § Including chest infection, cardiac complications, deep vein thrombosis, pulmonary embolus.

Sasha Taylor · Farhad Salimi · Arul Earnest · Alexander G Heriot · John R Zalcberg · Susannah Ahern

The MJA–Lancet Countdown on health and climate change was established in 2017, and produced its first Australian national assessment in 2018 and its first annual update in 2019. It examines indicators across five broad domains: climate change impacts, exposures and vulnerability; adaptation, planning and resilience for health; mitigation actions and health co‐benefits; economics and finance; and public and political engagement. In the wake of the unprecedented and catastrophic 2019–20 Australian bushfire season, in this special report we present the 2020 update, with a focus on the relationship between health, climate change and bushfires, highlighting indicators that explore these linkages. In an environment of continuing increases in summer maximum temperatures and heatwave intensity, substantial increases in both fire risk and population exposure to bushfires are having an impact on Australia’s health and economy. As a result of the “Black Summer” bushfires, the monthly airborne particulate matter less than 2.5 μm in diameter (PM2.5) concentrations in New South Wales and the Australian Capital Territory in December 2019 were the highest of any month in any state or territory over the period 2000–2019 at 26.0 μg/m3 and 71.6 μg/m3 respectively, and insured economic losses were $2.2 billion. We also found growing awareness of and engagement with the links between health and climate change, with a 50% increase in scientific publications and a doubling of newspaper articles on the topic in Australia in 2019 compared with 2018. However, despite clear and present need, Australia still lacks a nationwide adaptation plan for health. As Australia recovers from the compounded effects of the bushfires and the coronavirus disease 2019 (COVID‐19) pandemic, the health profession has a pivotal role to play. It is uniquely suited to integrate the response to these short term threats with the longer term public health implications of climate change, and to argue for the economic recovery from COVID‐19 to align with and strengthen Australia’s commitments under the Paris Agreement.

Ying Zhang · Paul J Beggs · Alice McGushin · Hilary Bambrick · Stefan Trueck · Ivan C Hanigan · Geoffrey G Morgan · Helen L Berry · Martina K Linnenluecke · Fay H Johnston · Anthony G Capon · Nick Watts

Artificial intelligence is being used in several different ways to curb the current pandemic while demonstrating its potential to be even more effective for the next one

Ian A Scott · Enrico W Coiera

Hospitals in the Northern Territory often operate beyond capacity and serve a sparsely distributed population with rates of chronic disease and household overcrowding that are higher than in many other parts of Australia. The NT consequently adopted particularly strict public health measures to avert the potentially catastrophic consequences of community transmission of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), including supervised isolation until viral clearance of all people with confirmed SARS‐CoV‐2 infections (Supporting Information 1). This measure provided a unique opportunity to study the duration and trajectory of viral shedding in relation to clinical illness. In this article, we describe epidemiologic, clinical, and virological aspects of the first 28 cases of coronavirus disease 2019 (COVID‐19) in the NT. The Top End and Central Australian Human Research Ethics Committees approved the study (reference, 2020‐3737). Between 4 March and 4 April 2020, 28 cases of COVID‐19 were diagnosed in the NT, all linked to overseas or interstate travel. The median age of patients was 45.0 years (range, 1.5–75 years); 16 were women (Supporting Information 1, table). Two patients required supplemental oxygen, one of whom also required intubation. There were no deaths. Symptoms had been present for a median 3 days (range, 0–16 days) before oro‐nasopharyngeal swab collection and lasted a median 9.5 days (range, 4–18 days). Viral RNA could be detected by multiplex tandem real‐time polymerase chain reaction (PCR) assay (AusDiagnostics; Supporting Information 1) for a median 25 days after symptom onset (range, 14–41 days; interquartile range [IQR], 21–32 days), and in most patients for more than two weeks after symptom resolution (median, 17.5 days; range, 2–31 days; IQR, 14.5–22.5 days) (Box 1). Within‐patient variability in viral target cycle threshold values during follow‐up was considerable (Box 2; Supporting Information 1, figure), despite adequate and consistent amounts of human biologic material in test samples (data not shown). Prolonged compulsory isolation was distressing for several patients. The phylogeny of the 27 available NT viral genomes was consistent with acquisition in locations on all inhabited continents (Box 3). Five genetic clusters were evident (maximum of one single nucleotide polymorphism within each cluster) that were also epidemiologically linked by shared travel or household contact. The SARS‐CoV‐2 genomes from two independent travellers without epidemiologic connections were identical, but matched other publicly available genomes, highlighting the importance of interpreting genomic analyses in their epidemiologic context. The priority of the strict NT isolation requirements for patients with COVID‐19 was viral containment at a time when data on the duration of viral transmissibility were sparse. More recent evidence suggests that viable SARS‐CoV‐2 is rarely isolated more than 10 days after symptom onset,1,2,3 and requirements have consequently been eased, while maintaining supervised isolation with health management during the period of greatest infectivity. The high degree of temporal variability in viral shedding during follow‐up indicates that a single assay is not adequate for excluding infection in patients at epidemiologic risk of COVID‐19. The NT implemented particularly aggressive public health measures to contain SARS‐CoV‐2 transmission. Epidemiologic and genomic analyses suggest that this response has successfully prevented local community transmission of the virus. Box 1 – Time course of 28 cases of coronavirus disease 2019 (COVID‐19) diagnosed in the Northern Territory, 4 March – 4 April 2020 Each line represents a single patient. Day zero is the day of collection of the first SARS‐CoV‐2‐positive specimen; thickened sections indicate the period of COVID‐19 symptoms. Closed circles indicate positive SARS‐CoV‐2 assay results, hollow circles negative assay results. Patients 13 and 15 (lighter marking) required supplemental oxygen. The bottom line summarises the median duration of symptoms prior to diagnosis, the median duration of symptoms, and the median time to viral clearance. Box 2 – Multiplex tandem polymerase chain reaction cycle threshold values for detection of the SARS‐CoV‐2 open reading frame 1a gene (ORF1a) Box 3 – Maximum likelihood phylogenetic tree, depicting SARS‐CoV‐2 genomes from the Northern Territory and elsewhere SARS‐CoV‐2 = severe acute respiratory syndrome coronavirus 2. The phylogenetic tree shows that SARS‐CoV‐2 genomes in the Northern Territory (on the inner side of the outer ring) were drawn from across the range of genomes reported elsewhere (outer ring). NT travel‐related cases with epidemiologic links formed genomic clusters. Two cases without epidemiologic links also comprised a cluster, but the genomes were identical with overseas genomes. The context genomes were obtained from GISAID (https://www.gisaid.org), with region based on location of the submitting laboratory; the Wuhan‐Hu‐1 genome was used as an outgroup, and the scale bar indicates substitutions per site.

for the Northern Territory COVID‐19 Response Group

To the Editor: Travel restrictions to control the transmission of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), the virus that causes coronavirus disease 2019 (COVID‐19), were rapidly implemented in Australia. Despite its apparent efficacy, this proactive approach has been criticised as unscientific and in breach of the International Health Regulations. A recently published comment1 claimed that travel restrictions were implemented without supporting scientific evidence and had “been challenged by public health researchers”, citing research on Ebola and influenza. However, their interpretation is not consistent with an evidence‐based approach. When managing a novel infection, evidence‐based decision making should (i) use the best available relevant information that is generalisable to the novel infection — for example, an infection with a similar route of transmission; that is, not Ebola, but rather severe acute respiratory syndrome (SARS), influenza, and Middle East respiratory syndrome (MERS) — and (ii) clearly define the outcome of interest (eg, prevention v delay). A recent review2 of travel restrictions for emerging infectious diseases, including SARS and MERS, found only one study regarding coronaviruses. The evidence identified supports the use of air travel bans to prevent the spread of coronavirus epidemics.2 Furthermore, systematic reviews,3,4,5 including the review4 cited in the comment,1 have reported that travel restrictions delayed, but did not prevent, the spread of influenza.3,4 These delays were up to 4 months,4 and up to 10 months if implemented in combination with other local strategies.5 At the start of the COVID‐19 pandemic, this reflected the best available evidence to make evidence‐based decisions regarding travel restrictions. The evidence suggests that travel restrictions may, therefore, be used to delay and attenuate the peak in case numbers to reduce the burden on the health system, allowing for preparations to be made to better manage the outbreak. The preparation measures may include upskilling the health care workforce, building new facilities, improving access to laboratory testing and ventilators, and stockpiling personal protective equipment. This is the primary goal of travel restrictions as public health interventions. We conclude that Australia's rapid introduction of travel restrictions is consistent with an evidence‐based approach that prioritises the precautionary principle and saving lives.

Jessica Stanhope · Philip Weinstein

Modelling suggests that elimination could have been achieved if Victoria had gone into stage 4 lockdown immediately from 9 July Victoria is the unlucky state in a lucky country. Australian states and territories, other than New South Wales, have achieved elimination of community transmission of the sudden acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2): 28 days of no locally acquired cases where the source is unknown; twice the maximum incubation period. The situation in NSW is mixed. On one hand, NSW had ongoing case notifications of 10–20 per day in the month to mid‐August 2020, arising largely from imported cases from Victoria. On the other hand, on 16 July there had only been three locally acquired cases of SARS‐CoV‐2 infection with no known source in the preceding 28 days, suggesting NSW was on the cusp of elimination.1 If NSW successfully contains the current outbreak, it may resume its prior trajectory towards the elimination of local transmission, leaving Victoria isolated as the only state with community transmission. As of late August, Queensland is also experiencing community transmission — possibly ending its elimination status (28 days of no locally acquired cases where the source is unknown), subject to investigation of the new cases. It seems unlikely that states and territories that have eliminated local transmission will relinquish their status by freely opening borders and engaging with Victoria (and NSW if community transmission remains). Indeed, on 17 August the Queensland Premier stated: “Let me make it very clear, we will always put Queenslanders first and … we do not have any intentions of opening any borders while there is community transmission active in Victoria and in New South Wales”.2 Australia proceeding with two separate systems (six or seven states and territories having eliminated the virus, one or two not) is a significant concern. There are three general strategic policy responses to the challenge of coronavirus disease 2019 (COVID‐19): elimination, suppression, and mitigation (or herd immunity). No response is free of economic, social and health harms; rather, it is about minimising harm. Society has largely rejected a mitigation response because of concerns about the likely high morbidity and mortality arising from such a response. On 24 July, the Australian Health Protection Principal Committee recommended “that the goal for Australia is to have no community transmission of COVID‐19”,3 and on the same day Prime Minister Scott Morrison accepted and affirmed this recommendation, stating “The goal of that is obviously, and has always been no community transmission”.4 Unfortunately, this first clear statement that Australia's goal is to eliminate community transmission was late in coming, as the Victorian outbreak was already in full swing, with case numbers peaking at a 5‐day average of about 500 per day from 29 July to 5 August, resulting in a stage 4 lockdown in metropolitan Melbourne from 6 pm on 2 August. Elimination strategy We know from New Zealand (population, 5.0 million)5 and Taiwan (23.8 million)6 that elimination of community transmission is achievable in island jurisdictions, with NZ having no community transmission for 102 days until 11 August. The advantage of elimination is that despite international border closures or strict quarantine, citizens can go about life with a near‐normal functioning of their society and economy. Elimination presents challenges. First, there is the extra effort to achieve it, and the fact that aiming to achieve elimination does not guarantee success. Second, having achieved elimination, there is the constant risk of the virus re‐entering due to quarantine breaches (eg, the current outbreak in NZ). How frequently a COVID‐19‐free jurisdiction with tight border controls will retain elimination status is unclear, although we know that NZ lasted 102 days with no community transmission and that Western Australia, Northern Territory, South Australia, Australian Capital Territory, Queensland and Tasmania achieved over 100 days without a locally acquired case with no known source (although the status of Queensland is unclear as of early September). Was elimination achievable with a 6‐week stage 3 lockdown as implemented in Victoria from 9 July, or a more stringent lockdown? Lockdowns are effective for COVID‐19 pandemic control.7,8 Our case for an explicit elimination strategy in Victoria at lockdown commencement in early July was that given Victoria was going into a lockdown for 6 weeks, there was probably only a marginal extra cost of “going hard” with a rigorous public health response that increased the probability of achieving elimination. But was elimination achievable within 6 weeks? We examined four policy scenarios using an agent‐based model, a type of microsimulation of individuals. The model accurately reflects the prior experience of both NZ and Australia ( https://github.com/JTHooker/COVIDModel), and here we adapted it to Victoria (including the case counts up to 14 July; see Supporting Information for details). The four policy approaches, all simulated from 9 July 2020, were: Standard: reflecting the first Australian stage 3 lockdown (calibrated to case numbers as described at https://github.com/JTHooker/COVIDModel), with key parameters including 85% of people observing physical distancing; those observing physical distancing doing so 85% of the time; 30% of adult workers being essential workers; 93% of people asked to isolate doing so; 20% uptake of the COVIDSafe app; but no closure of schools and no mask wearing. Standard with masks at 50%: Standard, plus 50% of people wearing masks in crowded indoor environments. Stringent with masks at 50%: Standard with masks at 50%, plus schools closed and essential workers restricted to 20% of workers. Stringent with masks at 90%: Stringent, with mask use increased to 90% (ie, close to stage 4, which was implemented in Melbourne from 6 pm on 2 August after the 5‐day moving average case numbers increased from 300 to 500 in the first 3 weeks of stage 3). Box 1 shows the percentage likelihood of elimination in Victoria, defined as the date of clearance of infection by the last case, and the date of last acquisition of infection. The model is omniscient about infectious status; in the real world, based on a definition of 28 days of no cases, elimination would occur about 2 weeks after the clearance dates shown in Box 1, A. Under the “standard” policy approach (ie, equivalent to stage 3 without masks), there was no chance that all infected people would have cleared their SARS‐CoV‐2 infection by 19 August (6 weeks after lockdown commenced; Box 1, A). The probabilities for the other three policy approaches achieving elimination 6 weeks after implementation (Box 1, A) were 0% for “standard with masks at 50%”; about 4% for “stringent with masks at 50%”; and 30% for “stringent with masks at 90%”. The probabilities of the last actual infection occurring by 19 August were more encouraging at 0%, 1%, 45% and 90%, respectively (Box 1, B). Of particular note, given that the stage 3 lockdown imposed on 9 July failed because caseloads increased to an average of 500 per day, in our simulations 48% of the 1000 iterations of the “standard” scenario (stage 3, no masks) and 22% of the 1000 iterations for “standard with masks at 50%” had peaks in the first 3 weeks in excess of 400 per day. This is consistent with what eventuated, and further speaks (in hindsight) to the desirability of entering a stage 4 lockdown on 9 July; the “stringent with masks at 90%” scenario had no instances of peak cases greater than 400 per day in the first 3 weeks. Undertaking simulation modelling of SARS‐CoV‐2 policy options is challenging and the uncertainties are still considerable even when using the best estimates available. Nevertheless, our results lend weight to the proposition that elimination was achievable if Victoria had gone into stage 4 lockdown with mandatory wearing of masks immediately from 9 July. A ten‐point plan to maximise the chance of elimination in Victoria Box 2 lists enhancements to the stay‐at‐home orders of the 9 July lockdown. The first and critical point was leadership. As above, we did get a clear statement of an elimination goal from the Chief Health Officers (who comprise the Australian Health Protection Principal Committee membership) and Prime Minister Scott Morrison on 24 July, but with the benefit of hindsight it was perhaps too late. Target‐setting is still not occurring (eg, a target number of cases per day could be set for when we step out of stage 4 under both elimination and suppression strategy options). Moreover, an expert advisory group on elimination was not convened, limiting the capacity for an optimal evidence‐informed policy response. Nevertheless, since the 9 July lockdown, progress with other aspects of the ten‐point plan has been made with the closure of schools, mandatory mask wearing, and commitments to improve contact tracing capacity. Conclusion We argued in the preprint version of this article on 17 July that Melbourne and Victoria should not waste the opportunity that the (then) 6‐week lockdown presented and go hard and early. By learning from the lessons on social and preventive measures to lower SARS‐CoV‐2 transmissibility,7,8,12,14 and specifically the lessons from NZ,3 Taiwan and the six Australian jurisdictions that have achieved elimination, Victoria could have increased its chances of also eliminating community transmission. Our work and that of others who have independently considered the alternatives consistently demonstrates that elimination was possible, and if achieved would have been optimal for health and for the economy in the long term.15,16,17 In this article, we modelled the situation as at mid‐July — we are now updating modelling under the current situation. Authors’ note: This Perspective was submitted to the MJA on 16 July 2020 and published as a preprint on 17 July.9 The revised version, submitted on 23 August, retains the simulation modelling of the original but the uncertainty of inputs was updated to include uncertainty other than stochastic uncertainty. Our aim was rapid modelling to estimate the probability of virus elimination during the planned 6‐week stage 3 lockdown that Victoria had just commenced. The revised version was also published as a preprint on mja.com.au on 4 September, following full peer review and prior to typesetting, pagination and proofreading. Box 1 – Percentage likelihood of elimination of community transmission of SARS‐CoV‐2 infection in Victoria, by date of clearance of last active infection (A) and date of acquisition of last infection (B)* * Across 1000 Monte Carlo simulations in an agent‐based SEIR (susceptible, exposed, infectious, recovered) model. The vertical dashed line is the date 6 weeks after implementation of the lockdown policies. Compared with modelling published in the preprint version of this article,9 the only change here is the inclusion of additional parameter uncertainty in addition to stochastic uncertainty (see Supporting Information), resulting in increased sloping in the curves due to a wider range of potential parameter values (ie, the time distribution to elimination is wider). Box 2 – A ten‐point plan to maximise the chance of successful elimination of community transmission of SARS‐CoV‐2 in Victoria, based on the planned 6‐week lockdown from 9 July 2020 (as published on 17 July 2020)9 Strong and decisive leadership with strategic clarity. An explicit goal of elimination should be articulated, learning from the New Zealand experience (Prime Minister Jacinda Ardern, government ministers and senior officials).10 A clear set of targets for loosening of policies needs to be articulated, so citizens know what is likely to happen and when. Convene an advisory group of experts in the elimination strategy and SARS‐CoV‐2 public health response, reporting weekly to the Victorian Chief Health Officer, with the agenda, papers and minutes made publicly available. Close all schools. Although children do not usually suffer severe illness from SARS‐CoV‐2 infection, the virus still transmits between children and staff in schools.11 Accordingly, schools need to close until such time as the daily rate of SARS‐CoV‐2 infection without a known source falls beneath a target set by the Chief Health Officer. Tighten the definition of essential shops to remain open. Supermarkets and chemists need to remain open. However, department stores and hardware stores should be closed. A staged re‐opening based on set target levels of daily numbers of SARS‐CoV‐2 infection without a known source should then be implemented, so long as mask wearing by both staff and patrons is mandatory, along with hand sanitiser use on entry and exit from stores. Require mask wearing by Melbourne residents in indoor environments where 1.5 m physical distancing cannot be ensured, such as supermarkets and (especially) public transport. While no panacea, the wearing of masks reduces the chance of infected people spreading the virus.12 Tighten the definition of essential workers and work. There is currently a loose definition of who is an essential worker and what is essential work. This needs urgent tightening; for example, as per the NZ definitions used in their level 4 lockdown.13 Require mask wearing by essential workers whenever they are in close contact with people other than those in their immediate household. Ensure financial and other supports to businesses, community and other groups most affected by more stringent stay‐at-home and lockdown requirements, and provide enhancements, targeted where warranted, to programs such as JobKeeper and JobSeeker. Further strengthen contact tracing to ensure the majority of notifications (and their close contacts) are interviewed within 24 hours of the index case notification and placed in isolation if necessary. The use of smart phone and digital adjuncts needs to be improved, be that for initial contact tracing (eg, the COVIDSafe app, or a South Korean‐style use of telecommunications data) or monitoring of adequacy of isolation (eg, text message follow‐up, GPS monitoring, or electronic bracelets). Extend suspension of international arrivals into Victorian quarantine and divert resources. To allow a stronger focus on elimination within Victoria, extend the suspension of international arrivals to Victoria. Quarantine capacity can be redeployed for isolation of Melbourne residents infected with SARS‐CoV‐2 (and potentially high risk close contacts) if they do not have satisfactory home environments for self‐isolation.

Tony Blakely · Jason Thompson · Natalie Carvalho · Laxman Bablani · Nick Wilson · Mark Stevenson