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Objective To estimate the numbers of COVID‐19‐related hospitalisations in Australia after re‐opening the international border. Design Population‐level deterministic compartmental epidemic modelling of eight scenarios applying various assumptions regarding SARS‐CoV‐2 transmissibility (baseline R 0 = 3.5 or 7.0), vaccine rollout speed (slow or fast), and scale of border re‐opening (mean of 2500 or 13 000 overseas arrivals per day). Setting Simulation population size, age structure, and age‐based contact rates based on recent estimates for the Australian population. We assumed that 80% vaccination coverage of people aged 16 years or more was reached in mid‐October 2021 (fast rollout) or early January 2022 (slow rollout). Main outcome measures Numbers of people admitted to hospital with COVID‐19, December 2021 ‒ December 2022. Results In scenarios assuming a highly transmissible SARS‐CoV‐2 variant (R 0 = 7.0), opening the international border on either scale was followed by surges in both infections and hospitalisations that would require public health measures beyond mask wearing and social distancing to avoid overwhelming the health system. Reducing the number of hospitalisations to manageable levels required several cycles of additional social and mobility restrictions. Conclusions If highly transmissible SARS‐CoV‐2 variants are circulating locally or overseas, large and disruptive COVID‐19 outbreaks will still be possible in Australia after 80% of people aged 16 years or more have been vaccinated. Continuing public health measures to restrict the spread of disease are likely to be necessary throughout 2022.

There has historically been very little data on cycling in Australia. This lack of data has made it difficult to track whether cycling has changed over a long period of time. The number of cycling trips per day per person increased by 25.1% from the Day-to-Day Travel in Australia 1985/86 Survey to the 2011 National Cycling Participation Survey, while the Australian population 9 years of age and older has increased by 58.5%. The crude rate estimates a 20% reduction in cycling relative to population; however, this analysis does not account for changing Australian demographics during that time. When the rates of cycling are age-sex standardised, cycling trips in Australia increased by an estimated 11.0% (95% CI: 10.8%, 11.1%). The estimated increases in cycling trips, both in raw numbers and age-sex adjusted rates, support increased investments in cycling in Australia.

BackgroundPreventing avoidable venous-thrombo-embolism (VTE) is a priority to improve patient and service outcomes after total hip and total knee arthroplasty (THA, TKA), but compliance with relevant clinical guidelines varies. This study aims to determine the degree to which prophylaxis was compliant with Australian Orthopaedic Association (AOA) VTE prophylaxis guidelines and whether non-compliance is associated with increased risk of VTE.Methods A prospective multi-centre cohort study of adults with osteoarthritis undergoing primary TKA/THA was completed at 19 high-volume public and private hospitals. Data were collected prior to surgery and for one-year post-surgery. Logistic regression was undertaken to explore associations between non-compliance with AOA VTE prophylaxis guidelines and symptomatic 90-day VTE outcomes. ResultsData were analysed for 1838 participants from 19 sites. The rate of non-compliance with all clinical guideline recommendations was 20.1% (N = 369), with 14.1% (N = 259) non-compliance for risk-stratified prophylaxis, 35.8% (N = 658) for duration, and 67.8% (N = 1246) for other general recommendations. Symptomatic VTE was experienced up to 90-days post-surgery by 48 people (2.6%). Overall guideline non-compliance (AOR = 0.1, 95%CI = 0.0 to 0.4, p = 0.006) was associated with a lower risk of symptomatic 90-day VTE. Results were consistent when people with high bleeding risk were excluded (AOR = 0.13, 95% CI = 0.02 to 0.49, p = 0.005).ConclusionsNon-compliance with the AOA VTE prophylaxis guidelines was associated with fewer VTEs within 90 days of arthroplasty. This counterintuitive finding is concerning and necessitates a rigorous review of the AOA VTE prevention clinical guideline.

COVID-19 population vaccination programs are underway globally. In Australia, the federal government has entered into three agreements for the supply of vaccines, with roll-out beginning for the highest priority groups in February 2021. Expansion of the vaccination program throughout February and March failed to meet government targets and this has been attributed to international supply issues. However, Australia has local capacity to manufacture one million doses of the AstraZeneca vaccine weekly and once fully operational this will greatly increase the national vaccination capacity. Under current plans, these vaccine doses will be distributed primarily through a network of general practices, to be joined in later phases by community pharmacies. It remains unclear whether these small distribution venues have the logistical capacity to administer vaccines at the rate they will become available. To inform this discussion, we applied stochastic queue network models to estimate the capacity of vaccination sites based on assumptions about appointment schedules, service times and available staff numbers. We specified distinct queueing models for two delivery modes: (i) mass vaccination hubs located in hospitals or sports arenas and (ii) smaller clinics situated in general practices or community pharmacies. Based on our assumed service times, the potential daily throughput for an eight hour clinic at a mass vaccination hub ranged from around 500 vaccinations for a relatively small hub to 1,400 vaccinations a day for a relatively large hub. For GP vaccination clinics, the estimated daily throughput ranged from about 100 vaccinations a day for a relatively small practice to almost 300 a day for a relatively large practice. Stress tests showed that for both delivery modes, sites with higher staff numbers were more robust to system pressures, such as increased arrivals or staff absences, and mass vaccination sites were more robust that GP clinics. Our analysis is accompanied by an interactive web-based queue simulation applet, which allows users to explore queue performance under their own assumptions regarding appointments, service times and staff availability. Different vaccine delivery modes offer distinct benefits and may be particularly appealing to specific population segments. A combination of expanded mass vaccination hubs and expanded GP vaccination is likely to achieve mass vaccination faster than either mode alone.

The Australian Government’s COVID-19 vaccine rollout strategy is scheduled to commence in late February 2021 and aims to vaccinate the Australian adult population by the end of October 2021. The task of vaccinating some 20 million people within this timeframe presents considerable logistical challenges. Key to meeting this target is the rate of vaccine delivery: the number of vaccine doses that can be administered per day. In the opening phase, high priority groups will receive the Pfizer/BioNTech vaccine through hospital hubs at an initial rate of 80,000 doses per week. However, pending regulatory approval, the currently announced plan appears to be to distribute the AstraZeneca vaccine to the bulk of the popluation through a combination of general practices and community pharmacies. Here, we run a series of projections to estimate how long it will take to vaccinate the Australian population under different assumptions about the rate of vaccine administration as well as the schedule for second doses and prevalence of vaccine hesitancy. Our analysis highlights the ambitious rate of vaccine administration that will be neccessary to meet the Australian Government completion target of October 2021. A rate of 200,000 doses per day would comfortably meet that target; 80,000 doses a day would see roll-out extended until mid-2022. Speed is of the essence when it comes to vaccine rollout: protecting the population quickly will minimise the risk of sporadic and costly lockdowns lockdowns and the potential for small, local clusters getting out of control and sparking new epidemic waves. The government should gather all its resources to maximise the daily vaccination rate, ideally aiming to ramp up administration to at least 200,000 doses per day as quickly as possible. Quickly achieving and maintaining this pace will likely require dedicated large-scale vaccination sites that are capable of delivering thousands of doses a week in addition to the enthusiastic participation of GP practices and community pharmacies around the country. Lessons on the neccessary logistical planning, including coordination of delivery, ultra-cold-chain storage and staffing, can potentially be learned from Israel, where between 7,000 and 20,000 vaccinations per million population have been delivered daily throughout January.

Background Total hip and total knee replacement (THR/TKR) are common and effective surgeries to reduce the pain and disability associated with arthritis but are associated with small but significant risks of preventable complications such as surgical site infection (SSI) and venous-thrombo-embolism (VTE). This study aims to determine the degree to which hospital care was compliant with clinical guidelines for the prevention of SSI and VTE after THR/TKR; and whether non-compliant prophylaxis is associated with increased risk of complications. Methods and findings A prospective multi-centre cohort study was undertaken in consenting adults with osteoarthritis undergoing elective primary TKR/THR at one of 19 high-volume Australian public or private hospitals. Data were collected prior to surgery and for one-year post-surgery. Four adjusted logistic regression analyses were undertaken to explore associations between binary non-compliance and the risk of surgical complications: (1) composite (simultaneous) non-compliance with both (VTE and antibiotic) guidelines and composite complications [all-cause mortality, VTE, readmission/reoperation for joint-related reasons (one-year) and non-joint-related reasons (35-days)], (2) VTE non-compliance and VTE outcomes, (3) antibiotic non-compliance and any SSI, and (4) antibiotic non-compliance and deep SSI. Data were analysed for 1875 participants. Guideline non-compliance rates were high: 65% (VTE), 87% (antibiotics) and 95% (composite guideline). Composite non-compliance was not associated with composite complication (12.8% vs 8.3%, adjusted odds ratio [AOR] = 1.41, 95%CI 0.68–3.45, p = 0.40). Non-compliance with VTE guidelines was associated with VTE outcomes (5% vs 2.4%, AOR = 2.83, 95%CI 1.59–5.28,p < 0.001). Non-compliance with antibiotic guidelines was associated with any SSI (14.8% vs 6.1%, AOR = 1.98, 95%CI 1.17–3.62,p = 0.02) but not deep infection (3.7% vs 1.2%,AOR = 2.39, 95%CI 0.85–10.00, p = 0.15). Conclusions We found high rates of clinical variation and statistically significant associations between non-compliance with VTE and antibiotic guidelines and increased risk of VTE and SSI, respectively. Complications after THR/TKR surgery may be decreased by improving compliance with clinical guidelines.

Background Total hip and total knee arthroplasties are among the most common types of surgery performed in Australia today and are effective treatments for severe osteoarthritis. However, the increasing financial burden on the health system owing to the increasing rates of surgery has led to a growing interest in improving the cost-effectiveness and safety of arthroplasty care. This study was designed to quantify the association between post-operative complications, a major cost driver, and the cost of investigations following total hip or knee arthroplasty. Methods This is a prospective cohort study of consecutive patients undergoing primary total hip or knee arthroplasty at an Australian public hospital. We measured the number and cost of imaging and pathology tests performed during the acute hospital stay and used linear regression to quantify the association between complication status and investigation costs. Results Five hundred patients were included in the analysis. On average, those with complications received more tests, and more expensive tests. The mean combined cost of imaging and pathology tests in patients with no complications was AU$ 187 (SD: 12.0). In comparison, patients with minor complications had a mean additional cost of AU$ 270 (SD: 31.0), and those with major complications had a mean additional cost of AU$ 493 (SD: 54.2) (p Conclusions In patients undergoing hip or knee arthroplasty, investigation costs are substantially greater in the presence of either minor or major complications. With growing volumes of total hip and total knee arthroplasties, a potential focus of future research could include optimising investigation practices for patients with and without complications.

BackgroundIn an effort to contain the COVID-19 epidemic, many governments across the world have enforced lockdown or social distancing measures. Several outbreak models have been developed to investigate the effects of different public health strategies for COVID-19, but they have not been developed for Pakistan and other South East Asian countries, where a large proportion of global population resides.MethodsWe developed a stochastic individual contact model by extending the widely-used Susceptible-Infectious-Recovered (SIR) compartment model with additional compartments to model both anticipated mitigating effects of public health intervention strategies for Pakistan. We estimated the projected spread, number of hospitalizations, and case fatalities under no intervention and four increasingly stringent public health strategies of social distancing and self-isolation at the national and provincial levels of Pakistan.ResultsOur analysis shows that without any public health interventions the expected number of cumulative case fatalities is 671,596 in Pakistan with the virus is expected to peak in terms of the number of required ICU-hospitalizations at 198,593 persons by the end of the June 2020. The estimated total numbers of cumulative case fatalities are lower for other public health strategies with strict social distancing showing the lowest number of deaths at 1,588 (Self-isolation: n=341,359; Flexible social distancing strategy: n=3,995; and Exit strategy: n=28,214). The lowest number of required ICU-hospitalization is also estimated for strict social distancing strategy (n=266 persons at the end of May 2020). Generally, the simulated effects of the different public health strategies at the provincial-level were similar to the national-level with strict social distancing showing the fewest number of case fatalities and ICU-hospitalizations.ConclusionOur results indicate that case fatalities and ICU-hospitalizations for Pakistan will be high without any public health interventions. While strict social distancing can potentially prevent a large number of deaths and ICU-hospitalizations, the government faces an important dilemma of potentially severe economic downfall. Consideration of a temporary strict social distancing strategy with gradual return of the lower-risk Pakistani population, as simulated in our exit strategy scenario, may an effective compromise between public health and economy of Pakistani population.

Objective Wrist deformity in older people is common following treatment for a wrist fracture, particularly after non-surgical treatment. A cohort of older wrist fracture patients were surveyed by telephone regarding perceived deformity, bother with deformity and patient-reported wrist function. The objectives were to: (1) determine whether older patients with wrist fractures perceived a deformity of their wrist and if they were bothered by it; (2) test if there were associations between deformity and treatment-type and between deformity and function; (3) test for associations between bother and treatment-type and between bother and function; (4) measure the test–retest reliability of the ‘bother’ question. Results Of 98 eligible patients who were invited to participate, 41 responded. Out of 41, 14 (34%) believed they had a deformity and 4 (10%) reported that they were bothered by the appearance of their wrist. Deformity was associated with non-surgical treatment (RR = 3.85, p = 0.006) but was not significantly associated with functional outcomes (p = 0.15). All those who were bothered belonged to the non-surgical treatment group. Bother was significantly associated with poorer functional outcomes (p = 0.006) and this association was clinically significant (MD = 35 points). The deformity and bother questions were found to have excellent test–retest reliability; κ = 1.00 and κ = 0.92, respectively.

Background Total hip and total knee arthroplasties are among the most common types of surgery performed in Australia today and are effective treatments for severe osteoarthritis. However, the increasing financial burden on the health system owing to the increasing rates of surgery has led to a growing interest in improving the cost-effectiveness and safety of arthroplasty care. This study was designed to examine the association between post-operative complications, a major cost driver, and the cost of investigations following total hip or knee arthroplasty. Methods This is a prospective cohort study of consecutive patients undergoing primary total hip or knee arthroplasty at an Australian public hospital. We measured the number and cost of imaging and pathology tests performed during the acute hospital stay and used linear regression to examine the association between complication status and investigations costs. Results 500 patients were included in the analysis. On average, those with complications received more tests, and more expensive tests. The mean combined cost of imaging and pathology tests in patients with no complications was AU$ 187 (SD: 12.0). In comparison, patients with minor complications had a mean additional cost of AU$ 270 (SD: 31.0), and those with major complications had a mean additional cost of AU$ 493 (SD: 54.2) (p

Background Clinical quality registries and other systems that conduct routine post-discharge surveillance of patient outcomes following surgery may have difficulty surveying patients who have limited proficiency in the language of the healthcare provider. Interpreter proxies (family and carers) are often used due to limited access to certified healthcare interpreters (due to cost or availability). The aim of this study was to assess the reliability of engaging interpreter proxies compared with certified healthcare interpreters for the administration of patient-reported health-related surveys for people with limited English proficiency (LEP). Methods People with LEP and due for a routine 6-month telephone follow-up post knee or hip arthroplasty were invited to participate. Participants were randomly allocated to having their first interview with an interpreter proxy or a certified healthcare interpreter followed by the second (crossover) interview within 2 weeks (range: 4 to 12 days) after the first interview using the alternative method. Agreement between the two methods was assessed using quadratic weighted Cohen’s kappa, intraclass correlation and concordance correlation co-efficient where appropriate for EQ-5D health domains, total Oxford hip and knee scores, patient satisfaction, operation success, readmission, reoperation, and post-surgical complication responses. The mean of the differences between the same data items collected by each of the two methods was also calculated. Results Eighty five participants (96%) completed the study. There was substantial to excellent inter-rater agreement (kappa = 0.69–0.87 and ICCs above 0.74) for all but one measure. The mean differences between family proxy and healthcare interpreter scores for each participant were small, ranging from 0.01 (score range of 1–5) to 0.72 (score range of 0–100). Conclusion These results suggest that using interpreter proxies is a reliable alternative to certified healthcare interpreters in conducting patient-reported health surveys, potentially making this process easier and cost effective for researchers and registries.

Objective: Online data centers (ODCs) are becoming increasingly popular for making health-related data available for research. Such centers provide good privacy protection during analysis by trusted researchers, but privacy concerns may still remain if the system outputs are not sufficiently anonymized. In this article, we propose a method for anonymizing analysis outputs from ODCs for publication in academic literature. Methods: We use as a model system the Secure Unified Research Environment, an online computing system that allows researchers to access and analyze linked health-related data for approved studies in Australia. This model system suggests realistic assumptions for an ODC that, together with literature and practice reviews, inform our solution design. Results: We propose a two-step approach to anonymizing analysis outputs from an ODC. A data preparation stage requires data custodians to apply some basic treatments to the dataset before making it available. A subsequent output anonymization stage requires researchers to use a checklist at the point of downloading analysis output. The checklist assists researchers with highlighting potential privacy concerns, then applying appropriate anonymization treatments. Conclusion: The checklist can be used more broadly in health care research, not just in ODCs. Ease of online publication as well as encouragement from journals to submit supplementary material are likely to increase both the volume and detail of analysis results publicly available, which in turn will increase the need for approaches such as the one suggested in this paper.

Background Throughout March 2020, leaders in countries across the world were making crucial decisions about how and when to implement public health interventions to combat the coronavirus disease (COVID-19). They urgently needed tools to help them to explore what will work best in their specific circumstances of epidemic size and spread, and feasible intervention scenarios. Objective We sought to rapidly develop a flexible, freely available simulation model for use by modelers and researchers to allow investigation of how various public health interventions implemented at various time points might change the shape of the COVID-19 epidemic curve. Methods “COVOID” (COVID-19 Open-Source Infection Dynamics) is a stochastic individual contact model (ICM), which extends the ICMs provided by the open-source EpiModel package for the R statistical computing environment. To demonstrate its use and inform urgent decisions on March 30, 2020, we modeled similar intervention scenarios to those reported by other investigators using various model types, as well as novel scenarios. The scenarios involved isolation of cases, moderate social distancing, and stricter population “lockdowns” enacted over varying time periods in a hypothetical population of 100,000 people. On April 30, 2020, we simulated the epidemic curve for the three contiguous local areas (population 287,344) in eastern Sydney, Australia that recorded 5.3% of Australian cases of COVID-19 through to April 30, 2020, under five different intervention scenarios and compared the modeled predictions with the observed epidemic curve for these areas. Results COVOID allocates each member of a population to one of seven compartments. The number of times individuals in the various compartments interact with each other and their probability of transmitting infection at each interaction can be varied to simulate the effects of interventions. Using COVOID on March 30, 2020, we were able to replicate the epidemic response patterns to specific social distancing intervention scenarios reported by others. The simulated curve for three local areas of Sydney from March 1 to April 30, 2020, was similar to the observed epidemic curve in terms of peak numbers of cases, total numbers of cases, and duration under a scenario representing the public health measures that were actually enacted, including case isolation and ramp-up of testing and social distancing measures. Conclusions COVOID allows rapid modeling of many potential intervention scenarios, can be tailored to diverse settings, and requires only standard computing infrastructure. It replicates the epidemic curves produced by other models that require highly detailed population-level data, and its predicted epidemic curve, using parameters simulating the public health measures that were enacted, was similar in form to that actually observed in Sydney, Australia. Our team and collaborators are currently developing an extended open-source COVOID package comprising of a suite of tools to explore intervention scenarios using several categories of models.

Background Patient reported outcomes are increasingly used to assess the success of surgical procedures. Patient reported complications are often included as an outcome. However, these data must be validated to be accurate and useful in clinical practice. Methods This was a retrospective descriptive study of 364 patients who had completed their six-month follow-up review questionnaire in the Arthroplasty Clinical Outcomes Registry, National (ACORN), an Australian orthopaedic registry. Patient-reported complications following total hip arthroplasty (THA) and total knee arthroplasty (TKA) were compared to surgeon-reported complications recorded in their electronic medical records at their various follow-up appointments. Sensitivity, specificity, positive predictive value and negative predictive value were calculated. Agreement was assessed using percentage agreement and Cohen’s kappa. Results Patient-reported data from the ACORN registry returned overall low sensitivity (0.14), negative predictive value (0.13) and kappa values (0.11), but very high specificity (0.98), positive predictive value (0.98) and agreement values (96.3%) for reporting of complications when compared to surgeon-reported data. Values varied depending on the type and category of complication. Conclusion Patients are accurate in reporting the absence of complications, but not the presence. Sensitivity of patient-reported complications needs to be improved. Greater attention to the clarity of the questions asked may help in this respect. Electronic supplementary material The online version of this article (10.1186/s12874-018-0645-0) contains supplementary material, which is available to authorized users.

IntroductionWhile linkage units perform population data linkage with high efficiency, other parts of the workflow from custodians to researchers remain largely outside the control of linkage operators. Most importantly, resource constraints at data custodians often limit quality control (QC) efforts and lead to delays in the data delivery to researchers. Objectives and Approachovercome these challenges, we have created the Data integration Unit (DIU) to undertake content data management and delivery in conjunction with the custodians who remain the principal data curators. Data is managed in the Custodian-Controlled Data Repository (CDDR) a highly secure virtual repository for data storage, analysis and access, established and operated by the DIU. Stringent controls for user access and data flows ensure that data is provided safely by custodians. Overseen by the custodians, DIU staff undertake QC activities, and integrate and deliver multiple datasets for approved linkage projects. ResultsLong-term data storage in the CCDR decreases data custodian workloads by reducing the frequency of content data provision to periodic updates. Feedback loops built into the QC process allow custodians to improve their datasets by learning from data issues identified by the DIU. Extensive QC undertaken by DIU staff on individual datasets and data validation across multiple datasets held in the CCDR ensure that the quality of data provided to researchers is improved. Moreover, DIU staff dedicated to data integration provide faster content data delivery to researchers. Lastly, the CCDR reduces the number of custodians researchers need to liaise with for data provision. Conclusion/ImplicationsOperational since February 2018, the DIU has delivered content data for several linkage projects, based on key datasets stored in the CCDR. The incorporation of additional datasets is currently negotiated. Recognising recent developments in secure analytics infrastructure, the further evolution of the CCDR towards a cloud-based model is anticipated.

Overall objectives or goalMany health data linkage ecosystems across the world have designed and implemented secure data analysis environments as one of their controls to protect patient privacy and confidentiality. These have been shaped by local legislation and data governance policies, available IT infrastructure and resources, and the skills and imagination of their architects. However, at present their various features and functionalities have not been reviewed, synthesised or contrasted. Burton et al [1] have proposed 12 criteria for Data Safe Havens in health and healthcare, which they conceptualise broadly as encompassing data governance and ethics, quality and curation of data repositories, and data security. Under this definition, secure analysis environments, which may or may not be integrated with data repositories, are a component of a Data Safe Haven, addressing the criterion “Appropriate secure access to individually identifying data”. To guide those building and operating these environments, and data custodians and stewards who need to assess their fitness-for-purpose, it would be of great value to discuss and agree an aggregate term (e.g. “Secure Data Lab”) that describes them, and to develop a more detailed set of criteria for what entails “Appropriate secure access” to linked health data. The goal of this session is to describe and document the approaches that have been taken by flagship secure data analysis environments internationally, including their approaches to authentication, assigning permissions, managing the ingress and egress of files and auditing transactions, and their responses to emerging opportunities, including cloud computing and national and international data sharing. We will explore how the interplay of physical, technical and procedural controls have been combined to create existing models, and the extent to which these can balance each other and be applied with flexibility depending on perceived risk and regimes. Session structurePrior to the session, we will develop a draft set of criteria for “Appropriate secure access” to linked health data. The session will comprise presentations describing existing secure analysis environments against the draft criteria, followed by a facilitated discussion. The secure data analysis environments that will be presented include: UNSW Sydney E-Research Institutional Cloud Architecture (ERICA) PopData BC Secure Research Environment (SRE) Institute for Clinical Evaluative Sciences (ICES) Data and Analytic Virtual Environment (IDAVE) Secure Anonymised Information Linkage (SAIL) Gateway Intended output or outcomeWe will write up the outcomes of the session as a scientific paper that proposes an aggregate term for secure data analysis environments for linked health data and a set of criteria for what entails “Appropriate secure access” to linked health data. Presenters and Facilitators Professor Louisa Jorm, Centre for Big Data Research in Health, UNSW Sydney, Australia Dr Tim Churches, South Western Sydney Clinical School, UNSW Sydney, Australia Professor Kim McGrail, Population Data BC, The University of British Columbia, Vancouver, Canada J. Charles Victor, Institute for Clinical Evaluative Sciences, Toronto, Canada Dr Kerina Jones, Swansea University Medical School, Wales, United Kingdom Professor David Ford, Swansea University Medical School, Wales, United Kingdom 1. Burton PR, Murtagh MJ, Boyd A, et al. Data Safe Havens in health research and healthcare. Bioinformatics 2015; 31(20): 3241–3248

ObjectiveRecent growth in the number of population health researchers accessing detailed datasets, either on their own computers or through virtual data centers, has the potential to increase privacy risks. In response, a checklist for identifying and reducing privacy risks in population health analysis outputs has been proposed for use by researchers themselves. In this study we explore the usability and reliability of such an approach by investigating whether different users identify the same privacy risks on applying the checklist to a sample of publications.MethodsThe checklist was applied to a sample of 100 academic population health publications distributed among 5 readers. Cohen’s κ was used to measure interrater agreement.ResultsOf the 566 instances of statistical output types found in the 100 publications, the most frequently occurring were counts, summary statistics, plots, and model outputs. Application of the checklist identified 128 outputs (22.6%) with potential privacy concerns. Most of these were associated with the reporting of small counts. Among these identified outputs, the readers found no substantial actual privacy concerns when context was taken into account. Interrater agreement for identifying potential privacy concerns was generally good.ConclusionThis study has demonstrated that a checklist can be a reliable tool to assist researchers with anonymizing analysis outputs in population health research. This further suggests that such an approach may have the potential to be developed into a broadly applicable standard providing consistent confidentiality protection across multiple analyses of the same data.

We investigated disparities in rates of acute myocardial infarction (AMI) between Aboriginal and non-Aboriginal people in the 199 Statistical Local Areas (SLAs) in New South Wales, Australia. Using routinely collected and linked hospital and mortality data from 2002 to 2007, we developed multilevel Poisson regression models to estimate the relative rates of first AMI events in the study period accounting for area of residence. Rates of AMI in Aboriginal people were more than two times that in non-Aboriginal people, with the disparity greatest in more disadvantaged and remote areas. AMI rates in Aboriginal people varied significantly by SLA, as did the Aboriginal to non-Aboriginal rate ratio. We identified almost 30 priority areas for universal and targeted preventive interventions that had both high rates of AMI for Aboriginal people and large disparities in rates.

This article responds to criticisms made in a rejoinder (Accident Analysis and Prevention 2012, 45: 107-109) questioning the validity of a study on the impact of mandatory helmet legislation (MHL) for cyclists in New South Wales, Australia. We systematically address the criticisms through clarification of our methods, extension of the original analysis and discussion of new evidence on the population-level effects of MHL. Extensions of our analysis confirm the original conclusions that MHL had a beneficial effect on head injury rates over and above background trends and changes in cycling participation. The ongoing debate around MHL draws attention away from important ways in which both safety and participation can be improved through investment in well-connected cycling infrastructure, fostering consideration between road users, and adequate legal protection for vulnerable road users. These are the essential elements for providing a cycling environment that encourages participation, with all its health, economic and environmental benefits, while maximising safety.

To describe the development of the public health surveillance system for the Sydney 2000 Olympic Games; document its major findings; and discuss the implications for public health surveillance for future events.Planning for the system took almost three years. Its major components included increased surveillance of communicable diseases; presentations to sentinel emergency departments; medical encounters at Olympic venues; cruise ship surveillance; environmental and food safety inspections; surveillance for bioterrorism; and global epidemic intelligence. A daily report integrated data from all sources.Sydney, Australia. Surveillance spanned the period 28 August to 4 October 2000.Residents of Sydney, athletes and officials, Australian and international visitors.No outbreaks of communicable diseases were detected. There were around 5% more presentations to Sydney emergency departments than in comparable periods in other years. Several incidents detected through surveillance, including injuries caused by broken glass, and a cluster of presentations related to the use of the drug ecstasy, prompted further action.Key elements in the success of public health surveillance for the Games included its careful planning, its comprehensive coverage of public health issues, and its timely reporting and communication processes. Future systems need to be flexible enough to detect the unexpected.

National Statistical Agencies and other data custodians are vital sources of data for research and policy analysis. However, external researchers must be provided with access to data in such a way that privacy and confidentiality are protected. We discuss two recently-implemented research data access systems. The first was developed by the Australian Bureau of Statistics for use with certain of its data collections. The second was developed by the Sax Institute, a non-profit health research non-government organisation, for use by population health and health services researchers to analyse complex, linked administrative health and related data sets provided by a range of data custodians. Although these organisations both chose remote access systems, it is interesting that there are significant differences between the two systems. We discuss the drivers for and consequences of the different choices made.

Background: The purpose of this study was to examine existing data on women diagnosed with breast cancer in New South Wales in 1991 and 1992 and to describe surgical treatments received on an inpatient basis. Methods: Analyses were based on the linkage of two databases: the New South Wales Central Cancer Registry and the New South Wales Health Department's Inpatient Statistics Collection. Data were limited to women who were resident and treated in New South Wales. Main analyses were restricted to definitive surgical procedures. Results: Thirty-six per cent of women treated surgically for breast cancer in 1991 had breast-conserving therapy. This had increased to 39% in 1992. There were substantial geographical variations in the use of breast-conserving therapy in New South Wales which could not be explained by patient characteristics. Age, degree of spread at diagnosis, and area health service/health region were all found to have an independent association with the probability of having a mastectomy. Conclusions: Women with a localized degree of spread living in non-metropolitan areas (Health Regions) were almost twice as likely to have a mastectomy as compared with similar women who were resident in metropolitan areas (Area Health Services). The concentration of radiotherapy services may have contributed to the urban/rural variation in breast-conserving therapy in New South Wales, but it is also likely that some of the variations that were observed may be a reflection of the failure of clinicians to use best current practice.

We analysed five-year relative survival of 6992 cases of cervical cancer incident between 1972 and 1991 in New South Wales (NSW) women, using data from the population-based state Cancer Registry. Follow-up was to 1992. Survival was determined by record linkage to death certificates. Relative survival was derived from absolute survival of cases with expected survival of age- and period-matched NSW women. Proportional hazard regression analysis was used for multivariate analysis. Relative survival at five years improved from 64 per cent in 1972-1976 to 72 per cent in 1987-1991, although the only significant increase occurred between 1972-1976 and 1977-1981 (64 to 70 per cent). Survival was better for the age groups 0-39 years (RR 0.51) and 40-49 years (RR 0.63) and worse for the elderly (> or = 65 years) (RR 1.47) than for the referent group (50-64 years). Excess mortality was much less for those with localised disease (referent group), than for those with regional spread (RR 3.47) or metastatic cancer (RR 10.5) at diagnosis. For the most recent period (1987-1991), relative five-year survival for localised disease was 82 per cent, for regional spread at diagnosis it was 49 per cent, and for metastatic cancer 21 per cent. When adjusted for confounding, excess mortality was significantly higher for adenocarcinoma (RR 1.16) than for squamous cell carcinoma. Five-year relative survival for cervical cancer in NSW women for the most recent period is similar to that in South Australia, and both compare favourably with international statistics. The lack of improvement of five-year survival for cervical cancer over 15 years since 1977-1981 reinforces the importance of prevention through regular screening by cytology.

Rissel and Wen?s article boldly proclaims that repealing mandatory helmet legislation (MHL) would greatly increase cycling uptake. However, closer examination of their results reveals that odds ratios are interpreted incorrectly several times and some findings were curiously omitted. They state that people 'aged 16-24 years...were significantly more likely to ride more if they did not have to wear a helmet'. This is only found to be true when compared to those aged 55+ but is not shown to be the case compared to the broader adult population. If the intent is to state those aged 16-24 years are significantly more likely than not to cycle more, this is clearly not true as significantly more people responded to the contrary (0.341, 95%CI: 0.235-0.447). Also, significantly more people in the other age groups responded they would not ride more, with an apparent downward trend in proportion by age.

The study aimed to assess the effect of compulsory cycle helmet legislation on cyclist head injuries given the ongoing debate in Australia as to the efficacy of this measure at a population level. We used hospital admissions data from New South Wales, Australia, from a 36 month period centred at the time legislation came into effect. Negative binomial regression of hospital admission counts of head and limb injuries to cyclists were performed to identify differential changes in head and limb injury rates at the time of legislation. Interaction terms were included to allow different trends between injury types and pre- and post-law time periods. To avoid the issue of lack of cyclist exposure data, we assumed equal exposures between head and limb injuries which allowed an arbitrary proxy exposure to be used in the model. As a comparison, analyses were also performed for pedestrian data to identify which of the observed effects were specific to cyclists. In general, the models identified a decreasing trend in injury rates prior to legislation, an increasing trend thereafter and a drop in rates at the time legislation was enacted, all of which were thought to represent background effects in transport safety. Head injury rates decreased significantly more than limb injury rates at the time of legislation among cyclists but not among pedestrians. This additional benefit was attributed to compulsory helmet legislation. Despite numerous data limitations, we identified evidence of a positive effect of compulsory cycle helmet legislation on cyclist head injuries at a population level such that repealing the law cannot be justified.

Daily counts of computer records of hospital emergency department arrivals grouped according to diagnosis (called here syndrome groupings) can be monitored by epidemiologists for changes in frequency that could provide early warning of bioterrorism events or naturally occurring disease outbreaks and epidemics. This type of public health surveillance is sometimes called syndromic surveillance. We used transitional Poisson regression models to obtain one-day-ahead arrival forecasts. Regression parameter estimates and forecasts were updated for each day using the latest 365 days of data. The resulting time series of recursive estimates of parameters such as the amplitude and location of the seasonal peaks as well as the one-day-ahead forecasts and forecast errors can be monitored to understand changes in epidemiology of each syndrome grouping. The counts for each syndrome grouping were autocorrelated and non-homogeneous Poisson. As such, the main methodological contribution of the article is the adaptation of Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) plans for monitoring non-homogeneous counts. These plans were valid for small counts where the assumption of normally distributed one-day-ahead forecasts errors, typically used in other papers, breaks down. In addition, these adaptive plans have the advantage that control limits do not have to be trained for different syndrome groupings or aggregations of emergency departments. Conventional methods for signaling increases in syndrome grouping counts, Shewhart, CUSUM, and EWMA control charts of the standardized forecast errors were also examined. Shewhart charts were, at times, insensitive to shifts of interest. CUSUM and EWMA charts were only reasonable for large counts. We illustrate our methods with respiratory, influenza, diarrhea, and abdominal pain syndrome groupings. Copyright © "IIE".

Surveillance has a fundamental role during public health emergencies to provide accurate and relevant information to guide decision making. For each phase of the NSW response to the pandemic H1N1 (2009) influenza there were significant differences in the public health surveillance objectives and response mechanisms. Consequently each phase placed a different emphasis on the various sources and types of surveillance information which were collected and reported upon. We examine whether the NSW public health surveillance systems were able to inform effective public health management throughout all phases of the pandemic (H1N1) 2009 influenza.

Background Mass gatherings have been defined by the World Health Organisation as "events attended by a sufficient number of people to strain the planning and response resources of a community, state or nation". This paper explores the public health response to mass gatherings in Sydney, the factors that influenced the extent of deployment of resources and the utility of planning for mass gatherings as a preparedness exercise for other health emergencies. Discussion Not all mass gatherings of people require enhanced surveillance and additional response. The main drivers of extensive public health planning for mass gatherings reflect geographical spread, number of international visitors, event duration and political and religious considerations. In these instances, the implementation of a formal risk assessment prior to the event with ongoing daily review is important in identifying public health hazards. Developing and utilising event-specific surveillance to provide early-warning systems that address the specific risks identified through the risk assessment process are essential. The extent to which additional resources are required will vary and depend on the current level of surveillance infrastructure. Planning the public health response is the third step in preparing for mass gatherings. If the existing public health workforce has been regularly trained in emergency response procedures then far less effort and resources will be needed to prepare for each mass gathering event. The use of formal emergency management structures and co-location of surveillance and planning operational teams during events facilitates timely communication and action. Summary One-off mass gathering events can provide a catalyst for innovation and engagement and result in opportunities for ongoing public health planning, training and surveillance enhancements that outlasted each event.

In 1972, cancer registration began in New South Wales (NSW), the most populous state in Australia. The operations of the Registry are described. By 1990, approximately 316 000 new cases of cancer had been notified from a population that had increased from 4.6 to 5.8 million. In 1981–1984, the most common sites in men were lung, prostate, colon, melanoma and bladder, and in women, breast, melanoma, colon, lung and unknown primary site. Cancers which, between 1973–1976 and 1981–1984, had increased in reported incidence by more than 25% were pharynx and kidney in both sexes, rectum, testis and melanoma in men, and lung and bladder in women; those decreasing by more than 10% were stomach in both sexes, oesophagus in men and cervix in women. Age-standardised incidence rates for melanoma (27.4 [m] and 23.8 [f] per 100 000 in 1987) and cancer of the renal pelvis in women (1.7 per 100 000 in 1989) are among the highest in the world.

Background Although syndromic surveillance systems are gaining acceptance as useful tools in public health, doubts remain about whether the anticipated early warning benefits exist. Many assessments of this question do not adequately account for the confounding effects of autocorrelation and trend when comparing surveillance time series and few compare the syndromic data stream against a continuous laboratory-based standard. We used time series methods to assess whether monitoring of daily counts of Emergency Department (ED) visits assigned a clinical diagnosis of influenza could offer earlier warning of increased incidence of viral influenza in the population compared with surveillance of daily counts of positive influenza test results from laboratories. Methods For the five-year period 2001 to 2005, time series were assembled of ED visits assigned a provisional ED diagnosis of influenza and of laboratory-confirmed influenza cases in New South Wales (NSW), Australia. Poisson regression models were fitted to both time series to minimise the confounding effects of trend and autocorrelation and to control for other calendar influences. To assess the relative timeliness of the two series, cross-correlation analysis was performed on the model residuals. Modelling and cross-correlation analysis were repeated for each individual year. Results Using the full five-year time series, short-term changes in the ED time series were estimated to precede changes in the laboratory series by three days. For individual years, the estimate was between three and 18 days. The time advantage estimated for the individual years 2003–2005 was consistently between three and four days. Conclusion Monitoring time series of ED visits clinically diagnosed with influenza could potentially provide three days early warning compared with surveillance of laboratory-confirmed influenza. When current laboratory processing and reporting delays are taken into account this time advantage is even greater.

It is estimated that between 80% and 90% of governmental data collections contain address information. Geocoding – the process of assigning geographic coordinates to addresses – is becoming increasingly important in application areas that involve the analysis and mining of such data. In many cases, address records are captured and/or stored in a free-form or inconsistent manner. This fact complicates the task of accurately matching such addresses to spatially-annotated reference data. In this paper we describe a geocoding system that is based on a comprehensive high-quality geocoded national address database. It uses a learning address parser based on hidden Markov models to segment free-form addresses into components, and a rule-based matching engine to determine the best matches to the reference database.

Integrating or linking data from different sources is an increasingly important task in the preprocessing stage of many data mining projects. The aim of such linkages is to merge all records relating to the same entity, such as a patient or a customer. If no common unique entity identifiers (keys) are available in all data sources, the linkage needs to be performed using the available identifying attributes, like names and addresses. Data confidentiality often limits or even prohibits successful data linkage, as either no consent can be gained (for example in biomedical studies) or the data holders are not willing to release their data for linkage by other parties. We present methods for confidential data linkage based on hash encoding, public key encryption and n-gram similarity comparison techniques, and show how blind data linkage can be performed.

Uniquely large numbers of people from all over the world will concentrate at Olympic venues scattered across Sydney, during the weeks in which the Sydney 2000 Olympic and Paralympic Games will be held.