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One of the key components of this research has been the mapping of Antarctic bed topography and ice thickness parameters that are crucial for modelling ice flow and hence for predicting future ice loss and the ensuing sea level rise. Supported by the Scientific Committee on Antarctic Research (SCAR), the Bedmap3 Action Group aims not only to produce new gridded maps of ice thickness and bed topography for the international scientific community, but also to standardize and make available all the geophysical survey data points used in producing the Bedmap gridded products. Here, we document the survey data used in the latest iteration, Bedmap3, incorporating and adding to all of the datasets previously used for Bedmap1 and Bedmap2, including ice bed, surface and thickness point data from all Antarctic geophysical campaigns since the 1950s. More specifically, we describe the processes used to standardize and make these and future surveys and gridded datasets accessible under the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles. With the goals of making the gridding process reproducible and allowing scientists to re-use the data freely for their own analysis, we introduce the new SCAR Bedmap Data Portal (https://bedmap.scar.org, last access: 1 March 2023) created to provide unprecedented open access to these important datasets through a web-map interface. We believe that this data release will be a valuable asset to Antarctic research and will greatly extend the life cycle of the data held within it. Data are available from the UK Polar Data Centre: https://data.bas.ac.uk (last access: 5 May 2023​​​​​​​). See the Data availability section for the complete list of datasets.

BACKGROUND: Up to one-half of childhood sarcomeric hypertrophic cardiomyopathy (HCM) presents before the age of 12 years, but this patient group has not been systematically characterized. OBJECTIVES: The aim of this study was to describe the clinical presentation and natural history of patients presenting with nonsyndromic HCM before the age of 12 years. METHODS: Data from the International Paediatric Hypertrophic Cardiomyopathy Consortium on 639 children diagnosed with HCM younger than 12 years were collected and compared with those from 568 children diagnosed between 12 and 16 years. RESULTS: At baseline, 339 patients (53.6%) had family histories of HCM, 132 (20.9%) had heart failure symptoms, and 250 (39.2%) were prescribed cardiac medications. The median maximal left ventricular wall thickness z-score was 8.7 (IQR: 5.3-14.4), and 145 patients (27.2%) had left ventricular outflow tract obstruction. Over a median follow-up period of 5.6 years (IQR: 2.3-10.0 years), 42 patients (6.6%) died, 21 (3.3%) underwent cardiac transplantation, and 69 (10.8%) had life-threatening arrhythmic events. Compared with those presenting after 12 years, a higher proportion of younger patients underwent myectomy (10.5% vs 7.2%; P = 0.045), but fewer received primary prevention implantable cardioverter-defibrillators (18.9% vs 30.1%; P = 0.041). The incidence of mortality or life-threatening arrhythmic events did not differ, but events occurred at a younger age. CONCLUSIONS: Early-onset childhood HCM is associated with a comparable symptom burden and cardiac phenotype as in patients presenting later in childhood. Long-term outcomes including mortality did not differ by age of presentation, but patients presenting at younger than 12 years experienced adverse events at younger ages.

AIMS: The 12-lead electrocardiogram (ECG) is routinely performed in children with hypertrophic cardiomyopathy (HCM). An ECG risk score has been suggested as a useful tool for risk stratification, but this has not been independently validated. This aim of this study was to describe the ECG phenotype of childhood HCM in a large, international, multi-centre cohort and investigate its role in risk prediction for arrhythmic events. METHODS AND RESULTS: Data from 356 childhood HCM patients with a mean age of 10.1 years (±4.5) were collected from a retrospective, multi-centre international cohort. Three hundred and forty-seven (97.5%) patients had ECG abnormalities at baseline, most commonly repolarization abnormalities (n = 277, 77.8%); left ventricular hypertrophy (n = 240, 67.7%); abnormal QRS axis (n = 126, 35.4%); or QT prolongation (n = 131, 36.8%). Over a median follow-up of 3.9 years (interquartile range 2.0-7.7), 25 (7%) had an arrhythmic event, with an overall annual event rate of 1.38 (95% CI 0.93-2.04). No ECG variables were associated with 5-year arrhythmic event on univariable or multivariable analysis. The ECG risk score threshold of >5 had modest discriminatory ability [C-index 0.60 (95% CI 0.484-0.715)], with corresponding negative and positive predictive values of 96.7% and 6.7. CONCLUSION: In a large, international, multi-centre cohort of childhood HCM, ECG abnormalities were common and varied. No ECG characteristic, either in isolation or combined in the previously described ECG risk score, was associated with 5-year sudden cardiac death risk. This suggests that the role of baseline ECG phenotype in improving risk stratification in childhood HCM is limited.

BACKGROUND: Maximal left ventricular wall thickness (MLVWT) is a risk factor for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). In adults, the severity of left ventricular hypertrophy has a nonlinear relationship with SCD, but it is not known whether the same complex relationship is seen in childhood. The aim of this study was to describe the relationship between left ventricular hypertrophy and SCD risk in a large international pediatric HCM cohort. METHODS: The study cohort comprised 1075 children (mean age, 10.2 years [±4.4]) diagnosed with HCM (1-16 years) from the International Paediatric Hypertrophic Cardiomyopathy Consortium. Anonymized, noninvasive clinical data were collected from baseline evaluation and follow-up, and 5-year estimated SCD risk was calculated (HCM Risk-Kids). RESULTS: MLVWT Z score was <10 in 598 (58.1%), ≥10 to <20 in 334 (31.1%), and ≥20 in 143 (13.3%). Higher MLVWT Z scores were associated with heart failure symptoms, unexplained syncope, left ventricular outflow tract obstruction, left atrial dilatation, and nonsustained ventricular tachycardia. One hundred twenty-two patients (71.3%) with MLVWT Z score ≥20 had coexisting risk factors for SCD. Over a median follow-up of 4.9 years (interquartile range, 2.3-9.3), 115 (10.7%) had an SCD event. Freedom from SCD event at 5 years for those with MLVWT Z scores <10, ≥10 to <20, and ≥20 was 95.6%, 87.4%, and 86.0, respectively. The estimated SCD risk at 5 years had a nonlinear, inverted U-shaped relationship with MLVWT Z score, peaking at Z score +23. The presence of coexisting risk factors had a summative effect on risk. CONCLUSIONS: In children with HCM, an inverted U-shaped relationship exists between left ventricular hypertrophy and estimated SCD risk. The presence of additional risk factors has a summative effect on risk. While MLVWT is important for risk stratification, it should not be used either as a binary variable or in isolation to guide implantable cardioverter def

The aim of this study was to describe the scope of the Australian Field Epidemiology Training Programme's contributions to the COVID-19 response during the first 10 months of the pandemic, to assist with quantifying the impact they have had during the pandemic and inform future Master of Applied Epidemiology programme learning priorities.

For public health response to be effective, it is essential that we identify support mechanisms for people working in challenging response environments. The Regional Office for the Western Pacific needs programmes, such as Field Epidemiology Training Programmes, to ensure sustained workforce development. However, during crises a modified mentorship-like program may foster temporary support and empowerment within the workforce.

BACKGROUND: Following high influenza activity in 2017, the state of Queensland, Australia, funded a quadrivalent inactivated influenza vaccination program for children aged 6 months to <5 years in 2018. We calculated influenza vaccine effectiveness (VE) among children eligible for this program. METHODS: A matched case-control study was conducted. Cases were identified using Queensland 2018 influenza notification data among children age-eligible for funded vaccination. Controls were drawn from Australian Immunisation Register records of Queensland resident children age-eligible for funded influenza vaccine. Up to 10 controls per case were matched for location and birthdate. First dose vaccination was valid if received ≥14 days prior to specimen collection; a second dose was valid if received ≥28 days after first dose receipt. VE was calculated for vaccine doses and adherence to national recommendations for two doses in the first season (schedule completeness) and adjusted (VEadj) for sex and First Nations status. RESULTS: There were 1,125 cases and 10,645 matched controls analysed. Overall VEadj against laboratory-confirmed influenza was 51% (95% confidence interval (CI) 41-60). VEadj was 60% (95% CI 46-70) for children who received two doses in 2018, and 60% (95% CI 48-69) for children vaccinated appropriately according to schedule completeness. VE increased with age. CONCLUSIONS: Moderate vaccine effectiveness was observed for children eligible for the funded program in Queensland in 2018, adding to the sparse evidence for influenza vaccine use in Australian children. Adhering to the national first season two dose schedule for influenza vaccine receipt in children ensures maximum protection.

Accurate and current information has been highlighted across the globe as a critical requirement for the COVID-19 pandemic response. To address this need, many interactive dashboards providing a range of different information about COVID-19 have been developed. A similar tool in Australia containing current information about COVID-19 could assist general practitioners and public health responders in their pandemic response efforts. The COVID-19 Real-time Information System for Preparedness and Epidemic Response (CRISPER) has been developed to provide accurate and spatially explicit real-time information for COVID-19 cases, deaths, testing and contact tracing locations in Australia. Developed based on feedback from key users and stakeholders, the system comprises three main components: (1) a data engine; (2) data visualization and interactive mapping tools; and (3) an automated alert system. This system provides integrated data from multiple sources in one platform which optimizes information sharing with public health responders, primary health care practitioners and the general public.

Coronavirus disease 2019 (COVID-19) has highlighted the need for the timely collection and sharing of public health data. It is important that data sharing is balanced with protecting confidentiality. Here we discuss an innovative mechanism to protect health data, called differential privacy. Differential privacy is a mathematically rigorous definition of privacy that aims to protect against all possible adversaries. In layperson's terms, statistical noise is applied to the data so that overall patterns can be described, but data on individuals are unlikely to be extracted. One of the first use cases for health data in Australia is the development of the COVID-19 Real-Time Information System for Preparedness and Epidemic Response (CRISPER), which provides proof of concept for the use of this technology in the health sector. If successful, this will benefit future sharing of public health data.