Chancellery Research - Research Publications
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ItemThe Role of Data in a Rapid and Coordinated Response to Infectious Disease Outbreaks(Research Data Alliance, 2020)How does data support preparedness towards infectious disease emergencies? What information is needed to identify the start of an outbreak? How does data inform the potential severity and spread of an outbreak? The infectious diseases data ecosystem is comprised of information from a wide range of sources like general practices, jurisdictional surveillance systems, clinical research, emergency departments, diagnostic laboratories, epidemiology studies and genomics. The carefully distilled knowledge from this diverse data ecosystem enables better preparedness for and response towards an outbreak. Past infectious disease outbreaks have demonstrated several challenges associated with rapid aggregation, integration and sharing of data to inform a response during an outbreak. It is essential to improve data collection, facilitate data sharing and support data usage for decision-making in the infectious diseases community. This keynote speech will describe the composition of the infectious disease data ecosystem and highlight some challenges from the past outbreaks associated with building the data ecosystem for a response. This speech will also describe how making data consistent and shareable has strengthened preparedness and response activities in present-day scenario.
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ItemNo Preview AvailableMinimum information model for APPRISE Virtual Biobank( 2022-01-21)
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ItemDifferential privacy for public health data: An innovative tool to optimize information sharing while protecting data confidentiality.(Elsevier BV, 2021-12-10)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.
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ItemNo Preview AvailableEpidemiology and omics – challenges and policy implications( 2021-04-23)Presented at the Organisation for Economic Co-operation and Development (OECD) Open Science Forum
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ItemDevelopment of the COVID-19 Real-Time Information System for Preparedness and Epidemic Response (CRISPER), Australia.(Frontiers Media SA, 2021)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.
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ItemExtensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D.(Springer Science and Business Media LLC, 2020-01-24)Protein-protein-interaction networks (PPINs) organize fundamental biological processes, but how oncogenic mutations impact these interactions and their functions at a network-level scale is poorly understood. Here, we analyze how a common oncogenic KRAS mutation (KRASG13D) affects PPIN structure and function of the Epidermal Growth Factor Receptor (EGFR) network in colorectal cancer (CRC) cells. Mapping >6000 PPIs shows that this network is extensively rewired in cells expressing transforming levels of KRASG13D (mtKRAS). The factors driving PPIN rewiring are multifactorial including changes in protein expression and phosphorylation. Mathematical modelling also suggests that the binding dynamics of low and high affinity KRAS interactors contribute to rewiring. PPIN rewiring substantially alters the composition of protein complexes, signal flow, transcriptional regulation, and cellular phenotype. These changes are validated by targeted and global experimental analysis. Importantly, genetic alterations in the most extensively rewired PPIN nodes occur frequently in CRC and are prognostic of poor patient outcomes.
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ItemHow Do Data Bolster Pandemic Preparedness and Response? How Do We Improve Data and Systems to Be Better Prepared?(CELL PRESS, 2021-01-08)How are data driving the response for the ongoing COVID-19 pandemic? How do data support preparedness toward epidemics and pandemics? How do data inform the potential severity and spread of an outbreak? Past infectious disease outbreaks have demonstrated several challenges associated with rapid aggregation, integration, and sharing of data to inform a response during an outbreak. The ongoing pandemic response has demonstrated the value of timely data collection and sharing and the usage of data for decision-making.
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ItemThe Australasian COVID-19 Trial (ASCOT) to assess clinical outcomes in hospitalised patients with SARS-CoV-2 infection (COVID-19) treated with lopinavir/ritonavir and/or hydroxychloroquine compared to standard of care: A structured summary of a study protocol for a randomised controlled trial(BMC, 2020-07-14)OBJECTIVES: To determine if lopinavir/ritonavir +/- hydroxychloroquine will reduce the proportion of participants who survive without requiring ventilatory support, 15 days after enrolment, in adult participants with non-critically ill SARS-CoV-2 infection. TRIAL DESIGN: ASCOT is an investigator-initiated, multi-centre, open-label, randomised controlled trial. Participants will have been hospitalised with confirmed COVID-19, and will be randomised 1:1:1:1 to receive lopinavir /ritonavir, hydroxychloroquine, both or neither drug in addition to standard of care management. PARTICIPANTS: Participants will be recruited from >80 hospitals across Australia and New Zealand, representing metropolitan and regional centres in both public and private sectors. Admitted patients will be eligible if aged ≥ 18 years, have confirmed SARS-CoV-2 by nucleic acid testing in the past 12 days and are expected to remain an inpatient for at least 48 hours from the time of randomisation. Potentially eligible participants will be excluded if admitted to intensive care or requiring high level respiratory support, are currently receiving study drugs or their use is contraindicated due to allergy, drug interaction or comorbidities (including baseline QTc prolongation of 470ms for women or 480ms for men), or death is anticipated imminently. INTERVENTION AND COMPARATOR: Participants will be randomised 1:1:1:1 to: Group 1: standard of care; Group 2: lopinavir (400mg) / ritonavir (100mg) twice daily for 10 days in tablet form; Group 3: hydroxychloroquine (800mg) 4x200mg administered 12 hours apart on Day 1, followed by 400mg twice a day for 6 days; Group 4: lopinavir /ritonavir plus hydroxychloroquine. MAIN OUTCOMES: Proportion of participants alive and not having required intensive respiratory support (invasive or non-invasive ventilation) at 15 days after enrolment. A range of clinical and virological secondary outcomes will also be evaluated. RANDOMISATION: The randomisation schedule will be generated by an independent statistician. Randomisation will be stratified by site and will be in permuted blocks of variable block size. The randomised sequence allocation will only be accessible to the data management group, and site investigators will have individual participant allocation provided through a web-based trial enrolment platform. BLINDING (MASKING): This is an open-label study, with researchers assessing the laboratory outcomes blinded to treatment allocation. No unblinding procedures relating to potential adverse effects are therefore required. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): We assumed that 5% of participants receiving standard of care would meet the primary outcome, aimed to evaluate whether interventions could lead to a relative risk of 0.5, assuming no interaction between intervention arms. This corresponds to a required sample size of 610 per arm, with a 5% two-sided significance level (alpha) and 80% power. The total sample size therefore is planned to be 2440. TRIAL STATUS: ASCOT protocol version 3, May 5, 2020. Recruitment opened April 4, 2020 and is ongoing, with planned completion of enrolment July 31, 2021. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ( ACTRN12620000445976 ). Prospectively registered April 6, 2020. FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.