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WALLABY pre-pilot survey: H i content of the Eridanus supergroupWe present observations of the Eridanus supergroup obtained with the Australian Square Kilometre Array Pathfinder (ASKAP) as part of the pre-pilot survey for the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY).
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Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and mortality in Africa: a geospatial modelling analysisSubstantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control.
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Human movement and environmental barriers shape the emergence of dengueUnderstanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown.
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Biases in Routine Influenza Surveillance Indicators Used to Monitor Infection Incidence and Recommendations for ImprovementMonitoring how the incidence of influenza infections changes over time is important for quantifying the transmission dynamics and clinical severity of influenza. Infection incidence is difficult to measure directly, and hence, other quantities which are more amenable to surveillance are used to monitor trends in infection levels, with the implicit assumption that they correlate with infection incidence.
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Malaria components of the Global Burden of Disease studyAdam Dan Francesca Susan Saddler Weiss Sanna Rumisha PhD PhD Dr PhD (Biostatistics) Research Officer Honorary Research Fellow Research Officer
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Malaria Atlas Project (MAP)The Malaria Atlas Project (MAP) aims to disseminate free, accurate and up-to-date geographical information on malaria and associated topics. Our mission is to generate new and innovative methods to map malaria, to produce a comprehensive range of maps and estimates that will support effective planning of malaria
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Statistical modelling under differential privacy constraints: a case study in fine-scale geographical analysis with Australian Bureau of Statistics TableBuilder dataConsistent with the principles of differential privacy protection, the Australian Bureau of Statistics artificially perturbs all count data from the Australian Census prior to its release to researchers through the TableBuilder platform. This perturbation involves the addition of random noise to every non-zero cell count followed by the suppression of small values to zero.
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Spatio-temporal spread of artemisinin resistance in Southeast AsiaCurrent malaria elimination targets must withstand a colossal challenge-resistance to the current gold standard antimalarial drug, namely artemisinin derivatives. If artemisinin resistance significantly expands to Africa or India, cases and malaria-related deaths are set to increase substantially.
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Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humansBuruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue with Mycobacterium ulcerans. BU is commonly reported across rural regions of Central and West Africa but has been increasing dramatically in temperate southeast Australia around the major metropolitan city of Melbourne, with most disease transmission occurring in the summer months.
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What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of MobilityHuman movement drives spatial transmission patterns of infectious diseases. Population-level mobility patterns are often quantified using aggregated data sets, such as census migration surveys or mobile phone data. These data are often unable to quantify individual-level travel patterns and lack the information needed to discern how mobility varies by demographic groups. Individual-level datasets can capture additional, more precise, aspects of mobility that may impact disease risk or transmission patterns and determine how mobility differs across cohorts; however, these data are rare, particularly in locations such as sub-Saharan Africa.