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Seroprevalence and associated risk factors of chikungunya, dengue, and Zika in eight districts in TanzaniaThis study was conducted to determine the seroprevalence and risk factors of chikungunya (CHIKV), dengue (DENV), and Zika (ZIKV) viruses in Tanzania.
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WALLABY pre-pilot survey: Two dark clouds in the vicinity of NGC 1395We present the Australian Square Kilometre Array Pathfinder (ASKAP) WALLABY pre-pilot observations of two 'dark' H i sources (with H i masses of a few times 108 {M}_\odot and no known stellar counterpart) that reside within 363 kpc of NGC 1395, the most massive early-type galaxy in the Eridanus group of galaxies.
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Geospatial modelling for malaria risk stratification and intervention targeting for low-endemic countriesEwan Punam Susan Tasmin Cameron Amratia Rumisha Symons BSc PhD PhD PhD (Biostatistics) Director of Malaria Risk Stratification Honorary Research
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Modelling temperature-driven changes in species associations across freshwater communitiesDue to global climate change–induced shifts in species distributions, estimating changes in community composition through the use of Species Distribution Models has become a key management tool. Being able to determine how species associations change along environmental gradients is likely to be pivotal in exploring the magnitude of future changes in species’ distributions.
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Emulator-based Bayesian optimization for efficient multi-objective calibration of an individual-based model of malariaIndividual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose using a Bayesian optimization framework employing Gaussian process or machine learning emulator functions to calibrate a complex malaria transmission simulator.
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Mapping the endemicity and seasonality of clinical malaria for intervention targeting in Haiti using routine case dataTowards the goal of malaria elimination on Hispaniola, the National Malaria Control Program of Haiti and its international partner organisations are conducting a campaign of interventions targeted to high-risk communities prioritised through evidence-based planning. Here we present a key piece of this planning: an up-to-date, fine-scale endemicity map and seasonality profile for Haiti informed by monthly case counts.
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Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infectionsAsymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures.
Our Child Health Analytics Team uses cutting-edge technologies to better understand how and why the health and wellbeing of children varies from place to place. We develop innovative geospatial methods that can harness large, complex datasets to pinpoint hotspots of elevated risk, evaluate change through time, and explore underlying drivers.
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Gaussian random fields: with and without covariancesWe begin with isotropic Gaussian random fields, and show how the Bochner-Godement theorem gives a natural way to describe their covariance structure. We continue with a study of Matérn processes on Euclidean space, spheres, manifolds and graphs, using Bessel potentials and stochastic partial differential equations (SPDEs).
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Spatial codistribution of HIV, tuberculosis and malaria in EthiopiaHIV, tuberculosis (TB) and malaria are the three most important infectious diseases in Ethiopia, and sub-Saharan Africa. Understanding the spatial codistribution of these diseases is critical for designing geographically targeted and integrated disease control programmes. This study investigated the spatial overlap and drivers of HIV, TB and malaria prevalence in Ethiopia.