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Research
A global mathematical model of climatic suitability for Plasmodium falciparum malariaClimatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control.
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Maps and metrics of insecticide-treated net access, use, and nets-per-capita in Africa from 2000-2020Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries.
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The prevalence of tuberculosis, malaria and soil-transmitted helminth infection in minority indigenous people of Southeast Asia and the Western Pacific: protocol for a systematic review and meta-analysisInfectious diseases such as tuberculosis (TB), malaria and soil-transmitted helminthiasis continue to impose a significant global health burden and socio-economic impact. Globally, minority indigenous people are disproportionately affected by poverty and are shown to experience a disparate burden of disease and poorer health outcomes than the comparative majority population.
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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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Malaria treatment for prevention: a modelling study of the impact of routine case management on malaria prevalence and burdenTesting and treating symptomatic malaria cases is crucial for case management, but it may also prevent future illness by reducing mean infection duration. Measuring the impact of effective treatment on burden and transmission via field studies or routine surveillance systems is difficult and potentially unethical. This project uses mathematical modeling to explore how increasing treatment of symptomatic cases impacts malaria prevalence and incidence.
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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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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.
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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.