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A Journey from Wild to Textbook Data to Reproducibly Refresh the Wages Data from the National Longitudinal Survey of Youth DatabaseTextbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection.
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Effects of zinc and vitamin A supplementation on prognostic markers and treatment outcomes of adults with pulmonary tuberculosis: a systematic review and meta-analysisUndernutrition is a major risk factor for tuberculosis (TB), which is estimated to be responsible for 1.9 million TB cases per year globally. The effectiveness of micronutrient supplementation on TB treatment outcomes and its prognostic markers (sputum conversion, serum zinc, retinol and haemoglobin levels) has been poorly understood.
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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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The overlapping burden of the three leading causes of disability and death in sub-Saharan African childrenDespite substantial declines since 2000, lower respiratory infections (LRIs), diarrhoeal diseases, and malaria remain among the leading causes of nonfatal and fatal disease burden for children under 5 years of age (under 5), primarily in sub-Saharan Africa.
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The Use of Interdisciplinary Approaches to Understand the Biology of Campylobacter jejuniCampylobacter jejuni is a bacterial pathogen recognised as a major cause of foodborne illness worldwide. While Campylobacter jejuni generally does not grow outside its host, it can survive outside of the host long enough to pose a health concern. This review presents an up-to-date description and evaluation of biological, mathematical, and statistical approaches used to understand the behaviour of this foodborne pathogen and suggests future avenues which can be explored.
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Improving disease surveillance data analysis, interpretation, and use at the district level in TanzaniaAn effective disease surveillance system is critical for early detection and response to disease epidemics. This study aimed to assess the capacity to manage and utilize disease surveillance data and implement an intervention to improve data analysis and use at the district level in Tanzania.
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Challenges in the case-based surveillance of infectious diseasesTo effectively inform infectious disease control strategies, accurate knowledge of the pathogen's transmission dynamics is required. Since the timings of infections are rarely known, estimates of the infection incidence, which is crucial for understanding the transmission dynamics, often rely on measurements of other quantities amenable to surveillance.
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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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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 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.