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Research
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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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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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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Child Health Analytics Research ProgramListed are all Telethon Kids Institute research teams involved in our Child Health Analytics Research Program. This program sits under the Brain and Behaviour research theme.
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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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A Maximum Entropy Model of the Distribution of Dengue Serotype in MexicoPathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling.
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Patterns and trends of in-hospital mortality due to non-communicable diseases and injuries in Tanzania, 2006–2015Globally, non-communicable diseases (NCD) kill about 40 million people annually, with about three-quarters of the deaths occurring in low- and middle-income countries. This study was carried out to determine the patterns, trends, and causes of in-hospital non-communicable disease (NCD) and injury deaths in Tanzania from 2006-2015.
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Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventionsSince 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach.
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Comodity forecastingProject description This project support the development of 10-year global forecasts of nets, insecticides, diagnostics, and treatments for malaria
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Sophisticated new modelling suggests keeping mask mandate could prevent 147,000 COVID-19 casesWA’s current Omicron COVID-19 outbreak could jump by 147,000 cases if mask mandates are abandoned before the Easter long weekend, according to sophisticated new modelling.