Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 19 of 19 for “"Computational Epidemiology"”.
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A High Performance C++ Generic Benchmark for Computational Epidemiology
An effective tool used by planners and policy makers in public health, such as Center for Disease Control (CDC), to curtail spread of infectious diseases over a given population is contagion diffusion simulations. These simulations model the relevant characteristics of the population (age, gender, …
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A Semantic Web-Based Digital Library Infrastructure to Facilitate Computational Epidemiology
Computational epidemiology generates and utilizes massive amounts of data. There are two primary categories of datasets: reported and synthetic. Reported data include epidemic data published by organizations (e.g., WHO, CDC, other national ministries and departments of health) during and following …
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MWEpi-Viz: an interactive visualization dashboard for ensemble simulations in computational epidemiology
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Modeling Emerging Infectious Diseases for Public Health Decision Support
… pose a serious threat to global public health. Computational epidemiology is a nascent subfield of public health that can provide insight into an outbreak in advance of traditional methodologies. Research in this dissertation will use fuse nontraditional, publicly available data sources with …
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Efficient Spatio-Temporal Network Analytics in Epidemiological Studies using Distributed Databases
… studies. We propose DiceX (Data Intensive Computational Epidemiology using supercomputers), which couples high-performance, Big Data and relational computing by embedding distributed data storage and processing engines within the supercomputer. It is characterized by scalable strategies for …
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Epidemiology Experimentation and Simulation Management through Scientific Digital Libraries
… data warehouses, simulation applications, computational resources, and storage systems. Managing and provisioning simulation content allows streamlined experimentation, collaboration, discovery, and content reuse within a simulation community. Formal definitions of this class of digital …
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Computational Analysis and Network-based Modeling of Cross-Species Transmissions
… CST dynamics is essential in ecology and computational epidemiology to enhance preparedness and resilience against future outbreaks. However, accurate prediction remains challenging due to biased pathogen sampling in existing CST databases and complex interactions among viral host range. …
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Spatio-temporal Event Detection and Forecasting in Social Media
… (1) Propose a novel integrated framework for computational epidemiology and social media mining; (2) Develop a semi-supervised multilayer perceptron for mining epidemic features; and (3) Design an online training algorithm.
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Modeling, Analysis and Comparison of Large Scale Social Contact Networks on Epidemic Studies
… are useful in diverse applications, including epidemiology, wireless networking and urban resilience. The vertices of a social contact network represent individual agents (e.g. people). Time varying edges represent time varying proximity relationship. The networks are relational -- node and …
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Applying Time-Valued Knowledge for Public Health Outbreak Response
… methodological contributions for the practice of computational epidemiology as well as a theoretical grounding for the further use of the C4 Response Model.
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Relational Computing Using HPC Resources: Services and Optimizations
Computational epidemiology involves processing, analysing and managing large volumes of data. Such massive datasets cannot be handled efficiently by using traditional standalone database management systems, owing to their limitation in the degree of computational efficiency and bandwidth to scale …
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Systems analysis of vaccination in the United States: Socio-behavioral dynamics, sentiment, effectiveness and efficiency
This dissertation examines the socio-behavioral determinants of vaccination and their impacts on public health, using a systems approach that emphasizes the interface between population health research, policy, and practice. First, we identify the facilitators and barriers of parental attitudes and …
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A Distributed Approach to EpiFast using Apache Spark
EpiFast is a parallel algorithm for large-scale epidemic simulations, based on an interpretation of the stochastic disease propagation in a contact network. The original EpiFast implementation is based on a master-slave computation model with a focus on distributed memory using …
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Sensitivity Analysis and Forecasting in Network Epidemiology Models
In recent years, several methods have been proposed for real-time modeling and forecasting of the epidemic curve. These methods range from simple compartmental models to complex agent-based models. In this dissertation, we present a model-based reasoning approach to forecasting the epidemic curve …
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Data-Driven Methods for Modeling and Predicting Multivariate Time Series using Surrogates
Modeling and predicting multivariate time series data has been of prime interest to researchers for many decades. Traditionally, time series prediction models have focused on finding attributes that have consistent correlations with target variable(s). However, diverse surrogate signals, such as …
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Mathematical modeling and control of epidemics as decision support systems to steer effective public health policies
L'abstract è presente nell'allegato / the abstract is in the attachment
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Computational Cost Analysis of Large-Scale Agent-Based Epidemic Simulations
… quality nodes (natural graphs) create large computational imbalances and communication hotspots. Secondly, the computation is performed by classes of tasks that are separated by global synchronization. The non-overlapping computations cause idle times, which introduce the load balancing and …
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Data Integration Methodologies and Services for Evaluation and Forecasting of Epidemics
… technologies to solve a novel problem in epidemiology, and provides a unique solution on which different applications can be built for analyzing epidemic containment strategies.
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Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases
Abstract Probabilistic reasoning under uncertainty suits well to analysis of disease dynamics. The stochastic nature of disease progression is modeled by applying the principles of Bayesian learning. Bayesian learning predicts the disease progression, including prevalence and incidence, for a …