Publications by authors named "Elif E Firat"
Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.
Philos Trans A Math Phys Eng Sci
October 2022
Article Synopsis
- The report discusses a collaboration between epidemiological modellers and visualization researchers to improve the understanding and modeling of the COVID-19 pandemic through existing visualization techniques.
- It highlights the effectiveness of visualization in epidemiological research, identifies ongoing challenges in the field, and offers recommendations for future collaborations.
- The goal is to encourage both scientific and visualization communities to work together, leveraging their strengths to tackle significant data-related challenges in epidemiology and other areas.
With the widespread advent of visualization techniques to convey complex data, visualization literacy (VL) is growing in importance. Two noteworthy facets of literacy are user understanding and the discovery of visual patterns with the help of graphical representations. The research literature on VL provides useful guidance and opportunities for further studies in this field.
View Article and Find Full Text PDFUncertainty quantification is a formal paradigm of statistical estimation that aims to account for all uncertainties inherent in the modelling process of real-world complex systems. The methods are directly applicable to stochastic models in epidemiology, however they have thus far not been widely used in this context. In this paper, we provide a tutorial on uncertainty quantification of stochastic epidemic models, aiming to facilitate the use of the uncertainty quantification paradigm for practitioners with other complex stochastic simulators of applied systems.
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