Visual Analytics based Search-Analyze-Forecast Framework for Epidemiological Time-series Data DOI

Tuna Gonen,

Yiwen Xing,

Çağatay Turkay

et al.

Published: Oct. 22, 2023

The COVID-19 pandemic has been a period where time-series of disease statistics, such as the number cases or vaccinations, have intensively used by public health professionals to estimate how their region compares others and what future could look like at home. Conventional visualizations are often limited in terms advanced comparative features supporting forecasting systematically. This paper presents visual analytics approach support data-driven prediction based on search-analyze-predict process comprising multi-metric, multi-criteria search method technique. These supported visualization framework for comprehensive comparison multiple time-series. We inform design our getting iterative feedback from experts globally, evaluate it both quantitatively qualitatively.

Language: Английский

Why Pandemics and Climate Change Are Hard to Understand and Make Decision-Making Difficult DOI Creative Commons
Alan Dix, Raymond Bond,

Ana Caraban

et al.

Interacting with Computers, Journal Year: 2023, Volume and Issue: 35(5), P. 744 - 761

Published: Aug. 28, 2023

Abstract This paper draws on diverse psychological, behavioural and numerical literature to understand some of the challenges we all face in making sense large-scale phenomena use this create a road map for HCI responses. body knowledge offers tools principles that can help researchers deliver value now, but also highlights future research. The is framed by looking at patterns information highlight common misunderstandings arise—not just politicians general public many academic community. does not have answers this, hope it provides and, perhaps more importantly, raises questions need address as scientific technical communities.

Language: Английский

Citations

2
How mathematical modelling can inform outbreak response vaccination DOI Creative Commons

Manjari Shankar,

Anna-Maria Hartner, Callum Arnold

et al.

BMC Infectious Diseases, Journal Year: 2024, Volume and Issue: 24(1)

Published: Dec. 1, 2024

Abstract Mathematical models are established tools to assist in outbreak response. They help characterise complex patterns disease spread, simulate control options public health authorities decision-making, and longer-term operational financial planning. In the context of vaccine-preventable diseases (VPDs), vaccines one most-cost effective response interventions, with potential avert significant morbidity mortality through timely delivery. Models can contribute design vaccine by investigating importance timeliness, identifying high-risk areas, prioritising use limited supply, highlighting surveillance gaps reporting, determining short- long-term benefits. this review, we examine how have been used inform for 10 VPDs, provide additional insights into challenges modelling, such as data gaps, key vaccine-specific considerations, communication between modellers stakeholders. We illustrate that while policy-oriented response, they only be good them.

Language: Английский

Citations

0
Perspective Chapter: EnsembleDashVis Views and Volunteers – A Retrospective and Early History DOI Creative Commons
Qiru Wang, Rita Borgo, Robert S. Laramee

et al.

IntechOpen eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 23, 2024

This paper offers a retrospective history of the early development stages EnsembleDashVis, visualization dashboard specifically crafted to support modelers in interpreting simulation model utilized forecast COVID-19 trends. The volunteer effort behind this was collaboratively contributed with Scottish Response Consortium (SCRC), objective enabling an enhanced comprehension complex dynamics pandemic through modeling data collected by NHS Scotland during first wave outbreak. chronicles design and journey system, guided feedback from domain experts, all taking place amidst exceptional circumstances unprecedented pandemic. outcome work is streamlined relationship discovery process between sets input parameters their respective outcomes, which leverages power information visual analytics (VIS). We hope that will serve as insightful resource for future effort, VIS emergency responses promote mutually beneficial engagement scientific communities.

Language: Английский

Citations

0
Development and Evaluation of Two Approaches of Visual Sensitivity Analysis to Support Epidemiological Modeling DOI

Erik Rydow,

Rita Borgo, Hui Fang

et al.

IEEE Transactions on Visualization and Computer Graphics, Journal Year: 2022, Volume and Issue: unknown, P. 1 - 11

Published: Jan. 1, 2022

Computational modeling is a commonly used technology in many scientific disciplines and has played noticeable role combating the COVID-19 pandemic. Modeling scientists conduct sensitivity analysis frequently to observe monitor behavior of model during its development deployment. The traditional algorithmic ranking sensitivity different parameters usually does not provide with sufficient information understand interactions between outputs, while need large number runs order gain actionable for parameter optimization. To address above challenge, we developed compared two visual analytics approaches, namely: xmlns:xlink="http://www.w3.org/1999/xlink">algorithm-centric visualization-assisted , xmlns:xlink="http://www.w3.org/1999/xlink">visualization-centric algorithm-assisted . We evaluated approaches based on structured analysis tasks as well feedback domain experts. While work was carried out context epidemiological modeling, this are directly applicable variety processes featuring time series can be extended models other types outputs.

Language: Английский

Citations

2
WITHDRAWN: RAMPVIS: A visualization and visual analytics infrastructure for COVID-19 data DOI Creative Commons

Erik Rydow,

Tuna Gönen,

Alexander Kachkaev

et al.

SoftwareX, Journal Year: 2023, Volume and Issue: unknown, P. 101416 - 101416

Published: May 1, 2023

The COVID-19 pandemic generated large amounts of diverse data, including testing, treatments, vaccine trials, data from modeling, etc. To support epidemiologists and modeling scientists in their efforts to understand respond the pandemic, there arose a need for web visualization visual analytics (VIS) applications provide insights decision-making. In this paper, we present RAMPVIS, an infrastructure designed range observational, analytical, model-developmental, dissemination tasks. One main features system is ability "propagate" one source similar ones, allows user quickly visualize data. addition COVID RAMPVIS software may be adapted used with different rapid other emergency responses.

Language: Английский

Citations

0
Visual Analytics based Search-Analyze-Forecast Framework for Epidemiological Time-series Data DOI

Tuna Gonen,

Yiwen Xing,

Çağatay Turkay

et al.

Published: Oct. 22, 2023

The COVID-19 pandemic has been a period where time-series of disease statistics, such as the number cases or vaccinations, have intensively used by public health professionals to estimate how their region compares others and what future could look like at home. Conventional visualizations are often limited in terms advanced comparative features supporting forecasting systematically. This paper presents visual analytics approach support data-driven prediction based on search-analyze-predict process comprising multi-metric, multi-criteria search method technique. These supported visualization framework for comprehensive comparison multiple time-series. We inform design our getting iterative feedback from experts globally, evaluate it both quantitatively qualitatively.

Language: Английский

Citations

0