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

Challenges for modelling interventions for future pandemics DOI Creative Commons
Mirjam Kretzschmar, Ben Ashby, Elizabeth Fearon

et al.

Epidemics, Journal Year: 2022, Volume and Issue: 38, P. 100546 - 100546

Published: Feb. 11, 2022

Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical pharmaceutical interventions for the control of epidemics that has been widely used during COVID-19 pandemic. In this paper, lessons learned from previous are highlight challenges future pandemic control. We consider availability use data, as well need correct parameterisation calibration model frameworks. discuss arise in describing distinguishing between interventions, within structures, allowing both host dynamics. also health economic political aspects interventions. Given diversity these challenges, broad variety interdisciplinary expertise is needed address them, combining mathematical knowledge with biological social insights, including economics communication skills. Addressing requires strong cross-disciplinary collaboration together close scientists policy makers.

Language: Английский

Citations

62
Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling DOI Creative Commons
Ben Swallow, Paul Birrell, Joshua Blake

et al.

Epidemics, Journal Year: 2022, Volume and Issue: 38, P. 100547 - 100547

Published: Feb. 10, 2022

The estimation of parameters and model structure for informing infectious disease response has become a focal point the recent pandemic. However, it also highlighted plethora challenges remaining in fast robust extraction information using data models to help inform policy. In this paper, we identify discuss four broad paradigm relating modelling, namely Uncertainty Quantification framework, estimation, model-based inference prediction, expert judgement. We postulate priorities methodology facilitate preparation future pandemics.

Language: Английский

Citations

33
The challenges of data in future pandemics DOI Creative Commons
Nigel Shadbolt, Alys Brett, Min Chen

et al.

Epidemics, Journal Year: 2022, Volume and Issue: 40, P. 100612 - 100612

Published: July 20, 2022

The use of data has been essential throughout the unfolding COVID-19 pandemic. We have needed it to populate our models, inform understanding, and shape responses disease. However, not always easy find access, varied in quality coverage, difficult reuse or repurpose. This paper reviews these other challenges recommends steps develop a ecosystem better able deal with future pandemics by supporting preparedness, prevention, detection response.

Language: Английский

Citations

23
A hybrid simulation approach for analyzing trends of infectious disease development, intervention measures and medical cost DOI

Hongli Zhu,

Fengyuan Jia,

Fengwei Jia

et al.

Journal of Simulation, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 26

Published: April 12, 2025

Language: Английский

Citations

0
RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses DOI Creative Commons
Min Chen, Alfie Abdul‐Rahman, Daniel Archambault

et al.

Epidemics, Journal Year: 2022, Volume and Issue: 39, P. 100569 - 100569

Published: April 28, 2022

The effort for combating the COVID-19 pandemic around world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges epidemiology, healthcare, biosciences, social sciences, there been an urgent need develop provide visualisation visual analytics (VIS) capacities support emergency responses under difficult operational conditions. this paper, we report experience group VIS volunteers who have working large research development consortium providing various observational, analytical, model-developmental, disseminative tasks. particular, describe our approaches that encountered requirements analysis, data acquisition, design, software system development, team organisation, resource planning. By reflecting on experience, propose set recommendations as first step towards methodology developing rapid responses.

Language: Английский

Citations

16
Modelling the spread and mitigation of an emerging vector-borne pathogen: Citrus greening in the U.S. DOI Creative Commons
Viet-Anh Nguyen, David W. Bartels, Christopher A. Gilligan

et al.

PLoS Computational Biology, Journal Year: 2023, Volume and Issue: 19(6), P. e1010156 - e1010156

Published: June 2, 2023

Predictive models, based upon epidemiological principles and fitted to surveillance data, play an increasingly important role in shaping regulatory operational policies for emerging outbreaks. Data parameterising these strategically models are often scarce when rapid actions required change the course of epidemic invading a new region. We introduce test flexible framework landscape-scale disease management vector-borne pathogen use with endemic vector populations. analyse predict spread Huanglongbing or citrus greening U.S. estimate parameters using survey data from one region (Texas) show how transfer construct predictive spatio-temporal another (California). The used screen effective coordinated reactive strategies different regions.

Language: Английский

Citations

9
Challenges on the interaction of models and policy for pandemic control DOI Creative Commons
Liza Hadley, Peter Challenor, Chris Dent

et al.

Epidemics, Journal Year: 2021, Volume and Issue: 37, P. 100499 - 100499

Published: Aug. 30, 2021

The COVID-19 pandemic has seen infectious disease modelling at the forefront of government decision-making. Models have been widely used throughout to estimate pathogen spread and explore potential impact different intervention strategies. Infectious modellers policymakers worked effectively together, but there are many avenues for progress on this interface. In paper, we identify discuss seven broad challenges interaction models policy control. We then conclude with suggestions recommendations future.

Language: Английский

Citations

20
Precision epidemiology at the nexus of mathematics and nanotechnology: Unraveling the dance of viral dynamics DOI
Alaa A. A. Aljabali, Mohammad A. Obeid, Mohamed El‐Tanani

et al.

Gene, Journal Year: 2024, Volume and Issue: 905, P. 148174 - 148174

Published: Jan. 18, 2024

Language: Английский

Citations

2
A framework for incorporating behavioural change into individual‐level spatial epidemic models DOI Creative Commons
Madeline A. Ward, Rob Deardon, Lorna E. Deeth

et al.

Canadian Journal of Statistics, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 21, 2024

Abstract Epidemic trajectories can be substantially impacted by people modifying their behaviours in response to changes perceived risk of spreading or contracting the disease. However, most infectious disease models assume a stable population behaviour. We present flexible new class models, called behavioural change individual‐level (BC‐ILMs), that incorporate both covariate information and data‐driven effect. Focusing on spatial BC‐ILMs, we consider four “alarm” functions model effect as function infection prevalence over time. Through simulation studies, find if is present, using an alarm function, even specified incorrectly, will result improvement posterior predictive performance assumes The methods are applied data from 2001 U.K. foot mouth epidemic. results show some evidence effect, although it may not meaningfully impact fit compared simpler ILM this dataset.

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