Uncertainty Quantification for Expensive COVID-19 Simulation Models (UQ4Covid)

昂贵的 COVID-19 模拟模型的不确定性量化 (UQ4Covid)

• 批准号: EP/V051555/1
• 负责人: Daniel Williamson
• 金额: $ 38.33万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV051555%2F1
• 关键词: Uncertainty; Quantification; Expensive; COVID; 19

Accurate mathematical models of transmission are crucial for targeting successful interventions to combat the spread of SARS-Cov2. In the UK, established models are used to provide real time policy support to Government through the Scientific Pandemic Influenza group - Modelling (SPI-M). Modellers in SPI-M have a proven track record, and models are continually adapted to respond to the evolving pandemic. When using models to inform decision making, it is crucial that all sources of uncertainty are properly accounted for when calibrating and predicting. For 30 years the UK has been a world-leader in developing Uncertainty Quantification (UQ); delivering methods for formal treatments of uncertainty when using models to understand the world, allowing efficient and robust calibration and prediction. Despite this, these techniques are not currently in place for COVID-19 simulation models, leading to slower-than-necessary adaptive model development-UQ allows for fast re-calibration-and an under-representation of uncertainty in predictions delivered to policymakers.This project will adapt and deliver UQ techniques, code and tutorials for models of COVID-19 in the UK, providing SPI-M modellers with tools to facilitate rapid re-calibration of their models when changes are made in response to the evolving pandemic, and to more accurately represent uncertainty in their predictions. We will work closely with MetaWards, a spatial meta-population transmission framework (Danon et al. 2009, 2020) that contributes to SPI-M, to develop and apply these tools as we move into the winter; enabling fast evaluation of interventions responding to localised outbreaks, efficacy of vaccine rollout strategies, duration of immunity and more.

准确的传播数学模型对于成功地采取干预措施以遏制SARS-Cov 2的传播至关重要。在联合王国，已建立的模型被用于通过科学大流行性流感小组-建模（SPI-M）向政府提供真实的及时政策支持。SPI-M中的建模人员有着良好的记录，并且不断调整模型以应对不断变化的流行病。当使用模型为决策提供信息时，在校准和预测时，正确考虑所有不确定性来源至关重要。30年来，英国一直是开发不确定性量化（UQ）的世界领导者;在使用模型了解世界时，提供正式处理不确定性的方法，允许有效和强大的校准和预测。尽管如此，这些技术目前还不适用于COVID-19模拟模型，导致自适应模型开发速度慢于必要-UQ允许快速重新校准-并且在向政策制定者提供的预测中不确定性的代表性不足。该项目将为英国的COVID-19模型调整和提供UQ技术，代码和教程，为SPI-M建模者提供工具，以便在应对不断演变的大流行作出改变时迅速重新校准其模型，并更准确地表示其预测中的不确定性。我们将与MetaWards密切合作，MetaWards是一个有助于SPI-M的空间元人群传播框架（Danon等人，2009年，2020年），在我们进入冬季时开发和应用这些工具;能够快速评估应对局部疫情的干预措施，疫苗推广策略的有效性，免疫力的持续时间等。

项目成果

The population attributable fraction of cases due to gatherings and groups with relevance to COVID-19 mitigation strategies.

• DOI: 10.1098/rstb.2020.0273
• 发表时间: 2021-07-19
• 期刊: Philosophical transactions of the Royal Society of London. Series B, Biological sciences
• 作者: Brooks-Pollock E;Read JM;House T;Medley GF;Keeling MJ;Danon L
• 通讯作者: Danon L

sj-pdf-1-smm-10.1177_09622802211065159 - Supplemental material for Meta-analysis of the severe acute respiratory syndrome coronavirus 2 serial intervals and the impact of parameter uncertainty on the coronavirus disease 2019 reproduction number

sj-pdf-1-smm-10.1177_09622802211065159 - 严重急性呼吸综合征冠状病毒2系列间隔的荟萃分析补充材料以及参数不确定性对冠状病毒病2019繁殖数的影响

• DOI: 10.25384/sage.17697913
• 发表时间: 2021
• 作者: Challen R

Meta-analysis of the severe acute respiratory syndrome coronavirus 2 serial intervals and the impact of parameter uncertainty on the coronavirus disease 2019 reproduction number.

• DOI: 10.1177/09622802211065159
• 发表时间: 2022-09
• 期刊: STATISTICAL METHODS IN MEDICAL RESEARCH
• 影响因子: 2.3
• 作者: Challen, Robert;Brooks-Pollock, Ellen;Tsaneva-Atanasova, Krasimira;Danon, Leon
• 通讯作者: Danon, Leon

Risk of mortality in patients infected with SARS-CoV-2 variant of concern 202012/1: matched cohort study.

• DOI: 10.1136/bmj.n579
• 发表时间: 2021-03-09
• 期刊: BMJ (Clinical research ed.)
• 作者: Challen R;Brooks-Pollock E;Read JM;Dyson L;Tsaneva-Atanasova K;Danon L
• 通讯作者: Danon L

High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions.

与重新开放的大学相关的高共价传播潜力可以通过分层干预来减轻。

• DOI: 10.1038/s41467-021-25169-3
• 发表时间: 2021-08-17
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Brooks-Pollock E;Christensen H;Trickey A;Hemani G;Nixon E;Thomas AC;Turner K;Finn A;Hickman M;Relton C;Danon L
• 通讯作者: Danon L