Research gaps and priorities for quantitative microbial risk assessment (QMRA).

IF 3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Risk Analysis Pub Date : 2024-11-01 Epub Date: 2024-05-21 DOI:10.1111/risa.14318
Kerry A Hamilton, Joanna Ciol Harrison, Jade Mitchell, Mark Weir, Marc Verhougstraete, Charles N Haas, A Pouyan Nejadhashemi, Julie Libarkin, Tiong Gim Aw, Kyle Bibby, Aaron Bivins, Joe Brown, Kara Dean, Gwyneth Dunbar, Joseph N S Eisenberg, Monica Emelko, Daniel Gerrity, Patrick L Gurian, Emma Hartnett, Michael Jahne, Rachael M Jones, Timothy R Julian, Hongwan Li, Yanbin Li, Jacqueline MacDonald Gibson, Gertjan Medema, J Scott Meschke, Alexis Mraz, Heather Murphy, David Oryang, Emmanuel de-Graft Johnson Owusu-Ansah, Emily Pasek, Abani K Pradhan, Maria Tereza Pepe Razzolini, Michael O Ryan, Mary Schoen, Patrick W M H Smeets, Jeffrey Soller, Helena Solo-Gabriele, Clinton Williams, Amanda M Wilson, Amy Zimmer-Faust, Jumana Alja'fari, Joan B Rose
{"title":"Research gaps and priorities for quantitative microbial risk assessment (QMRA).","authors":"Kerry A Hamilton, Joanna Ciol Harrison, Jade Mitchell, Mark Weir, Marc Verhougstraete, Charles N Haas, A Pouyan Nejadhashemi, Julie Libarkin, Tiong Gim Aw, Kyle Bibby, Aaron Bivins, Joe Brown, Kara Dean, Gwyneth Dunbar, Joseph N S Eisenberg, Monica Emelko, Daniel Gerrity, Patrick L Gurian, Emma Hartnett, Michael Jahne, Rachael M Jones, Timothy R Julian, Hongwan Li, Yanbin Li, Jacqueline MacDonald Gibson, Gertjan Medema, J Scott Meschke, Alexis Mraz, Heather Murphy, David Oryang, Emmanuel de-Graft Johnson Owusu-Ansah, Emily Pasek, Abani K Pradhan, Maria Tereza Pepe Razzolini, Michael O Ryan, Mary Schoen, Patrick W M H Smeets, Jeffrey Soller, Helena Solo-Gabriele, Clinton Williams, Amanda M Wilson, Amy Zimmer-Faust, Jumana Alja'fari, Joan B Rose","doi":"10.1111/risa.14318","DOIUrl":null,"url":null,"abstract":"<p><p>The coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose-response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co-exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source-to-outcome continuum. Cross-cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risk Analysis","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/risa.14318","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/21 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

The coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose-response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co-exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source-to-outcome continuum. Cross-cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.

微生物定量风险评估 (QMRA) 的研究空白和重点。
2019 年冠状病毒疾病大流行凸显了更快速、更常规地应用定量微生物风险评估(QMRA)等建模方法来保护公众健康的必要性。QMRA 是一门致力于了解、预测和减轻传染病风险的跨学科科学。为了让 QMRA 研究人员更好地为政策和公共卫生管理提供信息,我们举办了 QMRA 研究进展研讨会,以总结 QMRA 研究的前进方向。我们总结了 41 位 QMRA 研究人员和专家的见解,通过以下方式阐明 QMRA 在风险分析中的作用:(1)确定关键研究需求;(2)强调 QMRA 的新兴应用;(3)描述数据需求和关键科学工作,以改进 QMRA 科学。确定的主要研究重点包括:在 QMRA 中使用分子工具、推进剂量-反应方法、解决所需的暴露评估、协调 QMRA 的环境监测、统一疾病传播和 QMRA 模型之间的分界线、校准和/或验证 QMRA 模型、共同暴露和混合物建模,以及将变异性和不确定性纳入整个 "从源到果 "过程的标准化实践。已确定的跨领域需求包括:发展研究与实践社区、将 QMRA 与其他科学方法相结合、提高 QMRA 的转化率和影响力、建立沟通战略以及鼓励可持续的供资机制。最后,概述了推进 QMRA 科学的愿景,以便为国家到全球的健康评估、控制和政策提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Risk Analysis
Risk Analysis 数学-数学跨学科应用
CiteScore
7.50
自引率
10.50%
发文量
183
审稿时长
4.2 months
期刊介绍: Published on behalf of the Society for Risk Analysis, Risk Analysis is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. The topics covered include: • Human health and safety risks • Microbial risks • Engineering • Mathematical modeling • Risk characterization • Risk communication • Risk management and decision-making • Risk perception, acceptability, and ethics • Laws and regulatory policy • Ecological risks.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信