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.
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.