Details

Autor(en) / Beteiligte

• Hamilton, Kerry A
• Ciol Harrison, Joanna
• Mitchell, Jade
• Weir, Mark
• Verhougstraete, Marc
• Haas, Charles N
• Nejadhashemi, A Pouyan
• Libarkin, Julie
• Gim Aw, Tiong
• Bibby, Kyle
• Bivins, Aaron
• Brown, Joe
• Dean, Kara
• Dunbar, Gwyneth
• Eisenberg, Joseph N S
• Emelko, Monica
• Gerrity, Daniel
• Gurian, Patrick L
• Hartnett, Emma
• Jahne, Michael
• Jones, Rachael M
• Julian, Timothy R
• Li, Hongwan
• Li, Yanbin
• Gibson, Jacqueline MacDonald
• Medema, Gertjan
• Meschke, J Scott
• Mraz, Alexis
• Murphy, Heather
• Oryang, David
• Owusu-Ansah, Emmanuel de-Graft Johnson
• Pasek, Emily
• Pradhan, Abani K
• Razzolini, Maria Tereza Pepe
• Ryan, Michael O
• Schoen, Mary
• Smeets, Patrick W M H
• Soller, Jeffrey
• Solo-Gabriele, Helena
• Williams, Clinton
• Wilson, Amanda M
• Zimmer-Faust, Amy
• Alja'fari, Jumana
• Rose, Joan B

Titel

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

Ist Teil von

• Risk analysis, 2024-05

Ort / Verlag

United States

Erscheinungsjahr

2024

Quelle

Wiley Blackwell Single Titles

Beschreibungen/Notizen

• 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.