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Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of COVID-19 burden in the US to guide pandemic planning and decision-making in the context of high uncertainty. This effort was born out of an attempt to coordinate, synthesize and effectively use the unprecedented amount of predictive modeling that emerged throughout the COVID-19 pandemic. Here we describe the history of this massive collective research effort, the process of convening and maintaining an open modeling hub active over multiple years, and attempt to provide a blueprint for future efforts. We detail the process of generating 17 rounds of scenarios and projections at different stages of the COVID-19 pandemic, and disseminating results to the public health community and lay public. We also highlight how SMH was expanded to generate influenza projections during the 2022-23 season. We identify key impacts of SMH results on public health and draw lessons to improve future collaborative modeling efforts, research on scenario projections, and the interface between models and policy.
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http://dx.doi.org/10.1016/j.epidem.2023.100738 | DOI Listing |
BMC Public Health
September 2025
Department of Mathematics, Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Gottlieb-Daimler-Str.48, Kaiserslautern, 67663, Germany.
We study the dynamics of coexisting influenza and SARS-CoV-2 by adapting a well-established age-specific COVID-19 model to a multi-pathogen framework. Sensitivity analysis and adjustment of the model to real-world data are used to investigate the influence of age-related factors on disease dynamics. Our findings underscore the critical role that transmission rates play in shaping the spread of influenza and COVID-19.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
September 2025
Faculdade de Engenharia da Universidade do Porto, INESC TEC, Porto, Portugal.
Food waste generated throughout the food supply chain raises several environmental, social, and economic issues. Quantitative methods can aid in managing food waste by describing current contexts, predicting future scenarios, and improving related operations. However, a literature review on the use of quantitative methods, specifically the descriptive, predictive, and prescriptive dimensions, to assess and prevent food waste is lacking.
View Article and Find Full Text PDFMed Eng Phys
October 2025
Department of Engineering Science, University of Oxford, United Kingdom. Electronic address:
Traditionally, clinical devices are designed, tested and improved through lengthy and expensive laboratory experiments and clinical trials [1]. More recently, computational methods have allowed for rapid testing, speeding up the design process and enabling far more complete searches of design space. While computational models cannot fully capture the complexities of biological systems, they provide valuable insights into crucial underlying mechanisms, such as the effects of fluid-structure interactions (FSIs).
View Article and Find Full Text PDFJ R Soc Interface
September 2025
UK Centre for Ecology & Hydrology, Wallingford, Oxfordshire, UK.
Severe fever with thrombocytopaenia syndrome virus (SFTSV) was identified by the World Health Organization as a priority pathogen due to its high case-fatality rate in humans and rapid spread. It is maintained in nature through three transmission pathways: systemic, non-systemic and transovarial. Understanding the relative contributions of these transmission pathways is crucial for developing evidence-informed public health interventions to reduce its spillover risks to humans.
View Article and Find Full Text PDFJ Colloid Interface Sci
September 2025
Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Province, College of Engineering, Zhejiang Normal University, Jinhua 321004, China. Electronic address:
Developing high-performance wearable flexible sensors that can adapt well to complex environments has become a hotspot. Herein, a polyvinyl alcohol based composite hydrogel sensor with high mechanical strength, desirable frost/swelling resistance, and highly sensitive sensing performance was proposed by a multi-component collaborative design strategy. Meanwhile, an intelligent gesture recognition system was established by combining machine learning algorithm.
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