A case for ongoing structural support to maximise infectious disease modelling efficiency for future public health emergencies: A modelling perspective

作者：Epke A. Le Rutte, Andrew J. Shattock, Cheng Zhao, Soushieta Jagadesh, Miloš Balać, Sebastian Alexander Müller, Kai Nagel, Alexander Erath, Kay W. Axhausen, Thomas P. Van Boeckel, Melissa A. Penny · 发表于：Epidemics · 年份：2023 · DOI：10.1016/j.epidem.2023.100734 · 被引用次数：7 · 研究领域：COVID-19 epidemiological studies、Viral Infections and Outbreaks Research、Data-Driven Disease Surveillance

This short communication reflects upon the challenges and recommendations of multiple COVID-19 modelling and data analytic groups that provided quantitative evidence to support health policy discussions in Switzerland and Germany during the SARS-CoV-2 pandemic. Capacity strengthening outside infectious disease emergencies will be required to enable an environment for a timely, efficient, and data-driven response to support decisions during any future infectious disease emergency. This will require 1) a critical mass of trained experts who continuously advance state-of-the-art methodological tools, 2) the establishment of structural liaisons amongst scientists and decision-makers, and 3) the foundation and management of data-sharing frameworks.