COVID-19 disease modellers lacked structured training, policy, and data networks.
•Need for capacity strengthening outside infectious disease emergencies through.
•Trained experts continuously advancing state-of-the-art methodologies.
•Structural liaisons amongst scientists and decision-makers.
•Foundation and management of data-sharing frameworks.
AbstractThis 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.
KeywordsPublic health emergency
Modelling
COVID-19
SARS-CoV-2
Pandemic
Policy
© 2023 The Authors. Published by Elsevier B.V.
Comments (0)