A case for ongoing structural support to maximise infectious disease modelling efficiency for future public health emergencies: A modelling perspective
Epke A. Le Rutte,
Andrew J. Shattock,
Cheng Zhao,
Soushieta Jagadesh,
Miloš Balać,
Sebastian A. Müller,
Kai Nagel,
Alexander L. Erath,
Kay W. Axhausen,
Thomas P. Van Boeckel,
Melissa A. Penny
Affiliations
Epke A. Le Rutte
Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
Andrew J. Shattock
Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
Cheng Zhao
Health Geography and Policy group, ETH Zurich, Switzerland
Soushieta Jagadesh
Health Geography and Policy group, ETH Zurich, Switzerland
Miloš Balać
Institute of Transport planning and systems, ETH Zurich, Switzerland
Sebastian A. Müller
Transport Systems Planning and Transport Telematics, TU Berlin, Berlin, Germany
Kai Nagel
Transport Systems Planning and Transport Telematics, TU Berlin, Berlin, Germany
Institute of Transport planning and systems, ETH Zurich, Switzerland
Thomas P. Van Boeckel
Health Geography and Policy group, ETH Zurich, Switzerland; Department of Infectious Diseases, Institute for Biomedicine, University of Gothenburg, Gothenburg, Sweden; One Health Trust, Washington, DC, USA
Melissa A. Penny
Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland; Corresponding author at: Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
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.
