How understanding the diversity of perspectives and systems in governments can increase the impact of scientific research
Year: 2026
Type: article
Abstract: The COVID-19 crisis required scientists worldwide to contribute to complex, hectic, and unfamiliar governmental decision-processes. In this Perspective, we reflect on this intense interaction between science and health policy for pandemic response, drawing from the experience of infectious disease modellers across the world. We highlight the diversity of actors and interests in government, aiming to demystify the elusive 'policy makers'. We present a general taxonomy to help research scientists more effectively support evidence-based policy. We stress the importance of building and maintaining relationships appropriate to the diverse pool of government actors. Not recognising this diversity may lead to miscommunication and reduce the positive impacts of scientific evidence for public policy in crisis and non-crisis situations.
Source: Communications Health
Authors: Liza Hadley, Slimane Ben Miled, Hannah E. Clapham, Bimandra A. Djaafara, Louise Dyson, Sebastian Funk, Julia R. Gog, Hans Heesterbeek, Edward M. Hill, Emily Howerton, Valerie Isham, Amira Kebir, Matt Keeling, Stephen M. Kissler, Justin Lessler, Kathy Leung, Emma McBryde, James M. McCaw, Chris Erwin G. Mercado, Denis Mollison, S. M. Thumbi, Wirichada Pan-ngum, Lorenzo Pellis, Francisco J. Pérez-Reche, Michael J. Plank, Robin N. Thompson, Cécile Tran-Kiem
Institutions: University of Colorado Boulder, University of Cambridge, Tunis University, Institut Pasteur de Tunis, Tunis El Manar University, National University of Singapore, National University Health System, University of Indonesia, Oxford University Clinical Research Unit Indonesia, University of Warwick, London School of Hygiene & Tropical Medicine, Utrecht University, University of Liverpool, Health Protection Research Unit in Emerging and Zoonotic Infections at University of Liverpool, Princeton University, University College London, University of North Carolina at Chapel Hill, Johns Hopkins University, Hong Kong University of Science and Technology, Hong Kong Jockey Club, University of Hong Kong - Shenzhen Hospital, Laboratory of Data Discovery for Health, University of Hong Kong, The University of Queensland, The University of Melbourne, Heriot-Watt University, University of Nairobi, Washington State University, University of Edinburgh, Mahidol University, Mahidol Oxford Tropical Medicine Research Unit, University of Manchester, King's College London, University of Aberdeen, University of Canterbury, Te Pūnaha Matatini, University of Oxford, Fred Hutch Cancer Center
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
Funders: Vaccine Impact Modelling Consortium, National Science Foundation, U.S. Department of Health and Human Services, Bill and Melinda Gates Foundation, GAVI Alliance, Princeton University, Washington State University, Johns Hopkins University, London School of Hygiene and Tropical Medicine, Heriot-Watt University, Wellcome Trust, UK Research and Innovation, National Institute for Health Research Health Protection Research Unit, National Institute for Health and Care Research, Department of Health and Social Care, University of Warwick, University College London, University of Oxford, University of Manchester, University of Liverpool, University of Aberdeen, National University of Singapore, Royal Society Te Apārangi, University of Melbourne, University of Queensland, Universiteit Utrecht, Innovation and Technology Commission, University of Hong Kong, Institute of Environmental Science and Research, Liverpool John Moores University, Mahidol University, Hong Kong University of Science and Technology, Universitas Indonesia, Innovation and Technology Commission - Hong Kong, Université de Tunis, National University Health System, Université de Tunis El Manar, University of Hong Kong-Shenzhen Hospital, Institut Pasteur de Tunis, National Institutes of Health, Centers for Disease Control and Prevention, University of Colorado Boulder, University of North Carolina at Chapel Hill, Johns Hopkins Bloomberg School of Public Health, Medical Research Council, Engineering and Physical Sciences Research Council, Australian Research Council, National Health and Medical Research Council, Faculty of Tropical Medicine, Mahidol University, Marsden Fund, Fakultas Kedokteran, Universitas Indonesia, National Cancer Institute, Division of Mathematical Sciences, Carolina Population Center, University of North Carolina at Chapel Hill, Hong Kong Jockey Club
Awards: Thailand Africa and Asia Programme - GBP Core, G1163917794, Isaac Newton Institute for Mathematical Sciences (INI), G1213559922, G1234541941, G1493763487, Real-time modelling for forecasts during infectious disease outbreaks, G2259086438, MPOPHC: Quantitative design of effective testing-based policies through infection trajectory modeling, G2686910782, G2938587418, Thailand Africa and Asia Programme - GBP Core, Using data to improve public health: COVID-19 secondment, G4205538619, G4689185066, Imperial College London - to support the Vaccine Impact Modeling Consortium to provide modeling that supports efforts to reduce the burden of vaccine preventable diseases, Detection and identification of damage in composite fibre/metal laminate structures using guided ultrasonic waves, G5889588243, G5907235390, University of Nairobi - to support the University of Nairobi to strengthen the Centre for Epidemiological Modelling and Analysis (CEMA) to be a public good resource provid..., G6252953675, G6425325077, JUNIPER Partnership, Real-time modelling for forecasts during infectious disease outbreaks, Imperial College London - to improve the quality and timeliness of estimates of the impact of Gavi-funded vaccination programs via the establishment of a Vaccine Impact Mode..., G7640496707, G7913066000, G7975837827, Harnessing epidemiological and genomic data for understanding of respiratory virus transmission at multiple scales, Institut Pasteur de Tunis - to facilitate South-South data-centered collaborations and strengthen existing networks as well as modeling and analytics ecosystems., G8559613873, G8605616652, G8972344215
OpenAlex ID: W7170075525