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Published on: April 6, 2019
Advancing adoptability and sustainability of digital prediction tools for climate-sensitive infectious disease
Dung Phung1,2, Felipe J Colón-González3, Daniel M Weinberger4
1School of Public Health, The University of Queensland, Brisbane, Queensland, Australia. d.phung@uq.edu.au.
Abstract:
Few forecasting models have been translated into digital prediction tools for prevention and control of climate-sensitive infectious diseases. We propose a 3-U (useful, usable, and used) research framework for advancing the adoptability and sustainability of these tools. We make recommendations for 1) developing a tool with a high level of accuracy and sufficient lead time to permit effective proactive interventions (useful); 2) conducting a needs assessment to ensure that a tool meets the needs of end-users (usable); and 3) demonstrating the efficacy and cost-effectiveness of a tool to secure its adoption into routine surveillance and response systems (used).
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