Advancing adoptability and sustainability of digital prediction tools for climate-sensitive infectious disease prevention and control
Dung Phung, Felipe J. Colón‐González, Daniel M. Weinberger, Vinh Bui, Son Nghiem, Cordia Chu, Hai Phung, Nam Vu, Quang‐Van Doan, Masahiro Hashizume, Colleen L. Lau, Simon Reid, Phan Trong Lan, Duong Nhu Tran, Cong Tuan Pham, Do Kien Quoc, Robert Dubrow
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).