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<p>Few forecasting models have been translated into digital prediction tools for prevention and control of climate-sensitive infectious diseases. We propose a <i>3-U</i> (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 (<i>useful</i>); 2) conducting a needs assessment to ensure that a tool meets the needs of end-users (<i>usable</i>); and 3) demonstrating the efficacy and cost-effectiveness of a tool to secure its adoption into routine surveillance and response systems (<i>used)</i>.</p>

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Advancing adoptability and sustainability of digital prediction tools for climate-sensitive infectious disease prevention and control

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月14日

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  • Dung Phung,
  • Felipe J. Colón-González,
  • Daniel M. Weinberger,
  • Vinh Bui,
  • Son Nghiem,
  • Cordia Chu,
  • Hai Phung,
  • Nam Sinh Vu,
  • Quang-Van Doan,
  • Masahiro Hashizume,
  • Colleen L. Lau,
  • Simon Reid,
  • Lan Trong Phan,
  • Duong Nhu Tran,
  • Cong Tuan Pham,
  • Kien Quoc Do,
  • Robert Dubrow

摘要

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).