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Published (Version of record)CC BY V4.0, Open Access
Published (Version of record)CC BY V4.0, Open
Journal article
Advancing adoptability and sustainability of digital prediction tools for climate-sensitive infectious disease prevention and control
Nature communications, Vol.16(1), pp.1-8
14/02/2025
PMID: 39952939
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Source: InCites
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).
Details
- Title
- Advancing adoptability and sustainability of digital prediction tools for climate-sensitive infectious disease prevention and control
- Creators
- Dung Phung - The University of QueenslandFelipe J. Colón-González - Wellcome TrustDaniel M. Weinberger - Yale UniversityVinh Bui - Southern Cross UniversitySon Nghiem - Australian National UniversityCordia Chu - Griffith UniversityHai Phung - Griffith UniversityNam Sinh Vu - National Institute Of Hygiene And EpidemiologyQuang-Van Doan - Centre for Computational Sciences, University of TsukubaMasahiro Hashizume - The University of TokyoColleen L. Lau - The University of QueenslandSimon Reid - The University of QueenslandLan Trong Phan - National Institute Of Hygiene And EpidemiologyDuong Nhu Tran - National Institute Of Hygiene And EpidemiologyCong Tuan Pham - Griffith UniversityKien Quoc Do - The University of QueenslandRobert Dubrow - Yale University
- Publication Details
- Nature communications, Vol.16(1), pp.1-8
- Publisher
- Nature Publishing Group; BERLIN
- Grant note
- This work was supported by the Wellcome Trust [226474/Z/22/Z]. F.C.G., an employee of Wellcome Trust, contributed to methodology and reviewed and edited the manuscript as a co-author. C.L.L. was supported by an Australian National Health and Medical Research Council Fellowship (Grant number 1193826).
- Identifiers
- 991013260691202368
- Copyright
- © The Author(s) 2025
- Academic Unit
- Information Technology; Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article