Background: Digital health has progressed rapidly due to the advances in technology and the promises of improved health and personal health empowerment. Concurrently, the burden of respiratory disease is increasing, particularly in Asia, where mortality rates are higher, and public awareness and government engagement are lower than in other regions of the world. Leveraging digital health interventions to manage and mitigate respiratory disease presents itself as a potentially effective approach. This study aims to undertake a scoping review to map respiratory digital health interventions in South and Southeast Asia, identify existing technologies, opportunities, and gaps, and put forward pertinent recommendations from the insights gained. Methods: This study used a scoping review methodology as outlined by Arksey and O’Malley and the Joanna Briggs Institute. Medline, Embase, CINAHL, PsycINFO, Cochrane Library, Web of Science, PakMediNet and MyMedR databases were searched along with key websites grey literature databases. Results: This scoping review has extracted and analysed data from 87 studies conducted in 14 South and Southeast Asian countries. Results were mapped to the WHO classification of digital health interventions categories to better understand their use. Digital health interventions are primarily being used for communication with patientes and between patients and providers. Moreover, interventions targeting tuberculosis were the most numerous. Many ‘old’ interventions, such as SMS, are still being used but updated. Artificial intelligence and machine learning are also widely used in the region at a small scale. There was a high prevalence of pilot interventions compared to mature ones. Conclusions: This scoping review collates and synthesises information and knowledge in the current state of digital health interventions, showing that there is a need to evaluate whether a pilot project is needed before starting, there is a need to report on interventions systematically to aid evaluation and lessons learnt, and that artificial intelligence and machine learning interventions are promising but should adhere to best ethical and equity practices.
