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In Interactive journal of medical research

BACKGROUND : The COVID-19 pandemic has triggered the greater use of digital technologies as part of the healthcare response in many countries, including in Indonesia.

OBJECTIVE : The objective of our study was to identify and review the use of digital health technologies in COVID-19 detection and response management in Indonesia. It is the world's fourth most populous nation, and Southeast Asia's most populous country, with considerable public health pressures.

METHODS : This paper conducted a literature review of publicly accessible information in technical and scientific journals, as well as news articles between September 2020 to August 2022 to identify the use case examples of digital technologies in COVID-19 detection and response management in Indonesia.

RESULTS : The results are presented into three groups, namely (i) Big Data, Artificial Intelligence and Machine Learning (technologies for the collection and/or processing of data); (ii) Healthcare System Technologies (acting at the public health level); and (iii) Population Treatment (acting at the individual patient level). Some of these technologies are the result of government-academia-private sector collaborations during the pandemic, which represent a novel, multi-sectoral practice in Indonesia within the public healthcare ecosystem. A small number of the identified technologies pre-existed the pandemic, but were upgraded and adapted for the current needs.

CONCLUSIONS : Digital technologies were developed in Indonesia during the pandemic, with a direct impact in supporting the COVID-19 management, detection, response, and treatment. They addressed different areas of the technological spectrum, and with different levels of adoption, ranging from local, regional to national. The indirect impact from this wave of technological creation and use, is to provide a strong foundation for fostering future multi-sectoral collaboration within the national healthcare system of Indonesia.

Nur Aisyah Dewi, Lokopessy Alfiano Fawwaz, Naman Maryan, Diva Haniena, Manikam Logan, Adisasmito Wiku, Kozlakidis Zisis