Evidence map›Paper›PMID 36623206›Full record

ArticleInteractive journal of medical research2023

The Use of Digital Technology for COVID-19 Detection and Response Management in Indonesia: Mixed Methods Study.

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

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Article in Interactive journal of medical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Dewi Nur Aisyah *Indonesia One Health University Network, Depok, Indonesia.ORCID https://orcid.org/0000-0003-2247-0612
Alfiano Fawwaz Lokopessy *Indonesia One Health University Network, Depok, Indonesia.ORCID https://orcid.org/0000-0001-7001-4094
Maryan Naman *Aceso Global Health Consultants Pte Limited, Singapore, Singapore.ORCID https://orcid.org/0000-0002-1861-7602
Haniena Diva *Indonesia One Health University Network, Depok, Indonesia.ORCID https://orcid.org/0000-0001-6014-7387
Logan Manikam *Department of Epidemiology and Public Health, Institute of Epidemiology and Health Care, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-5288-3325
Wiku Adisasmito *Indonesia One Health University Network, Depok, Indonesia.ORCID https://orcid.org/0000-0002-8788-2362
Zisis Kozlakidis *International Agency for Research on Cancer World Health Organization, Lyon, France.ORCID https://orcid.org/0000-0002-3836-7209

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has triggered a greater use of digital technologies as part of the health care response in many countries, including Indonesia. It is the world's fourth-most populous nation and Southeast Asia's most populous country, with considerable public health pressures.

objectiveThe aim of our study is to identify and review the use of digital health technologies in COVID-19 detection and response management in Indonesia.

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

resultsThe results are presented in 3 groups, namely (1) big data, artificial intelligence, and machine learning (technologies for the collection or processing of data); (2) health care system technologies (acting at the public health level); and (3) COVID-19 screening, population treatment, and prevention 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, multisectoral practice in Indonesia within the public health care ecosystem. A small number of the identified technologies pre-existed the pandemic but were upgraded and adapted for current needs.

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

Indexed as

COVID-19decontaminationdigital healthdigital innovationdigital technologyIndonesiaresponse managementrobot innovation

Identifiers

PMID36623206
PMCPMC10012204

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read1
measurements read13
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.