Introducing a Regulatory Sandbox Into the Indonesian Health System Using e-Malaria as a Use Case: Participatory Action Study.

Background: Regulatory sandboxes offer an alternative solution to address regulatory challenges in adopting disruptive technologies. Although regulatory sandboxes have been widely implemented in the financial sector across more than 50 countries, their application to the health sector remains limited.

Objective: This study aims to explore stakeholders' perspectives on introducing a regulatory sandbox into the Indonesian health system using e-malaria as a use case.

Mental Health Teleconsultation Patterns on the Most Popular mHealth Platforms in Indonesia.

Access to telehealth services increased significantly during the COVID-19 pandemic in Indonesia, including for mental health. This study aims to analyze the patterns and variations of mental health teleconsultation (especially for insomnia and depression) on selected Android-based mHealth platforms in Indonesia. We performed 32 teleconsultation sessions on 8 most popular mHealth platforms.

Comparison of Non-AI and AI-Enabled M-Health Platforms for COVID-19 Self Screening in Indonesia.

This study aimed to analyze and differentiate the role of AI and no AI-supported m-health platforms for COVID-19 self-screening in Indonesia. We utilized a mysterious shopping method to develop four standardized cases with various severity levels of COVID-19 tested in Indonesia's most popular mHealth platforms. We selected seven apps from the top 200 free mHealth apps in the "Medical" category in the Google Play Store equipped with COVID-19 symptom checkers.

Community Mobility and COVID-19 Dynamics in Jakarta, Indonesia.

In response to the COVID-19 pandemic, mobile-phone data on population movement became publicly available, including Google Community Mobility Reports (CMR). This study explored the utilization of mobility data to predict COVID-19 dynamics in Jakarta, Indonesia. We acquired aggregated and anonymized mobility data sets from 15 February to 31 December 2020.

Social media sentiment analysis to monitor the performance of vaccination coverage during the early phase of the national COVID-19 vaccine rollout.

Background And Objective: Social media sentiment analysis based on Twitter data can facilitate real-time monitoring of COVID-19 vaccine-related concerns. Thus, the governments can adopt proactive measures to address misinformation and inappropriate behaviors surrounding the COVID-19 vaccine, threatening the success of the national vaccination campaign. This study aims to identify the correlation between COVID-19 vaccine sentiments expressed on Twitter and COVID-19 vaccination coverage, case increase, and case fatality rate in Indonesia.

Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study.

Background: Given the ongoing COVID-19 pandemic situation, accurate predictions could greatly help in the health resource management for future waves. However, as a new entity, COVID-19's disease dynamics seemed difficult to predict. External factors, such as internet search data, need to be included in the models to increase their accuracy.

Mapping and Visualization of Cancer Research in Indonesia: A Scientometric Analysis.

Introduction: The incidence of cancer and its prevalence are increasing in Indonesia. It is crucial to ensure national cancer policies are evidence-based and promote research. While cancer research is being conducted across Indonesia, the extent and focus of research activities are not known, with no existing synthesis of the cancer research landscape.

Design and prototype of TOMO: an app for improving drug resistant TB treatment adherence.

Drug resistance and multi drugs tuberculosis (DR/MDR-TB) are associated with patients' low adherence to undergoing complex treatment. Driven by the increasing use and penetration of a smartphone and the End of TB Strategy that seeks for digital health solution, Center for Tropical Medicine Universitas Gadjah Mada has developed TOMO, an Android-based app for improving medication adherence in MDR-TB. This paper aims to present the sequential steps to develop the app, its general architecture, and its functionalities.

High variability in model performance of Google relative search volumes in spatially clustered COVID-19 areas of the USA.

Objective: Incorporating spatial analyses and online health information queries may be beneficial in understanding the role of Google relative search volume (RSV) data as a secondary public health surveillance tool during pandemics. This study identified coronavirus disease 2019 (COVID-19) clustering and defined the predictability performance of Google RSV models in clustered and non-clustered areas of the USA.

Methods: Getis-Ord General and local G statistics were used to identify monthly clustering patterns.

Understanding the Community Risk Perceptions of the COVID-19 Outbreak in South Korea: Infodemiology Study.

Background: South Korea is among the best-performing countries in tackling the coronavirus pandemic by using mass drive-through testing, face mask use, and extensive social distancing. However, understanding the patterns of risk perception could also facilitate effective risk communication to minimize the impacts of disease spread during this crisis.

Objective: We attempt to explore patterns of community health risk perceptions of COVID-19 in South Korea using internet search data.

Development and validation of an instrument for measuring competencies on public health informatics of primary health care worker (PHIC4PHC) in Indonesia.

Because of the increasing adoption and use of technology in primary health care (PHC), public health informatics competencies (PHIC) are becoming essential for public health workers. Unfortunately, no studies have measured PHIC in resource-limited setting. This paper describes the process of developing and validating Public Health Informatics Competencies for Primary Health Care (PHIC4PHC), an instrument for measuring PHC workers' competencies in public health informatics.

Improving Dengue Surveillance System with Administrative Claim Data in Indonesia: Opportunities and Challenges.

Administrative claim data is believed as one of the promising data set to augment the mandatory surveillance system which suffered from under-reporting and delay in reporting. Therefore, this study aims to examine whether the Indonesian National Health Insurance (INHI) sample data could complement dengue case-based surveillance system in a more practical way. Afterwards, this analysis also identified several future opportunities and challenges in improving the dengue surveillance system.

Epidemiology and risk factors of Strongyloides stercoralis infection in Papua, Indonesia: a molecular diagnostic study.

Strongyloides stercoralis is a parasitic worm that is of considerable clinical relevance. Indeed, it may persist asymptomatically for many years, but can lead to potentially fatal dissemination when the host's immune status is impaired. As commonly employed stool microscopy techniques (e.

Applications of Google Search Trends for risk communication in infectious disease management: A case study of the COVID-19 outbreak in Taiwan.

Objective: An emerging outbreak of a novel coronavirus, COVID-19, has now been detected in at least 211 countries worldwide. Given this pandemic situation, robust risk communication is urgently needed, particularly in affected countries. Therefore, this study explored the potential use of Google Trends (GT) to monitor public restlessness toward COVID-19 infection in Taiwan.

Developing an Indonesia's health literacy short-form survey questionnaire (HLS-EU-SQ10-IDN) using the feature selection and genetic algorithm.

Background And Objective: Measuring health literacy becomes more important because its association with health status and healthcare outcomes. Studies have developed at least 133 measurement tools for health literacy. HLS-EU-Q47 is a questionnaire consisting of 12 sub-dimensions and 47 questions developed by the Europe Health Literacy Consortium.

Correlation between Google Trends on dengue fever and national surveillance report in Indonesia.

: Digital traces are rapidly used for health monitoring purposes in recent years. This approach is growing as the consequence of increased use of mobile phone, Internet, and machine learning. Many studies reported the use of Google Trends data as a potential data source to assist traditional surveillance systems.

Encouraging On-Time Completion of Leprosy Patients Treatment: Implementing E-Leprosy Framework to Primary Health Care in Indonesia.

Low adherence to leprosy treatment is the main challenge in Indonesia. This is a quasi-experimental observational study in a real setting of a leprosy control program in Indonesia. The study is aimed at evaluating an e-leprosy framework in increasing the rate of on-time attendance at primary health care and on-time completion of treatment of leprosy patients.

Spatiotemporal patterns of malaria at cross-boundaries area in Menoreh Hills, Java, Indonesia.

Background: Comprehensive reports of malaria in Menoreh Hills, Central Java, Indonesia, a unique district cross-boundaries area under three districts and two provinces have been published previously. However, no study was performed to identify the hotspots of malaria in this cross-boundaries area, Kaligesing and Bagelen Subdistricts in Purworejo, Jawa Tengah Province and Kokap Subdistrict in Kulon Progo, Yogyakarta Province, using a longitudinal spatial data.

Methods: Monthly reports of malaria cases at primary health centres during 2005-2015 were collected and processed with ArcGIS and SaTScan to identify the malaria distribution at the village level.

UTAUT for HSS: initial framework to study health IT adoption in the developing countries.

Unified Theory of Acceptance and Use of Technology (UTAUT) is an integrative concept that has been used widely to measure IT adoption. However, a recent study in a developing country concluded that UTAUT is not adequate in predicting IT adoption within the context of health system strengthening (HSS). It has been suggested that context-specific dimensions to modify UTAUT should be considered.

Ten-years trend of dengue research in Indonesia and South-east Asian countries: a bibliometric analysis.

Background: Dengue fever is a mosquito-borne viral disease with high incidence in over 128 countries. WHO estimates 500,000 people with severe dengue are hospitalized annually and 2.5% of those affected die.

Metadata Correction: Importance-Performance Analysis of Personal Health Records in Taiwan: A Web-Based Survey.

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Importance-Performance Analysis of Personal Health Records in Taiwan: A Web-Based Survey.

Background: Empowering personal health records (PHRs) provides basic human right, awareness, and intention for health promotion. As health care delivery changes toward patient-centered services, PHRs become an indispensable platform for consumers and providers. Recently, the government introduced "My health bank," a Web-based electronic medical records (EMRs) repository for consumers.

Development of a web-based liver cancer prediction model for type II diabetes patients by using an artificial neural network.

Background: Diabetes mellitus is associated with an increased risk of liver cancer, and these two diseases are among the most common and important causes of morbidity and mortality in Taiwan.

Purpose: To use data mining techniques to develop a model for predicting the development of liver cancer within 6 years of diagnosis with type II diabetes.

Methods: Data were obtained from the National Health Insurance Research Database (NHIRD) of Taiwan, which covers approximately 22 million people.

Change of strategy is required for malaria elimination: a case study in Purworejo District, Central Java Province, Indonesia.

Background: Malaria has been targeted for elimination from Indonesia by 2030, with varying timelines for specific geographical areas based on disease endemicity. The regional deadline for malaria elimination for Java island, given the steady decrease of malaria cases, was the end of 2015. Purworejo District, a malaria-endemic area in Java with an annual parasite incidence (API) of 0.