Developing One Health surveillance systems.

The health of humans, domestic and wild animals, plants, and the environment are inter-dependent. Global anthropogenic change is a key driver of disease emergence and spread and leads to biodiversity loss and ecosystem function degradation, which are themselves drivers of disease emergence. Pathogen spill-over events and subsequent disease outbreaks, including pandemics, in humans, animals and plants may arise when factors driving disease emergence and spread converge. One Health is an integrated approach that aims to sustainably balance and optimize human, animal and ecosystem health. Conventional disease surveillance has been siloed by sectors, with separate systems addressing the health of humans, domestic animals, cultivated plants, wildlife and the environment. One Health surveillance should include integrated surveillance for known and unknown pathogens, but combined with this more traditional disease-based surveillance, it also must include surveillance of drivers of disease emergence to improve prevention and mitigation of spill-over events. Here, we outline such an approach, including the characteristics and components required to overcome barriers and to optimize an integrated One Health surveillance system.

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

BACKGROUND: The 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. OBJECTIVE: The aim of our study is to identify and review the use of digital health technologies in COVID-19 detection and response management in Indonesia. METHODS: We 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. RESULTS: The 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. CONCLUSIONS: Digital 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.

The Use of a Health Compliance Monitoring System During the COVID-19 Pandemic in Indonesia: Evaluation Study.

BACKGROUND: COVID-19 cases are soaring in Asia. Indonesia, Southeast Asia's most populous country, is now ranked second in the number of cases and deaths in Asia, after India. The compliance toward mask wearing, social distancing, and hand washing needs to be monitored to assess public behavioral changes that can reduce transmission. OBJECTIVE: This study aimed to evaluate this compliance in Indonesia between October 2020 and May 2021 and demonstrate the use of the Bersatu Lawan COVID-19 (BLC) mobile app in monitoring this compliance. METHODS: Data were collected in real time by the BLC app from reports submitted by personnel of military services, police officers, and behavioral change ambassadors. Subsequently, the data were analyzed automatically by the system managed by the Indonesia National Task Force for the Acceleration of COVID-19 Mitigation. RESULTS: Between October 1, 2020, and May 2, 2021, the BLC app generated more than 165 million reports, with 469 million people monitored and 124,315,568 locations under observation in 514 districts/cities in 34 provinces in Indonesia. This paper grouped them into 4 colored zones, based on the degree of compliance, and analyzed variations among regions and locations. CONCLUSIONS: Compliance rates vary among the 34 provinces and among the districts and cities of those provinces. However, compliance to mask wearing seems slightly higher than social distancing. This finding suggests that policy makers need to promote higher compliance in other measures, including social distancing and hand washing, whose efficacies have been proven to break the chain of transmission when combined with masks wearing.

Laboratory Readiness and Response for SARS-Cov-2 in Indonesia.

The laboratory diagnosis of SARS-CoV-2 infection comprises the informational cornerstone in the effort to contain the infections. Therefore, the ability to leverage laboratories' capacity in diagnostic testing and to increase the number of people being tested are critical. This paper reviews the readiness of Indonesian laboratories during the early months of the pandemic. It discusses the success of cross-sectoral collaboration among previously siloed national and sub-national government institutions, international development agencies, and private sector stakeholders. This collaboration managed to scale-up the COVID-19 referral laboratory network from one Ministry of Health NIHRD laboratory in the capital to 685 laboratories across 34 provinces. However, this rapid growth within 12 months since the first Indonesian case was discovered remained insufficient to cater for the constantly surging testing demands within the world's fourth most populous country. Reflecting on how other countries built their current pandemic preparedness from past emergencies, this paper highlights challenges and opportunities in workforce shortage, logistic distribution, and complex administration that need to be addressed.

International, Transdisciplinary, and Ecohealth Action for Sustainable Agriculture in Asia.

Sustainably intensifying agriculture to secure food for people, while minimizing the human, animal, and environmental health impacts is an unprecedented global food security challenge. Action research is needed to understand and mitigate impacts, with Ecosystem approaches to health (Ecohealth) emerging as a promising framework to support such efforts. Yet, few have critically examined the application of Ecohealth principles in an agricultural context, particularly in Southeast Asia where agricultural intensification is rapidly expanding. In this paper, we evaluate the strengths, challenges, and opportunities of agriculture-related Ecohealth projects in low-resource settings of Vietnam, Thailand, Indonesia, and China, drawing on a case study of the Field Building Leadership Initiative (FBLI). To do this, we used a developmental evaluation framework involving several iterative cycles of document reviews, interviews, focus groups, and outcome harvesting with researchers, partners, and community members involved in FBLI. Results highlight the importance of transdisciplinarity, participation, and knowledge-to-action principles in co-generating knowledge and co-developing practical solutions. Implementing such principles presents challenges in terms of coordinating regional collaborations, managing high workloads, meaningfully engaging communities, and ensuring ongoing monitoring and evaluation. To address these challenges, there is a need to strengthen capacity in integrated approaches to health, improve institutionalization of Ecohealth, foster community engagement, and systematically monitor and evaluate efforts. Ecohealth holds significant promise in improving food security, but only when considerable time is spent developing and implementing projects with communities.

A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak.

BACKGROUND: Since the first cases reported in Wuhan, China, in December 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread worldwide. In Indonesia, the first case was reported in early March 2020, and the numbers of confirmed infections have been increasing until now. Efforts to contain the virus globally and in Indonesia are ongoing. This is the very first manuscript using a spatial-temporal model to describe the SARS-CoV-2 transmission in Indonesia, as well as providing a patient profile for all confirmed COVID-19 cases. METHOD: Data was collected from the official website of the Indonesia National Task Force for the Acceleration of COVID-19, from the period of 02 March 2020-02 August 2020. The data from RT-PCR confirmed, SARS-CoV-2 positive patients was categorized according to demographics, symptoms and comorbidities based on case categorization (confirmed, recovered, dead). The data collected provides granular and thorough information on time and geographical location for all 34 Provinces across Indonesia. RESULTS: A cumulative total of 111,450 confirmed cases of were reported in Indonesia during the study period. Of those confirmed cases 67.79% (75,551/111,450) were shown as recovered and 4.83% (5,382/111,450) of them as died. Patients were mostly male (50.52%; 56,300/111,450) and adults aged 31 to 45 years old (29.73%; 33,132/111,450). Overall patient presentation symptoms of cough and fever, as well as chronic disease comorbidities were in line with previously published data from elsewhere in South-East Asia. The data reported here, shows that from the detection of the first confirmed case and within a short time period of 40 days, all the provinces of Indonesia were affected by COVID-19. CONCLUSIONS: This study is the first to provide detailed characteristics of the confirmed SARS-CoV-2 patients in Indonesia, including their demographic profile and COVID-19 presentation history. It used a spatial-temporal analysis to present the epidemic spread from the very beginning of the outbreak throughout all provinces in the country. The increase of new confirmed cases has been consistent during this time period for all provinces, with some demonstrating a sharp increase, in part due to the surge in national diagnostic capacity. This information delivers a ready resource that can be used for prediction modelling, and is utilized continuously by the current Indonesian Task Force in order to advise on potential implementation or removal of public distancing measures, and on potential availability of healthcare capacity in their efforts to ultimately manage the outbreak.

Knowledge, Attitudes, and Behaviors on Utilizing Mobile Health Technology for TB in Indonesia: A Qualitative Pilot Study.

Tuberculosis (TB) infections remain a global health burden with a high incidence rate in South-East Asia, including Indonesia. TB control strategy is founded on early case detection and complete treatment to minimize transmission and prevent the emergence of drug resistance. However, many patients face challenges to comply with daily medication, causing many to adhere inconsistently or stop prematurely. Technological solutions could enhance adherence to treatment and support national screening and follow-up policies. These include telephone video communication, enabling health professionals to watch patients take their medication, address patients' concerns, and provide advice and support. This manuscript describes the outcome of a qualitative pilot study, based on a series of focus group discussions to assess the knowledge, attitudes, and behaviors, on the potential utilization of mobile technology for health purposes with a particular focus on TB treatment follow-up. The findings illustrate that general knowledge of mobile health technologies, of their legal framework of operations, and of their exact potential within the healthcare system is incomplete or poor. The novel findings are as follows: (a) the willingness of participants to learn about these technologies, (b) the open and welcoming attitude toward receiving such information even within frontline community settings, and (c) the willingness to back a government-supported, healthcare-driven set of such initiatives. Potential implementation barriers have also been highlighted. This study is an important first step toward understanding the attitudes and behaviors on utilizing mobile health technology for TB in Indonesia.

Geographic and socioeconomic disparity in cardiovascular risk factors in Indonesia: analysis of the Basic Health Research 2018.

BACKGROUND: Cardiovascular diseases (CVDs) accounted for over 17 million deaths and 353 million disability-adjusted life years lost in 2016. The risk factors are also high and increasing with high blood pressure, smoking, and high body mass index contributed to up to 212 million disability-adjusted life years in 2016. To help reduce the burden, it is crucial to understand the geographic and socioeconomic disparities in CVD risk factors. METHODS: Employing both geospatial and quantitative analyses, we analyzed the disparities in the prevalence of smoking, physical inactivity, obesity, hypertension, and diabetes in Indonesia. CVD data was from Riskesdas 2018, and socioeconomic data was from the World Bank. RESULTS: Our findings show a very high prevalence of CVD risk factors with the prevalence of smoking, physical activity, obesity, hypertension ranged from 28 to 33%. Results also show the geographic disparity in CVD risk factors in all five Indonesian regions. Moreover, results show socioeconomic disparity with the prevalence of obesity, hypertension, and diabetes are higher among urban and the richest and most educated districts while that physical inactivity and smoking is higher among rural and the least educated districts. CONCLUSION: The CVD burden is high and increasing in particularly among urban areas and districts with higher income and education levels. While the government needs to continue tackling the persistent burden from maternal mortality and infectious diseases, they need to put more effort into the prevention and control of CVDs and their risk factors.

Surveillance and characterisation of influenza viruses among patients with influenza-like illness in Bali, Indonesia, July 2010-June 2014.

BACKGROUND: Although Indonesia has high fatality rate of human A/H5N1 cases, epidemiological and clinical data on influenza virus circulation among humans has been limited. Within Indonesia, Bali province is of interest due to high population densities of humans, pigs and poultry. This study aims to characterize and compare the epidemiological and clinical patterns of influenza viruses in humans through surveillance among patients with influenza-like illness (ILI) in Bali, Indonesia. METHODS: ILI patients were recruited at 21 sentinel health facilities across all nine regencies in Bali, from July 2010 to June 2014. PCR-based assays were used for detection and subtyping of influenza viruses. Demographic, behavioural and clinical data were tested for associations with influenza using chi-squared tests and logistic regression. RESULTS: Of 2077 ILI patients, 291 (14.0%) tested positive for influenza A, 152 (7.3%) for influenza B, and 16 (0.77%) for both influenza A and B. Of the influenza A isolates, the majority 61.2% were A/H3N2, followed by A/H1N1-pdm09 (80; 26.1%). Two A/H5N1 were identified. Influenza positive rates were significantly higher during wet season months (28.3%), compared with the dry season (13.8%; χ2 = 61.1; df = 1; p < 0.0001). Clinical predictors for infection varied by virus type, with measured fever (≥38 °C) more strongly associated with influenza B (AOR: 1.62; 95% CI: 1.10, 2.39). CONCLUSION: Influenza circulates year-round among humans in Bali with higher activity during the wet season. High contact rates with poultry and pigs, along with influenza virus detection that could not be subtyped through conventional assays, highlight the need for molecular studies to characterize epidemiological and evolutionary dynamics of influenza in this setting.

Identification and Distribution of Pathogens in a Major Tertiary Hospital of Indonesia.

The nosocomial persistence of multiple drug resistance organisms constitutes a global threat. Healthcare-setting acquired infections are subject to substantial selection pressure and are frequently associated with drug resistance. As part of the microbiological surveillance of the Sanglah tertiary referral hospital in the island province of Bali, the distribution of bacterial pathogen and their relative susceptibilities were recorded over a 30 months period. This is the first such detailed study benchmarking the type and sensitivity of bacterial pathogens in a major tertiary referral hospital within Indonesia and it is hoped that it will lead to similar reports in the near future, while informing local and national antimicrobial stewardship policies.

Piloting the One Health Systems Mapping and Analysis Resource Toolkit in Indonesia.

As a global network, countries are being asked to meet goals set forth in the Global Health Security Agenda (GHSA) for a workforce capable of effective and efficient prevention, detection and response to infectious disease threats. There is great need for a cross-sectoral workforce that can innovate and problem-solve. To achieve GHSA goals, countries need a way to visualize their existing system, identify opportunities for improvement, and achieve improved cross-sectoral interactions. The One Health Systems Mapping and Analysis Resource Toolkit (OH-SMART) was successfully piloted in West Sumatra, Indonesia, and was used to enhance multi-agency collaboration around infectious disease outbreaks and proved to be an adaptable, scalable process requiring minimal resources. The authors present OH-SMART as a potential tool to help countries analyze their existing health system and create relevant action steps to improve cross-sectoral collaborations.

Pandemic influenza and health system resource gaps in Bali: an analysis through a resource transmission dynamics model.

The failure to contain pandemic influenza A(H1N1) 2009 in Mexico has shifted global attention from containment to mitigation. Limited surveillance and reporting have, however, prevented detailed assessment of mitigation during the pandemic, particularly in low- and middle-income countries. To assess pandemic influenza case management capabilities in a resource-limited setting, the authors used a health system questionnaire and density-dependent, deterministic transmission model for Bali, Indonesia, determining resource gaps. The majority of health resources were focused in and around the provincial capital, Denpasar; however, gaps are found in every district for nursing staff, surgical masks, and N95 masks. A relatively low pathogenicity pandemic influenza virus would see an overall surplus for physicians, antivirals, and antimicrobials; however, a more pathogenic virus would lead to gaps in every resource except antimicrobials. Resources could be allocated more evenly across Bali. These, however, are in short supply universally and therefore redistribution would not fill resource gaps.

Recognizing true H5N1 infections in humans during confirmed outbreaks.

INTRODUCTION: The goal of this study was to evaluate whether any characteristics that are evident at presentation for urgent medical attention could be used to differentiate cases of H5N1 in the absence of viral testing. METHODOLOGY: Information about exposure to poultry, clinical signs and symptoms, treatments, and outcomes was abstracted from existing data in the global avian influenza registry (www.avianfluregistry.org) using standardized data collection tools for documented and possible cases of H5N1 infection who presented for medical attention between 2005-2011 during known H5N1 outbreaks in Azerbaijan, Indonesia, Pakistan and Turkey. RESULTS: Demography, exposure to poultry, and presenting symptoms were compared, with only the common symptoms of fever and headache presenting significantly more frequently in confirmed H5N1 cases than in possible cases. Reported exposure to  infected humans was also more common in confirmed cases. In contrast, unexplained respiratory illness, sore throat, excess sputum production, and rhinorrhea were more frequent in possible cases. Overall, oseltamivir treatment showed a survival benefit, with the greatest benefit shown in H5N1 cases who were treated within two days of symptom onset (51% reduction in case fatality). CONCLUSION: Since prompt treatment with antivirals conferred a strong survival benefit for H5N1 cases, presumptive antiviral treatment should be considered for all possible cases presenting during an outbreak of H5N1 as a potentially life-saving measure.

Human influenza A H5N1 in Indonesia: health care service-associated delays in treatment initiation.

BACKGROUND: Indonesia has had more recorded human cases of influenza A H5N1 than any other country, with one of the world's highest case fatality rates. Understanding barriers to treatment may help ensure life-saving influenza-specific treatment is provided early enough to meaningfully improve clinical outcomes. METHODS: Data for this observational study of humans infected with influenza A H5N1 were obtained primarily from Ministry of Health, Provincial and District Health Office clinical records. Data included time from symptom onset to presentation for medical care, source of medical care provided, influenza virology, time to initiation of influenza-specific treatment with antiviral drugs, and survival. RESULTS: Data on 124 human cases of virologically confirmed avian influenza were collected between September 2005 and December 2010, representing 73% of all reported Indonesia cases. The median time from health service presentation to antiviral drug initiation was 7.0 days. Time to viral testing was highly correlated with starting antiviral treatment (p < 0.0001). We found substantial variability in the time to viral testing (p = 0.04) by type of medical care provider. Antivirals were started promptly after diagnosis (median 0 days). CONCLUSIONS: Delays in the delivery of appropriate care to human cases of avian influenza H5N1 in Indonesia appear related to delays in diagnosis rather than presentation to health care settings. Either cases are not suspected of being H5N1 cases until nearly one week after presenting for medical care, or viral testing and/or antiviral treatment is not available where patients are presenting for care. Health system delays have increased since 2007.