The state of diabetes care and obstacles to better care in Aceh, Indonesia: a mixed-methods study.

BACKGROUND: Cardio-metabolic diseases are a major cause of death worldwide, including in Indonesia, where diabetes is one of the most critical diseases for the health system to manage. METHODS: We describe the characteristics, levels of control, health behavior, and diabetes-related complications of diabetes patients in Aceh, Indonesia. We use baseline data and blood testing from a randomized-controlled trial. We conducted semi-structured interviews with eight health providers from Posbindu and Prolanis programs that target diabetes and other non-communicable diseases (NCDs). We also conducted three focus group discussions with 24 diabetes patients about their experiences of living with diabetes and the existing support programs. RESULTS: The blood tests revealed average HbA1c levels indicative of poor glycemic control in 75.8 percent of patients and only 20.3 percent were free from any symptoms. Our qualitative findings suggest that patients are diagnosed after diabetes-related symptoms manifest, and that they find it hard to comply with treatment recommendations and lifestyle advice. The existing programs related to NCDs are not tailored to their needs. CONCLUSION: We identify the need to improve diabetes screening to enable earlier treatment and achieve better control of the disease. Among diagnosed patients, there are widespread beliefs about diabetes medication and alternative forms of treatment that need to be addressed in a respectful dialogue between healthcare professionals and patients. Current diabetes screening, treatment and management programs should be revised to meet the needs of the affected population and to better respond to the increasing burden of this disease.

Optimal control on a mathematical model to pattern the progression of coronavirus disease 2019 (COVID-19) in Indonesia.

Background: Understanding the pattern of COVID-19 infection progression is critical for health policymakers. Reaching the exponential peak of cases, flattening the curve, and treating all of the active cases are the keys to success in reducing outbreak transmission. The objective of this study was to determine the most effective model for predicting the peak of COVID-19 in Indonesia, using a deterministic model. Methods: The SEI2RS model considers five strategies for control, namely: large-scale social restriction ( u1 ), contact tracing ( u2 ), mass testing ( u3 ) , case detection and treatment ( u4 ), and the wearing of face masks ( u5 ). Three scenarios were developed, each differentiated by the controls. The model used April 10, 2020, and December 31, 2020, as the initial and final times. Results: The simulation results indicated that the peak of COVID-19 cases for scenarios 1, 2, and 3 occur on the 59th day with 33,151 cases, on the 38th day with 37,908 cases, and on the 40th day with 39,305 cases. For all of the scenarios, the decline phase shows a slow downward slope and about 8000 cases of COVID-19 still active by the end of 2020. Conclusion: The study concludes that scenario 2, which consists of large-scale social restriction (u1), contact tracing (u2), case detection and treatment (u4), and the wearing of face masks (u5), is the most rational scenario to control COVID-19 spreading in Indonesia.