Mental Health, Environmental, and Socioeconomic Geographic Factors of Severe Drug Addiction: Analysis of Rehabilitation Center Data in Indonesia.

Background: A growing number of recent literatures have attempted to document the factors related to drug use in different contexts, but limited studies analyzed the factors related to patient's severity level. Objective: We aimed to examine the correlates of behavioral, environmental, socioeconomic, geographic factors, and severe drug addiction. Methods: We used a sample of 6790 people who use drugs (PWUD) from rehabilitation centers during 2019 to 2020 in Indonesia. Data were obtained from Drugs Rehabilitation Information System (SIRENA) by the Indonesian National Narcotics Agency (BNN) during 2019 to 2020. SIRENA used the adapted version of WHO's Addiction Severity Index (ASI), which assesses patient's addiction severity level and relevant factors. A composite of the ASI factors is classified as "poor" or "serious" if its score is 4 or higher. The data was analyzed using logistic regression model to estimate correlations of severe drug addiction. Results: We found a high prevalence (65.08%) of our sample reported having severe drug addiction, which needed intervention and support. Poor psychiatric condition (OR = 4.02, CI: 2.97-5.44), serious work-related issue (OR = 2.10, 1.75-2.51), poor medical condition (OR = 2.01, 1.32-3.06), and serious family and social problems (OR = 2.56, 2.15-3.05) were significantly associated with severe drug addiction. Male users had higher odds of severe drug addiction (OR = 1.81, 1.55-2.20), compared to female counterparts. Patients in urban areas had higher odds of severe drug addiction (OR = 1.19, 1.1-1.3) than those in rural. Those in less developed regions (eg, Sumatera, Kalimantan, and Sulawesi) had higher odds of severe drug addiction (OR = 2.33, 1.9-2.9), compared to those in the most developed region (eg, Java and Bali). Conclusion: This evidence can help policymakers in refining the harm reduction policies in Indonesia and other countries with similar settings.

Macroeconomic impact of tobacco taxation in Indonesia.

BACKGROUND: A significant tobacco tax increase has long been advocated to reduce Indonesia's high smoking prevalence. However, implementing such a policy remains challenging due to the tobacco industry's argument that it would negatively impact the economy. OBJECTIVE: This study aims to provide a comprehensive estimate of the net impact of tobacco taxation on Indonesia's economy. METHOD: The impact of the tax hike on the economy is simulated through a change in cigarette demand and reallocation of household's budget and allocation government spending from additional tobacco tax revenue. Input-output analysis is employed to estimate the net effect of the tobacco tax rise on the total economic output, income and employment in Indonesia. FINDING: Increasing the tobacco tax would generate a net positive impact on the economy as it would increase economic output, household income and employment. The positive impact is mainly driven by government spending from additional revenue from increased tobacco taxes. Spending tax revenue using the current structure of government spending has the potential to generate the optimal economic effect. Increasing tobacco tax by 45% from the 2019 tax level would increase economic output, household income and employment by Rp84.2 trillion, Rp24.1 trillion and 400.3 thousand jobs, respectively.

Changes in Smoking Status and Behaviors After the First 10 Months of COVID-19 Pandemic in Indonesia.

INTRODUCTION: There remains inconclusive evidence on potential changes in smoking status and behaviors during the coronavirus disease 2019 (COVID-9) pandemic, especially in developing countries. AIMS AND METHODS: This study explores the direction of changes in smoking status and behaviors after 10 months of the COVID-19 pandemic in Indonesia as well as examining the association between economic shocks and changes in smoking behaviors. Primary data were gathered through a phone survey targeting productive-age mobile-phone users in Indonesia (n = 1082). Descriptive analysis was employed to determine changes in smoking status and behaviors 10 months into the pandemic, while logistic regression analysis was used to investigate how employment shocks, financial strain, COVID-19-related indicators, and demographic characteristics were associated with smoking behaviors of people who continue smoking. RESULTS: Respondents experiencing changes in smoking status were dominated by people who persistently smoked during the pandemic, while those who quit, relapsed, and started smoking, was extremely small. Nevertheless, a considerable portion of people who continue smoking adjusted their smoking behaviors: 40.3% reduced smoking intensity and 25.3% switched to lower-price cigarettes. Multivariable regression analysis revealed that, among people who continue smoking, those who experienced financial strain during the pandemic had higher odds of reducing smoking intensity, while those who switched to lower job status had higher odds of switching to cheaper cigarettes. CONCLUSIONS: The research has shown that smoking status and behaviors of people who continue smoking mostly remained unchanged after 10 months of the COVID-19 pandemic. Changes in employment and financial conditions during the pandemic were associated with modified smoking behaviors. IMPLICATIONS: This study is the first to determine the direction and analyze the factors of changes in smoking during the COVID-19 pandemic in Indonesia. This new understanding should help improve predicting the trends in smoking in future crises or pandemics in developing countries, specifically Indonesia. The discovered patterns on smokers' reaction to an exogenous shock may provide evidence to support tobacco control policies in Indonesia.

The role of behavioural immune system and belief in COVID-19 misinformation on COVID-19 protective behaviours in Indonesia.

This study (N = 1306) investigated the role behavioural immune system and specific beliefs in COVID-19 misinformation in predicting COVID-19 protective behaviours. By analysing the data from an online survey, we found that germ avoidance significantly predicted social distancing and was negatively correlated to transportation use. Belief in conspiracy theories and non-psychological cures and prevention methods were negatively associated to social distancing, while the latter also predicted lower preventive commodities purchasing. These findings suggested that germ aversion should be incorporated in the promotion of COVID-19 prevention behaviours and that any misinformation related to COVID-19 should be minimized to improve people's protective behaviours.

Seroprevalence of antibodies against SARS-Cov-2 in the high impacted sub-district in Jakarta, Indonesia.

BACKGROUND: Understanding the actual prevalence of COVID-19 transmission in the community is vital for strategic responses to the pandemic. This study aims to estimate the actual infection of COVID-19 through a seroprevalence survey and to predict infection fatality rate (IFR) in Tanjung Priok, the hardest-hit sub-district by the COVID-19 in Jakarta, Indonesia. METHODS: We conducted a venous blood sampling (phlebotomy) to 3,196 individuals in Tanjung Priok between Nov 23, 2020, and Feb 19, 2021 to detect their antibodies against SARS-CoV-2. Using an enumerator-administered questionnaire, we collected data on the respondents' demographic characteristics, COVID-19 test history, COVID-19 symptoms in the last 14 days, comorbidities, and protective behaviours during the last month. We employed descriptive analysis to estimate the seroprevalence and IFR. FINDINGS: The prevalence of Antibody against SARS-CoV-2 was 28.52% (95% CI 25.44-31.81%), with the result being higher in females than males (OR 1.20; 95% CI 1.02-1.42). By the end of the data collection (February 9, 2021), the cumulative cases of COVID-19 in Tanjung Priok were reported to be experienced by 9,861 people (2.4%). Those aged 45-65 were more likely to be seropositive than 15-19 years old (OR 1.42; 95% CI 1.05-1.92). Nearly one third (31%) of the subjects who developed at least one COVID-19 symptom in the last 14 days of the data collection were seropositive. The estimated IFR was 0.08% (95% CI 0.07-0.09), with a higher figure recorded in males (0.09; 95% CI 0.08-0.10) than females (0.07; 95% CI 0.06-0.08), and oldest age group (45-65) (0.21; 95% CI 0.18-0.23) than other younger groups. CONCLUSION: An under-reporting issue was found between the estimated COVID-19 seroprevalence and the reported cumulative cases in Tanjung Priok. More efforts are required to amplify epidemiological surveillance by the provincial and local governments.

Socioeconomic and Behavioral Correlates of COVID-19 Infections among Hospital Workers in the Greater Jakarta Area, Indonesia: A Cross-Sectional Study.

(1) Background: because of close contacts with COVID-19 patients, hospital workers are among the highest risk groups for infection. This study examined the socioeconomic and behavioral correlates of COVID-19 infection among hospital workers in Indonesia, the country hardest-hit by the disease in the Southeast Asia region. (2) Methods: we conducted a cross-sectional study, which collected data from 1397 hospital staff from eight hospitals in the Greater Jakarta area during April-July 2020. The data was collected using an online self-administered questionnaire and Reverse Transcription-Polymerase Chain Reaction (RT-PCR) tests. We employed descriptive statistics and adjusted and unadjusted logistic regressions to analyze the data of hospital workers as well as the subgroups of healthcare and non-healthcare workers. (3) Results: from a total of 1397 hospital staff in the study, 22 (1.6%) were infected. In terms of correlates, being a healthcare worker (adjusted odds ratio (AOR) = 8.31, 95% CI 1.27-54.54) and having a household size of more than five (AOR = 4.09, 1.02-16.43) were significantly associated with a higher risk of infection. On the other hand, those with middle- and upper-expenditure levels were shown to have a lower risk of infection (AOR = 0.06, 0.01-0.66). Behavioral factors associated with COVID-19 infection among healthcare and non-healthcare workers included knowledge of standard personal protective equipment (PPE) (AOR = 0.08, 0.01-0.54) and application of the six-step handwashing technique (AOR = 0.32, 0.12-0.83). (4) Conclusion: among hospital staff, correlates of COVID-19 infection included being a healthcare worker, household size, expenditure level, knowledge and use of PPE, and application of appropriate hand washing techniques.