Factors Associated with Death in COVID-19 Patients in Jakarta, Indonesia: An Epidemiological Study.

BACKGROUND: Coronavirus Disease 2019 is an emerging respiratory disease that is now a pandemic. Indonesia is experiencing a rapid surge of cases but the local data are scarce. METHODS: this is an analysis using data from the ongoing recapitulation of Epidemiological Surveillance (ES) by the Provincial Health Office of Jakarta from March 2nd to April 27th 2020. We evaluated demographic and clinical characteristics of all confirmed cases in association with death. RESULTS: of the 4,052 patients, 381 (9.4%) patients were deceased. Multivariable analysis showed that death was associated with older age (odds ratio [OR] 1.03; 95% confidence interval [CI] 1.02, 1.05, per year increase; p<0.001), dyspnea (OR 4.83; 95% CI 3.20, 7.29; p<0.001), pneumonia (OR 2.46; 95%CI 1.56, 3.88; p<0.001), and pre-existing hypertension (OR 1.86; 95% CI 1.24, 2.78; p=0.003). Death was highest in the week of April 6th 2020 and declined in the subsequent weeks, after a large-scale social restriction commenced. CONCLUSION: older age, dyspnea, pneumonia, and pre-existing hypertension were associated with death. Mortality was high, but may be reduced by lockdown.

The impact of government pandemic policies on the vulnerability of healthcare workers to SARS-CoV-2 infection and mortality in Jakarta Province, Indonesia.

INTRODUCTION: Healthcare workers (HCWs) are on the frontlines of the COVID-19 pandemic, putting them at a higher risk of infection and disease than non-HCWs. We analysed the effects of government policies for the public and for HCWs on the likelihood of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and mortality among HCWs during the first 8 months of the pandemic in Jakarta province, the capital city and COVID-19 hotspot in Indonesia. METHODS: We conducted a retrospective cohort study using secondary data from the Jakarta provincial government from March to October 2020, which included sociodemographic characteristics, symptoms, comorbidities and COVID-19 diagnosis history for all cases. A generalized linear mixed-effect regression model was used to determine the effect of each month on the odds ratio (OR) of COVID-19 cases and deaths for HCW compared with non-HCW, assuming that monthly trends were influenced by varying government policies. RESULTS: A total of 894,487 suspected and confirmed COVID-19 cases in health facilities in Jakarta province were analysed. The OR of confirmed cases for HCW was 2.04 (95% CI 2.00-2.08; p < .001) compared to non-HCW. Despite this higher OR for infection, the case fatality rate (2.32 per 100) and OR (1.02, 95% CI 0.93-1.11; p = .65) of COVID-19 deaths for HCW were similar to those of non-HCW. We observed a trend towards a lower number of COVID-19 patients in hospitals and lower odds of COVID-19 cases among HCWs during the April-to-July 2020 phase compared to the August-to-October phase. This chronologically aligned with more extensive policies to support hospital-based, community-based and well-being-related actions to protect HCW. CONCLUSIONS: HCW had higher odds of having SARS-CoV-2 infection, yet similar odds of death from COVID-19, as compared to non-HCW. Government policies with collective efforts to prevent hospital overcapacity during high transmission and burden periods of the pandemic should be prioritized.

Healthcare workers (HCWs) had higher exposure and odds of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection than non-HCWs but a similar risk of death, consistent with previous studies.Government policies favouring reduced workloads of HCW and interventions to promote resilience can be achieved through combined hospital-based, community-based and well-being-related approaches.Studies to identify the patterns and trends of COVID-19 cases and deaths, hospital admissions and policy dynamics are important to promote evidence-based decision-making by the government.

Dental Implant Osseointegration Inhibition by Nicotine through Increasing nAChR, NFATc1 Expression, Osteoclast Numbers, and Decreasing Osteoblast Numbers.

OBJECTIVE: The success of dental implants is determined by the osteointegration process. Many studies state that smoking cigarettes can inhibit osseointegration, but the inhibition mechanism is still unclear.The aim of this study was to identify and analyze the effect of nicotine on the inhibition of dental implant osseointegration through the expression of nicotinic acetylcholine receptor (nAChR), nuclear factor of activated T cells cytoplasmic 1 (NFATc1), osteoclast, and osteoblast numbers. MATERIALS AND METHODS: This study is an experimental study of 16 New Zealand rabbits, randomized across two groups. Group 1 (eight rabbits) was a control group, and group 2 (eight rabbits) was a treatment group. The treatment group was given 2.5 mg/kg body weight/day of nicotine by injection 1 week before placement of the implant until the end of research. Observations were made in the first and the eighth week by measuring the number of osteoblast and osteoclast by immunohistology test and the expression of nAChR and NFATc1 by immunohistochemistry test. STATISTICAL ANALYSIS: Data was analyzed using a one-way analysis of variance and Student's t-test. A p-value of < 0.05 was considered statistically significant. RESULTS: Significant differences were found between the control and treatment groups (p < 0.05). Results showed that nicotine increases the expression of nAChR and decreases the number of osteoblasts and the expression of BMP2 and osteocalcin. CONCLUSION: Nicotine inhibits the osseointegration of dental implants by increasing nAChR, NFATc1, osteoclast numbers, and decreasing osteoblast numbers.

Fungicide Activity of Culture Extract from Kocuria palustris 19C38A1 against Fusarium oxysporum.

Secondary metabolites of actinomycetes are a potential source of bioactive compounds in the agricultural sector. This study aimed to determine the fungicidal properties of extracts of marine organism-derived actinomycetes. Actinomycetes were isolated from marine organisms using agar media with 1% colloidal chitin in artificial seawater. Then, the isolates were cultured on liquid media with 1% colloidal chitin in artificial seawater under static conditions for 14 days. The culture was extracted, the fungicide properties were evaluated using the microtiter 96-well plate method, and the influence of inhibition was visualized using apotome and SEM. Finally, the active extract was analyzed using LCMSMS. In the present study, 19 actinomycetes were isolated from marine organisms, and the isolates were examined with regard to their antifungal activities. Of these nineteen isolates, the isolate 19C38A1 was picked out from the rest. Hence, it showed significant control towards F. oxysporum. The prospective strain 19C38A1 was determined to be Kocuria palustris 19C38A1. The extract 19C38A1 was shown to cause damage to cell integrity, indicated by the shrinking form, and inhibited germination in the F. oxysporum; subsequently, the chemical characteristics of the compound produced by the potential isolate 19C38A1 indicated the presence of benzimidazole compounds in the active fraction of C38BK2FA. These results indicate that actinomycetes derived from marine organisms near the coast of Oluhuta, Tomini Bay, Gorontalo, related to strain 19C38A1, are not widely known as sources of valuable fungicides. This preliminary information is important, as it can be used as a basis for further development in the search for fungicides derived from marine actinomycetes.

Pandemic inequity in a megacity: a multilevel analysis of individual, community and healthcare vulnerability risks for COVID-19 mortality in Jakarta, Indonesia.

INTRODUCTION: Worldwide, the 33 recognised megacities comprise approximately 7% of the global population, yet account for 20% COVID-19 deaths. The specific inequities and other factors within megacities that affect vulnerability to COVID-19 mortality remain poorly defined. We assessed individual, community-level and healthcare factors associated with COVID-19-related mortality in a megacity of Jakarta, Indonesia, during two epidemic waves spanning 2 March 2020 to 31 August 2021. METHODS: This retrospective cohort included residents of Jakarta, Indonesia, with PCR-confirmed COVID-19. We extracted demographic, clinical, outcome (recovered or died), vaccine coverage data and disease prevalence from Jakarta Health Office surveillance records, and collected subdistrict level sociodemographics data from various official sources. We used multilevel logistic regression to examine individual, community and subdistrict-level healthcare factors and their associations with COVID-19 mortality. RESULTS: Of 705 503 cases with a definitive outcome by 31 August 2021, 694 706 (98.5%) recovered and 10 797 (1.5%) died. The median age was 36 years (IQR 24-50), 13.2% (93 459) were <18 years and 51.6% were female. The subdistrict level accounted for 1.5% of variance in mortality (p<0.0001). Mortality ranged from 0.9 to 1.8% by subdistrict. Individual-level factors associated with death were older age, male sex, comorbidities and age <5 years during the first wave (adjusted OR (aOR)) 1.56, 95% CI 1.04 to 2.35; reference: age 20-29 years). Community-level factors associated with death were poverty (aOR for the poorer quarter 1.35, 95% CI 1.17 to 1.55; reference: wealthiest quarter) and high population density (aOR for the highest density 1.34, 95% CI 1.14 to 2.58; reference: the lowest). Healthcare factor associated with death was low vaccine coverage (aOR for the lowest coverage 1.25, 95% CI 1.13 to 1.38; reference: the highest). CONCLUSION: In addition to individual risk factors, living in areas with high poverty and density, and low healthcare performance further increase the vulnerability of communities to COVID-19-associated death in urban low-resource settings.

Geographical heterogeneity and socio-ecological risk profiles of dengue in Jakarta, Indonesia.

The aim of this study was to assess the role of climate variability on the incidence of dengue fever (DF), an endemic arboviral infection existing in Jakarta, Indonesia. The work carried out included analysis of the spatial distribution of confirmed DF cases from January 2007 to December 2018 characterising the sociodemographical and ecological factors in DF high-risk areas. Spearman's rank correlation was used to examine the relationship between DF incidence and climatic factors. Spatial clustering and hotspots of DF were examined using global Moran's I statistic and the local indicator for spatial association analysis. Classification and regression tree (CART) analysis was performed to compare and identify demographical and socio-ecological characteristics of the identified hotspots and low-risk clusters. The seasonality of DF incidence was correlated with precipitation (r=0.254, P<0.01), humidity (r=0.340, P<0.01), dipole mode index (r= -0.459, P<0.01) and Tmin (r= -0.181, P<0.05). DF incidence was spatially clustered at the village level (I=0.294, P<0.001) and 22 hotspots were identified with a concentration in the central and eastern parts of Jakarta. CART analysis showed that age and occupation were the most important factors explaining DF clustering. Areaspecific and population-targeted interventions are needed to improve the situation among those living in the identified DF high-risk areas in Jakarta.

The Impact of Hyperbaric Oxygen Therapy on Serum C-Reactive Protein Levels, Osteoprotegerin Expression, and Osteoclast Numbers in Induced-Periodontitis Diabetic Rats.

OBJECTIVES: This study aimed to examine the impact of hyperbaric oxygen therapy (HBOT) on serum C-reactive protein (CRP) levels, osteoclast numbers, and osteoprotegerin (OPG) expression in periodontitis-induced diabetic rats MATERIALS AND METHODS: This study constituted an in vivo laboratory-based experiment incorporating a posttest only control group design. Thirty male Wistar rats were divided into three groups of research subjects: a healthy group (K0), periodontitis-induced diabetic group (K1), and periodontitis-induced diabetic group treated with HBOT for 7 days (K2). After treatment, the subjects were sacrificed to determine the level of serum CRP by the ELISA method. Immunohistochemical analysis was conducted to check the level of OPG expression, while a histological analysis was undertaken to quantify the number of osteoclasts. STATISTICAL ANALYSIS: The data was analyzed using a one-way ANOVA and Least Significant Difference (LSD) test on which a result of p < 0.05 was considered statistically significant. RESULTS: HBOT appreciably decreased serum CRP levels, significantly enhancing OPG expression in periodontitis-induced diabetic (p < 0.05) and decreasing the number of osteoclasts in -periodontitis-induced diabetic (p > 0.05). CONCLUSION: HBOT reduced the serum CRP level, increased OPG expression, and decreased osteoclast numbers in periodontitis-induced diabetic rats.

Superspreading in early transmissions of COVID-19 in Indonesia.

This paper presents a study of early epidemiological assessment of COVID-19 transmission dynamics in Indonesia. The aim is to quantify heterogeneity in the numbers of secondary infections. To this end, we estimate the basic reproduction number [Formula: see text] and the overdispersion parameter [Formula: see text] at two regions in Indonesia: Jakarta-Depok and Batam. The method to estimate [Formula: see text] is based on a sequential Bayesian method, while the parameter [Formula: see text] is estimated by fitting the secondary case data with a negative binomial distribution. Based on the first 1288 confirmed cases collected from both regions, we find a high degree of individual-level variation in the transmission. The basic reproduction number [Formula: see text] is estimated at 6.79 and 2.47, while the overdispersion parameter [Formula: see text] of a negative-binomial distribution is estimated at 0.06 and 0.2 for Jakarta-Depok and Batam, respectively. This suggests that superspreading events played a key role in the early stage of the outbreak, i.e., a small number of infected individuals are responsible for large numbers of COVID-19 transmission. This finding can be used to determine effective public measures, such as rapid isolation and identification, which are critical since delay of diagnosis is the most common cause of superspreading events.