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.

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.

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 health care vulnerability risks for COVID-19 mortality in Jakarta, Indonesia

BackgroundThe 33 recognized 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 health care factors associated with COVID-19-related mortality in a megacity of Jakarta, Indonesia, during two epidemic waves spanning March 2, 2020, to August 31, 2021. MethodsThis retrospective cohort included all 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 sub-district level socio-demographics data from various official sources. We used multi-level logistic regression to examine individual, community and sub-district-level health care factors and their associations with COVID-19-mortality. FindingsOf 705,503 cases with a definitive outcome by August 31, 2021, 694,706 (98{middle dot}5%) recovered and 10,797 (1{middle dot}5%) died. The median age was 36 years (IQR 24-50), 13{middle dot}2% (93,459) were <18 years, and 51{middle dot}6% were female. The sub-district level accounted for 1{middle dot}5% of variance in mortality (p<0.0001). Individual-level factors associated with death were older age, male sex, comorbidities, and, during the first wave, age <5 years (adjusted odds ratio (aOR) 1{middle dot}56, 95%CI 1{middle dot}04-2{middle dot}35; reference: age 20-29 years). Community-level factors associated with death were poverty (aOR for the poorer quarter 1{middle dot}35, 95%CI 1{middle dot}17-1{middle dot}55; reference: wealthiest quarter), high population density (aOR for the highest density 1{middle dot}34, 95%CI 1{middle dot}14-2{middle dot}58; reference: the lowest), low vaccine coverage (aOR for the lowest coverage 1{middle dot}25, 95%CI 1{middle dot}13-1{middle dot}38; reference: the highest). InterpretationIn addition to individual risk factors, living in areas with high poverty and density, and low health care performance further increase the vulnerability of communities to COVID-19-associated death in urban low-resource settings. FundingWellcome (UK) Africa Asia Programme Vietnam (106680/Z/14/Z). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed on November 22, 2021, for articles that assessed individual, community, and healthcare vulnerability factors associated with coronavirus disease 2019 (COVID-19) mortality, using the search terms ("novel coronavirus" OR "SARS-CoV-2" OR "COVID-19") AND ("death" OR "mortality" OR "deceased") AND ("community" OR "social") AND ("healthcare" OR "health system"). The 33 recognized 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. At individual-level, studies have shown COVID-19-related mortality to be associated with older age and common underlying chronic co-morbidities including hypertension, diabetes, obesity, cardiac disease, chronic kidney disease and liver disease. Only few studies from North America, and South America have reported the association between lower community-level socio-economic status and healthcare performance with increased risk of COVID-19-related death. We found no studies have been done to assess individual, community, and healthcare vulnerability factors associated with COVID-19 mortality risk, especially in lower-and middle-income countries (LMIC) where accessing quality health care services is often challenging for substantial proportions of population, due to under-resourced and fragile health systems. In Southeast Asia, by November 22, 2021, COVID-19 case fatality rate had been reported at 2{middle dot}2% (23,951/1,104,835) in Vietnam, 1{middle dot}7% (47,288/2,826,853) in Philippines, 1{middle dot}0% (20,434/2,071,009) in Thailand, 1{middle dot}2% (30,063/2,591,486) in Malaysia, 2{middle dot}4% (2,905/119,904) in Cambodia, and 0{middle dot}3% in Singapore (667/253,649). Indonesia has the highest number of COVID-19 cases and deaths in the region, reporting 3{middle dot}4% case fatality rate (143,744 /4,253,598), with the highest number of cases in the capital city of Jakarta. A preliminary analysis of the first five months of surveillance in Jakarta found that 497 of 4265 (12%) hospitalised patients had died, associated with older age, male sex; pre-existing hypertension, diabetes, or chronic kidney disease; clinical diagnosis of pneumonia; multiple (>3) symptoms; immediate intensive care unit admission, or intubation. Added value of this studyThis retrospective population-based study of the complete epidemiological surveillance data of Jakarta during the first eighteen months of the epidemic is the largest studies in LMIC to date, that comprehensively analysed the individual, community, and healthcare vulnerability associated with COVID-19-related mortality among individuals diagnosed with PCR-confirmed COVID-19. The overall case fatality rate among general population in Jakarta was 1{middle dot}5% (10,797/705,503). Individual factors associated with risk of death were older age, male sex, comorbidities, and, during the first wave, age <5 years (adjusted odds ratio (aOR) 1{middle dot}56, 95%CI 1{middle dot}04-2{middle dot}35; reference: age 20-29 years). The risk of death was further increased for people living in sub-districts with high rates of poverty (aOR for the poorer quarter 1{middle dot}35, 95%CI 1{middle dot}17-1{middle dot}55; reference: wealthiest quarter), high population density (aOR for the highest density 1{middle dot}34, 95%CI 1{middle dot}14-2{middle dot}58), and low COVID-19 vaccination coverage (aOR for the lowest coverage 1{middle dot}25, 95%CI 1{middle dot}13-1{middle dot}38; reference: the highest). Implications of all available evidenceDifferences in socio-demographics and access to quality health services, among other factors, greatly influence COVID-19 mortality in low-resource settings. This study affirmed that in addition to well-known individual risk factors, community-level socio-demographics and healthcare factors further increase the vulnerability of communities to die from COVID-19 in urban low-resource settings. These results highlight the need for accelerated vaccine rollout and additional preventive interventions to protect the urban poor who are most vulnerable to dying from COVID-19.

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.

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.

Excess mortality during the first ten months of COVID-19 epidemic at Jakarta, Indonesia

Excess mortality during the COVID-19 epidemic is an important measure of health impacts. We examined mortality records from January 2015 to October 2020 from government sources at Jakarta, Indonesia: 1) burials in public cemeteries; 2) civil death registration; and 3) health authority death registration. During 2015-2019, an average of 26,342 burials occurred each year from January to October. During the same period of 2020, there were 42,460 burials, an excess of 61%. Burial activities began surging in early January 2020, two months before the first official laboratory confirmation of SARS-CoV-2 infection in Indonesia in March 2020. Analysis of civil death registrations or health authority death registration showed insensitive trends during 2020. Burial records indicated substantially increased mortality associated with the onset of and ongoing COVID-19 epidemic in Jakarta and suggest that SARS-CoV-2 transmission may have been initiated and progressing at least two months prior to official detection. Article summary lineAnalysis of civil records of burials in Jakarta, Indonesia showed a 61% increase during 2020 compared to the previous five years, a trend that began two months prior to first official confirmation of SARS-CoV-2 transmission in the city.

Clinical characteristics and mortality associated with COVID-19 in Jakarta, Indonesia: a hospital-based retrospective cohort study

BackgroundData on COVID-19-related mortality and associated factors from low-resource settings are scarce. This study examined clinical characteristics and factors associated with in-hospital mortality of COVID-19 patients in Jakarta, Indonesia, from March 2 to July 31, 2020. MethodsThis retrospective cohort included all hospitalised patients with PCR-confirmed COVID-19 in 55 hospitals. We extracted demographic and clinical data, including hospital outcomes (discharge or death). We used Cox regression to examine factors associated with mortality. FindingsOf 4265 patients with a definitive outcome by July 31, 3768 (88%) were discharged and 497 (12%) died. The median age was 46 years (IQR 32-57), 5% were children, and 31% had at least one comorbidity. Age-specific mortalities were 11% (7/61) for <5 years; 4% (1/23) for 5-9; 2% (3/133) for 10-19; 2% (8/638) for 20-29; 3% (26/755) for 30-39; 7% (61/819) for 40-49; 17% (155/941) for 50-59; 22% (132/611) for 60-69; and 34% (96/284) for [≥]70. Risk of death was associated with higher age; pre-existing hypertension, cardiac disease, chronic kidney disease or liver disease; clinical diagnosis of pneumonia; multiple (>3) symptoms; and shorter time from symptom onset to admission. Patients <50 years with >1 comorbidity had a nearly six-fold higher risk of death than those without (adjusted hazard ratio 5{middle dot}50, 95% CI 2{middle dot}72-11{middle dot}13; 27% vs 3% mortality). InterpretationOverall mortality was lower than reported in high-income countries, probably due to younger age distribution and fewer comorbidities. However, deaths occurred across all ages, with >10% mortality among children <5 years and adults >50 years.

Modeling COVID-19 Transmissions and Evaluation of Large Scale Social Restriction in Jakarta, Indonesia

This paper presents mathematical modeling and quantitative evaluation of Large Scale Social Restriction (LSSR) in Jakarta between 10 April and 4 June 2020. The special capital region of Jakarta is the only province among 34 provinces in Indonesia with an average Testing Positivity Rate (TPR) below 5% recommended by the World Health Organization (WHO). The transmission model is based on a discrete-time compartmental epidemiological model incorporating suspected cases. The quantitative evaluation is measured based on the estimation of the time-varying effective reproduction number ([R]t). Our results show the LSSR has been successfully suppressed the spread of COVID-19 in Jakarta, which was indicated by [R]t < 1. However, once the LSSR was relaxed, the effective reproduction number increased significantly. The model is further used for short-term forecasting to mitigate the course of the pandemic.

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.

Quantifying the dynamics of COVID-19 burden and impact of interventions in Java, Indonesia

BackgroundAs in many countries, quantifying COVID-19 spread in Indonesia remains challenging due to testing limitations. In Java, non-pharmaceutical interventions (NPIs) were implemented throughout 2020. However, as a vaccination campaign launches, cases and deaths are rising across the island. MethodsWe used modelling to explore the extent to which data on burials in Jakarta using strict COVID-19 protocols (C19P) provide additional insight into the transmissibility of the disease, epidemic trajectory, and the impact of NPIs. We assess how implementation of NPIs in early 2021 will shape the epidemic during the period of likely vaccine roll-out. ResultsC19P burial data in Jakarta suggest a death toll approximately 3.3 times higher than reported. Transmission estimates using these data suggest earlier, larger, and more sustained impact of NPIs. Measures to reduce sub-national spread, particularly during Ramadan, substantially mitigated spread to more vulnerable rural areas. Given current trajectory, daily cases and deaths are likely to increase in most regions as the vaccine is rolled-out. Transmission may peak in early 2021 in Jakarta if current levels of control are maintained. However, relaxation of control measures is likely to lead to a subsequent resurgence in the absence of an effective vaccination campaign. ConclusionSyndromic measures of mortality provide a more complete picture of COVID-19 severity upon which to base decision-making. The high potential impact of the vaccine in Java is attributable to reductions in transmission to date and dependent on these being maintained. Increases in control in the relatively short-term will likely yield large, synergistic increases in vaccine impact. Key questionsO_ST_ABSWhat is already known?C_ST_ABSO_LIIn many settings, limited SARS-CoV-2 testing makes it difficult to estimate the true trajectory and associated burden of the virus. C_LIO_LINon-pharmaceutical interventions (NPIs) are key tools to mitigate SARS-CoV-2 transmission. C_LIO_LIVaccines show promise but effectiveness depends upon prioritization strategies, roll-out and uptake. C_LI What are the new findings?O_LIThis study gives evidence of the value of syndrome-based mortality as a metric, which is less dependent upon testing capacity with which to estimate transmission trends and evaluate intervention impact. C_LIO_LINPIs implemented in Java earlier in the pandemic have substantially slowed the course of the epidemic with movement restrictions during Ramadan preventing spread to more vulnerable rural populations. C_LIO_LIPopulation-level immunity remains below proposed herd-immunity thresholds for the virus, though it is likely substantially higher in Jakarta. C_LI What do the new findings imply?O_LIGiven current levels of control, upwards trends in deaths are likely to continue in many provinces while the vaccine is scheduled to be rolled out. A key exception is Jakarta where population-level immunity may increase to a level where the epidemic begins to decline before the vaccine campaign has reached high coverage. C_LIO_LIFurther relaxation of measures would lead to more rapidly progressing epidemics, depleting the eventual incremental effectiveness of the vaccine. Maintaining adherence to control measures in Jakarta may be particularly challenging if the epidemic enters a decline phase but will remain necessary to prevent a subsequent large wave. Elsewhere, higher levels of control with NPIs are likely to yield high synergistic vaccine impact. C_LI

Superspreading in Early Transmissions of COVID-19 in Indonesia

We estimate the basic reproduction number[R] 0 and the overdispersion parameter[K] at two regions in Indonesia: Jakarta-Depok and Batam. Based on the first 1288 confirmed cases in both regions, we find a high degree of individual-level variation in the transmission. The basic reproduction number[R] 0 is estimated at 6.79 and 2.47, while the overdispersion parameter[K] 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 amounts of COVID-19 transmission.

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.