ABSTRACT
Background: COVID-19 is a pandemic disease caused by droplet infection from SARS-CoV-2. Due to its rapid transmission and high case fatality rate, the identification of risk factors and prognostic factors is important. Obesity is a risk factor for poor outcomes in COVID-19. It is associated with chronic inflammation, disorders of the immune system. Obesity can be determined based on BMI. Chest X-Ray is supported in establishing the diagnosis and prognosis of COVID-19 patients. Assessment of the severity index of Chest X-Ray radiographs can use the Modified Chest X-Ray Scoring System of RSUP Dr. Soetomo. This study was conducted to analyze the relationship between BMI and chest radiography severity index in hospitalized COVID-19 patients at dr. Mohammad Hoesin Palembang in 2021. Methods: This research used a cross-sectional analytic observational design. Sampling was done using a consecutive sampling technique with 70 samples and obtained from the patient's medical record. The data were analyzed by univariate and bivariate (Chi-Square) using IBM SPSS Statistics 26 software. Results: Patients with BMI Overweight-Obesity had more in Moderate-Severe (18.6%) radiographic severity index scores (18.6%) than Normal-Mild (15.7%). Chi-Square bivariate analysis, BMI (p=0.033;p-value <0.05) had a significant relationship with the chest radiographic severity index with Odds Ratio 3,00, 95% CI (1,073–8,386). Conclusion: There is a significant relationship between body mass index and chest radiography severity index in COVID-19 patients. Overweight-Obesity BMI patients have a 3-fold chance of having a Moderate-Severe category of radiographic severity index compared to Underweight-Normal BMI patients.
ABSTRACT
The purpose of the research that the author wants to achieve is to find out the development of maritime-based MICE tourism during the COVID-19 pandemic in South Sulawesi. The type of research used is descriptive qualitative. The results of this study indicate that the potential in the Malino tourist area is very much both from Nature Tourism, Cultural Tourism and Artificial Tourism so that if it is developed to the maximum it will make the Malino tourist area more popular and tourists visiting can increase with the availability of adequate facilities.
ABSTRACT
Covid have confirmed as pandemic global by the World Health Organization (WHO), because spread that very fast among humans. As a result of the Covid-19 virus, many infected patients died, including from all countries on the Asian continent. Like the case that occurred in one of the Asian countries, namely India, which is one of the countries that experienced a spike in Covid-19 cases, the transmission of thevirus Covid-19 in India penetrated more than 400,000 cases in 1 day. The number is the highest daily record set by India during the Covid-19 pandemic. However, it was found that the problem of the spread of Covid-19 tends to increase, this is the country with the second largest population in the world. The total number of Covid-19 cases in the country has reached 21 million or second only to the United States. The vastness of India's territory allows the need for grouping the parts by region in India. This grouping produces the center points for the spread of Covid-19 cases. The purpose of grouping Covid-19 cases based on clusters is to find out the weight/percentage value generated from each of these clusters using the K-Means Clustering method. This method is used to map the spread of the Covid-19 virus from various regions in India based on confirmed cases, dead, recovered and active/new clusters. The benefits obtained for the government in overcoming Covid-19 cases are to create strategies to prevent the spread of Covid-19 based on information from the results of regional clustering in India The results obtained from research conducted in 38 regions in India using 4 clusters resulted in Confirmed cases (C0) 199 items, Died (C1) 779 items, Recovered (C2) 21 items, and Active/new cluster (C3) 231 items with a totalcluster of 1230items. © 2021 IEEE.