COVID-19 cases in Indonesia still remain a concern, particularly for public health. Several factors, such as gender, age, comorbidity, occupation, and vaccination status, might influence COVID-19 infection. Individuals who have many predicting factors have a higher risk of being infected by COVID-19. Other studies have not yet shown the significance of predicting factors for COVID-19 infection in Indonesia. The study explored the association between the predicting factors and COVID-19 infection in Indonesia. The study used a cross-sectional method with a population of all Indonesian communities. It was conducted in August 2021 by distributing a Google Form questionnaire in Indonesia. By a saturated sampling of the population in Jawa, Sumatera, Sulawesi, Kalimantan, and Papua, 776 Indonesians were selected; they were aged > 17 years and voluntarily completed the questionnaires. whereas respondents with incomplete data were excluded from this study. The data were analyzed using a binary logistic regression test in SPSS (version 21.0). The respondents include 134 men (17.3%) and 642 women (82.7%). The binary logistic regression analysis showed that COVID-19 infection was more common among respondents who were non-health-care workers (p  0.001) and less common among those who had been fully vaccinated (p  0.001). The COVID-19 infection was significantly associated with occupation and vaccination status.  Keywords: COVID-19 Infection, Predicting Factors, Public Health, Health-Care Worker, COVID-19 Vaccination, Comorbidity

Long-term COVID-19 could occur in COVID-19 patients, affecting the patient's quality of life, and becoming a  problem for public health. However, information is rarely on factors associated with the occurrence of long COVID-19 cases. This study analyzed factors associated with long-term COVID-19. The study was an observational cross-sectional, conducted in August 2021. The data were collected through a Google form questionnaire distributed to COVID-19 survivors in Indonesian. They must be aged more than 17 years to meet the inclusion criteria, while those with incomplete data were excluded. The data were processed by using SPSS 21 with an ordinal regression test in which an alpha level was 5%. As many as 101 from 16 men (15.8%) and 85 women (84.2%) were obtained. Comorbid status (p-value = 0.001) and duration of treatment (p-value = 0.034 and 0.015) had a significant association with the occurrence of long-term COVID-19. Meanwhile, age, gender, occupation, type of care, and vaccination status were not likely associated with long-term COVID-19. COVID-19 patients with comorbidity and a long duration of treatment are more likely to experience long-term COVID-19. Keywords: COVID-19, long-term COVID-19, factor, public health

ObjectivesAmong Chronic Myeloid Leukemia (CML) patients treated with Tyrosine Kinase Inhibitor (TKI-imatinib-nilotinib), some showed a suboptimal response. Based on pharmacokinetic studies, TKI trough level (${C}_{min}\hat{\infty }$) is associated with clinical outcomes, reflected by the BCR-ABL ratio. However, the interindividual pharmacokinetic variability of imatinib and nilotinib is found to be moderate–high. This study aims to analyze the relationship between TKI ${C}_{min}\hat{\infty }$ and BCL-ABL ratio in chronic-phase CML patients.MethodsCross-sectional study to CML chronic-phase patients treated with imatinib 400 mg daily or nilotinib 400 or 800 mg daily for ≥12 months. The exclusion criteria were therapy discontinuation within 29 days (imatinib) or 8 days (nilotinib) before the sampling day. Blood samples were drawn 1 h before the next dose. Imatinib-nilotinib ${C}_{min}\hat{\infty }$ and BCR-ABL ratio were measured using HPLC and RT-qPCR. The relationship was analyzed using bivariate correlation Spearman’s rho test.ResultsTwenty-three imatinib and 11 nilotinib patients met the inclusion criteria. The mean imatinib and nilotinib ${C}_{min}\hat{\infty }$ were 1,065.46 ± 765.71 and 1,445 ± 1,010.35 ng/mL respectively. There were large interindividual variations in both groups (71.87% vs. 69.88%). Half of the patients in each group were found to reach ${C}_{min}\hat{\infty }$ target (≥1.000 ng/mL, imatinib; ≥800 ng/mL nilotinib), but only 12 (35,29%) of them result in BCR-ABL ratio ≤0.1%. ${C}_{min}\hat{\infty }$ imatinib was found to be significantly associated with BCR-ABL ratio. But, not with the nilotinib group.ConclusionsThere were high interindividual variations of imatinib and nilotinib correlated with BCR-ABL ratio, but no correlation in nilotinib.

Abstract The Covid-19 pandemic can influence the mental condition of patients and affect their immunity levels. This article aims to investigate the mental health symptoms and disorders of Covid-19 survivors. This was observational and cross-sectional research. A total of 175 respondents participated, 84% of them being women and 16% being men. Their work history includes health workers at 75.4% and others at 24.6%. Respondents who have experienced anxiety are 32%, sadness was 25.7%, fear was 22.9%, and panic was 14.3%. The logistic regression showed that all of the tested characteristics have no significant effect on the respondents’ mental states of anxiety, fear, and panic, with p-values ​​of 0.388, 0.893, and 0.166; 0.245, 0.691, and 0.353; 0.612, 0.410, and 0.828. However, from the test results, it was observed that gender has a significant effect on sadness with a p-value of 0.027 and OR value of 5.308 (CI = 1.204-23.399). The percentage of women respondents that experienced sadness was 29.3% and men respondents were 7.1%. Other characteristics, which are age and work history, have no significant effect on sadness, with p-values ​​of 0.650 and 0.844 respectively.  There are no variables that affect anxiety, fear, and panic. Feelings of sadness in patients are influenced by gender. Keywords: anxiety; Covid-19; mental disorder; mental health

Background: Healthcare workers in Indonesia have been prioritized for vaccination. Nevertheless, fully vaccinated healthcare workers are still at risk of being infected with COVID-19, but will be less likely to develop severe symptoms, be hospitalized or be at risk for death as compared to those who have not been vaccinated. Objectives: This study aims to analyze the incidence of COVID-19 in fully vaccinated healthcare workers. Methods: This cross-sectional study was conducted in 2021. All healthcare workers who have been fully vaccinated, have recovered from COVID-19 (2-4 weeks after vaccination) and able to complete a questionnaire were the participants. The collected data was then analyzed using the cascade method. Results: Based on the 529 collected questionnaires, by using the cascade analysis conclude that the percentage of healthcare workers who have been fully vaccinated was 99%, healthcare workers who have been fully vaccinated and then infected with COVID-19 was 14%, healthcare workers who have been fully vaccinated, infected with COVID-19 and hospitalized was 4%, healthcare workers who have been fully vaccinated, exposed to COVID-19, hospitalized and experienced the long-haul effect of COVID-19 was 0%. Discussion: Health workers are still at risk of being confirmed by COVID-19, because have high risk of being exposed in the workplace. The risk of being confirmed and severity are also influenced by age, gender and comorbidities. Conclusions: Complete vaccinations of healthcare workers did not reduce their risk of being infected with COVID-19, however, it can reduce the severity and the risk of the long-haul effects.