Workflow for Identification of Burkholderia pseudomallei Clinical Isolates in Myanmar.

Burkholderia pseudomallei, the highly infectious and causative organism of melioidosis, was first identified in Myanmar in 1911. B. pseudomallei was identified in Myanmar because of its genetic relatedness to Burkholderia species. In this study, we identified two isolates of Burkholderia cenocepacia, two Acinetobacter baumannii complexes, and 18 clinical isolates of B. pseudomallei using Vitek 2. These isolates were first screened using a latex agglutination test, which showed positive results in 20 of the 22 isolates. All isolates were cultured on Ashdown՚s agar and further tested using molecular methods. Specific PCR for type III secretion system (TTSs) gene clusters indicated 19 B. pseudomallei isolates out of 22 isolates. Furthermore, 16S rRNA and recA gene sequencing were used as the gold standard methods and yielded the same results. RapID NF Plus detected 16 B. pseudomallei out of 22 isolates. Vitek 2 and RapID NF Plus should be considered key tools in the diagnosis of melioidosis and surveillance of B. pseudomallei in Myanmar; however, accurate identification must be confirmed by TTS1 PCR. This study evaluated the presumptive workflow for the investigation of B. pseudomallei infections using different methods and options, in line with the available equipment.

Genomic Tracking of SARS-CoV-2 Variants in Myanmar.

In December 2019, the COVID-19 disease started in Wuhan, China. The WHO declared a pandemic on 12 March 2020, and the disease started in Myanmar on 23 March 2020. In December 2020, different variants were brought worldwide, threatening global health. To counter those threats, Myanmar started the COVID-19 variant surveillance program in late 2020. Whole genome sequencing was done six times between January 2021 and March 2022. Among them, 83 samples with a PCR threshold cycle of less than 25 were chosen. Then, we used MiSeq FGx for sequencing and Illumina DRAGEN COVIDSeq pipeline, command line interface, GISAID, and MEGA version 7 for data analysis. In January 2021, no variant was detected. The second run, during the rise of cases in June 2021, showed Alpha, Delta, and Kappa variants. The third and the fourth runs in August and December showed only a Delta variant. Omicron and Delta variants were detected during the fifth run in January 2022. The sixth run in March 2022 showed only Omicron BA.2. Amino acid mutation at the receptor binding domain of Spike glycoprotein started since the second run coupling with high transmission, recurrence, and vaccine escape. We also found the mutation at the primer targets used in current RT-PCR platforms, but there was no mutation at the existing antiviral drug targets. The occurrence of multiple variants and mutations claimed vigilance at ports of entry and preparedness for effective control measures. Genomic surveillance with the observation of evolutionary data is required to predict imminent threats of the current disease and diagnose emerging infectious diseases.

Assessment of depressive symptoms in patients with COVID-19 during the second wave of epidemic in Myanmar: A cross-sectional single-center study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic has had a great impact on every aspect of society. All countries launched preventive measures such as quarantine, lockdown, and physical distancing to control the disease spread. These restrictions might effect on daily life and mental health. This study aimed to assess the prevalence and associated factors of depressive symptoms in patients with COVID-19 at the Treatment Center. METHODS: A cross-sectional telephone survey was carried out at Hmawbi COVID-19 Treatment Center, Myanmar from December 2020 to January 2021. A total of 142 patients with COVID-19 who met the criteria were invited to participate in the study. A pre-tested Center for Epidemiologic Studies Depression Scale (CES-D) was used as a tool for depressive symptoms assessment. Data were analyzed by using binary logistic regression to identify associated factors of depressive symptoms. Adjusted odds ratio (AOR) with a 95% confidence interval (CI) was computed to determine the level of significance with a p < 0.05. RESULTS: The prevalence of depressive symptoms in patients with COVID-19 was 38.7%, with the means (± standard deviation, SD) subscale of somatic symptom, negative effect, and anhedonia were 4.64 (±2.53), 2.51 (± 2.12), and 5.01 (± 3.26), respectively. The patients with 40 years and older (AOR: 2.99, 95% CI: 1.36-6.59), < 4 of household size (AOR: 3.45, 95% CI: 1.46-8.15), ≤ 400,000 kyats of monthly family income (AOR: 2.38, 95% CI: 1.02-5.54) and infection to family members (AOR: 4.18, 95% CI: 1.74-10.07) were significant associated factors of depressive symptoms. CONCLUSION: The high prevalence of depressive symptoms, approximately 40%, was found in patients with COVID-19 in the Treatment Center. Establishments of psychosocial supports, providing psychoeducation, enhancing the social contact with family and friends, and using credible source of information related COVID-19 would be integral parts of mental health services in COVID-19 pandemic situation.

Delay in treatment initiation and treatment outcomes among adult patients with multidrug-resistant tuberculosis at Yangon Regional Tuberculosis Centre, Myanmar: A retrospective study.

BACKGROUND: Myanmar faces a health security threat, with an increasing number of multidrug-resistant tuberculosis (MDR-TB) cases. Long delays in the initiation of treatment are a barrier to MDR-TB control. OBJECTIVES: The main objectives of this study were (1) to identify the determinants of delay in treatment initiation after MDR-TB diagnosis, and (2) to explore the effects of treatment delay on disease infectivity, severity, treatment adherence, and treatment outcomes. METHODS: This retrospective study reviewed 330 MDR-TB treatment cards for patients enrolled for treatment at Yangon Regional Tuberculosis Centre, in 2014. RESULTS: Median treatment delay was 105 days, interquartile range (IQR) 106 (61-167) days; (51.5%) of patients experienced a long treatment delay (≥ 105 days). Regarding the determinants of treatment delay, this study identified important patient-healthcare system interaction factors. Significant risk factors of long treatment delay included female sex, age > 30 years, and prior contact with patients with MDR-TB. Patients with long treatment delays were significantly different from those with short delays, in terms of having high sputum smear grade, resistance to more than two main drugs (isoniazid and rifampicin), and long culture conversion time. In this study, delay in the initiation of treatment was associated with poor treatment outcome, but this was not statistically significant after adjusting for other risk factors. Median treatment-delay times were longer among patients with poor outcomes (144 days) than those with successful outcomes (102 days). CONCLUSIONS: Post-diagnosis delays in the initiation of treatment among MDR-TB patients were significantly long. The study results showed that inadequate MDR-TB treatment initiation center, centralization of treatment initiation, limitation of human resources, were health-system factors delaying timely treatment initiation and implementation of an effective TB-control program. Our findings highlight the need for immediate interventions to reduce treatment delay and improve treatment outcomes, including scaling up diagnostic capacity with Xpert MTB/RIF at township level, expansion of decentralized MDR-TB treatment initiation centers, ensuring a productive health workforce comprising trained health personnel, and providing health education and treatment-adherence counseling to patients and family members.