The Institute of Epidemiology, Disease Control and Research (IEDCR) conducts active, case-based national antimicrobial resistance (AMR) surveillance in Bangladesh. The Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project accessed aggregated retrospective data from non-IEDCR study sites and 9 IEDCR sites to understand the pattern and extent of AMR and to use analyzed data to guide ongoing and future national AMR surveillance in both public and private laboratories. Record-keeping practices, data completeness, quality control, and antimicrobial susceptibility test practices were investigated in all laboratories participating in case-based IEDCR surveillance and laboratory-based CAPTURA sites. All 9 IEDCR laboratories recorded detailed case-based data (n = 16 816) in electronic format for a priority subset of processed laboratory samples. In contrast, most CAPTURA sites (n = 18/33 [54.5%]) used handwritten registers to store data. The CAPTURA sites were characterized by fewer recorded variables (such as patient demographics, clinical history, and laboratory findings) with 1 020 197 individual data, less integration of patient records with the laboratory information system, and nonuniform practice of data recording; however, data were collected from all available clinical samples. The analyses conducted on AMR data collected by IEDCR and CAPTURA in Bangladesh provide current data collection status and highlight opportunities to improve ongoing data collection to strengthen current AMR surveillance system initiatives. We recommend a tailored approach to conduct AMR surveillance in high-burden, resource-limited settings.

Antimicrobial resistance (AMR) is a critical public health issue in Bangladesh, where antibiotic use is widespread but often unregulated. This nationwide cross-sectional study (2017–2020) analyzed data from 26 public and private laboratories across all divisions of the country. Standardized data on antimicrobial susceptibility testing (AST) were collected, curated, and analyzed using WHONET, QAAPT, and R software to assess resistance patterns in 232,329 bacterial isolates from various clinical specimens. Escherichia coli was the most common pathogen (32.5%), followed by Klebsiella sp. (15.5%) and Pseudomonas sp. (10.6%). Urine specimens comprised 50.3% of the tested samples, while blood and soft tissue/body fluids accounted for 12.1% and 24.8%, respectively. Patients aged 55 years and older represented the largest group (36.3%), highlighting their vulnerability to drug-resistant infections. Resistance to third-generation cephalosporins was alarmingly high in Escherichia coli (62.9% resistant to ceftriaxone), whereas carbapenem resistance remained relatively low (5.3% and 6.8% to imipenem and meropenem, respectively). Klebsiella sp. showed widespread resistance, though carbapenems remained relatively effective (imipenem resistance 20.3%, meropenem 21.7%). In contrast, Salmonella sp. remained largely sensitive to third-generation cephalosporins. However, 42% of Staphylococcus aureus isolates were methicillin-resistant (MRSA). This study underscores the urgent need for improved antibiotic stewardship, enhanced diagnostic capacity, and strengthened AMR surveillance to preserve treatment options in Bangladesh.

The analysis and visualisation of antimicrobial resistance (AMR) surveillance data is a crucial challenge, especially in high-burden, low-middle-income countries. We describe the design, development, integration, and implementation of the Quick Analysis of Antimicrobial Patterns and Trends (QAAPT) tool for AMR data analysis and visualisation. The QAAPT tool was created by the Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia project, led by the International Vaccine Institute (IVI). This open-source web-based tool/application generates statistical and visual outputs of AMR data, offers data curation options, and can be integrated with laboratory information management systems. The QAAPT tool is user-friendly and is operable by someone with limited expertise in software or programming. As a part of the project, the tool was used to analyse data from 72 laboratories across 7 Asian countries. In this study, we present the technical aspects of tool development and highlight implementation outcomes for analysing and generating visual reports from more than 2.37 million highly heterogeneous antimicrobial susceptibility test data points.

Introduction: Antimicrobial resistance (AMR) is a global public health issue, particularly in resource-limited, low- to middle-income countries like Bangladesh. In this study, we analyze and present four years of data on AMR from a tertiary care hospital in Bangladesh to inform policymakers and the wider community. Methods: In a retrospective cross-sectional study, we collected data for 4403 bacterial isolates reported between January 2017 and February 2020 at Mymensingh Medical College Hospital (MMCH), Bangladesh. All data were entered, cleaned, and analyzed using the software Stata Version-16.0, WHONET, a microbiology laboratory data management solution, and Quick Analysis of Antimicrobial Patterns and Trends (QAAPT), an AMR data visualization platform. Results: The bacteria were most commonly isolated from urine (71.66%, n = 3155), followed by pus (11.63%, n = 512), sputum (6.70%, n = 295), wound swabs (6.70%, n = 295), stool (1.91%, n = 84), endotracheal aspirate (1.20%, n = 53), and blood (0.20%, n = 9). Gram-negative bacteria predominated in all samples. Escherichia coli was the most common Gram-negative bacterium (31.30%, n = 1378), while Staphylococcus aureus was the most common Gram-positive bacterium (4.38%, n = 193). Antimicrobial susceptibility testing (AST) showed that multidrug resistance in Gram-negative bacteria such as E. coli, Klebsiella sp., and Acinetobacter sp. was common. S. aureus exhibited high resistance rates for beta-lactams, macrolides, and quinolones. In the urine samples, E. coli demonstrated high resistance to antibiotics like amoxicillin/clavulanic acid, ciprofloxacin, ceftriaxone, and cefuroxime (60–100%). Critical and high-priority pathogens as listed by the WHO constituted approximately 60% of the isolates. The AMR trends over three months showed increased resistance to amoxicillin/clavulanic acid for E. coli and to cefuroxime for Klebsiella sp. For S. aureus, the resistance to ciprofloxacin increased over three years, while the resistance to azithromycin decreased. Conclusions: There is a rise in bacterial resistance to the available antibiotics, with a significant prevalence of critical and high-priority pathogens in Bangladesh. We recommend vigilant AMR surveillance and stewardship programs to control the AMR in this country.

Objectives: The intent of this study was to evaluate and improve microbiology laboratory diagnostic capacity in selected National AMR Reference laboratories from South and Southeast Asia for AMR testing utilizing EQA and targeted follow-up support. Methods: A baseline assessment was conducted to evaluate quality management system (QMS) practices for laboratories participating in the Strengthening External Quality Assessment in Asia (EQASIA-EQA) programme for the first time. Following each EQA iteration, laboratory assessments were conducted, and underperforming laboratories received online consultations to identify root causes of deviations and implement corrective and preventive actions (CAPA). Laboratories with persistent underperformance, onsite visits and targeted training sessions were provided to support quality improvement. Results: Significant gaps were identified in the QMS of the 24 laboratories surveyed, with 38% lacking a QMS and 42% not conducting internal audits. Many laboratories lacked standard operating procedures (SOPs) for key processes, CAPA and equipment maintenance. Training and competency assessments were insufficient, with 50% of laboratories not conducting competency assessments. Additionally, 46% did not perform root cause analysis for EQA deviations, and 42% lacked a structured quality control programme. Water purity testing and equipment maintenance were also inadequate. Of the four baseline-assessed laboratories, three underperformed twice, and one underperformed three times across EQA iterations. Key deficiencies included the absence of a QMS and SOPs, as well as inadequate staff training and internal quality control. After targeted follow-up support, improvements were observed in QMS implementation, SOP development, staff training and quality control. Conclusions: Participation in EQA, combined with targeted follow-up support, enhances laboratory quality and performance. These improvements ultimately contribute to the provision of reliable data that can guide policy actions to combat AMR.

Introduction: Antimicrobial resistance (AMR) is a critical global public health issue, leading to prolonged illness, increased morbidity and mortality, and rising healthcare costs. The effectiveness of antibiotics is diminishing due to the emergence of resistant bacterial strains. This study aimed to determine the bacterial profile and AMR patterns of clinical isolates at Uttara Adhunik Medical College Hospital (UAMCH), Dhaka. Methods: A retrospective study was conducted at UAMCH from January 2017 to December 2019. A total of 32,187 clinical specimens (urine, blood, stool, wound swabs/pus, and sputum) were processed, of which 4232 yielded positive cultures. Bacterial identification followed standard bacteriological methods, and antibiotic susceptibility was assessed using the Kirby–Bauer disc diffusion method per CLSI guidelines. Data analysis was conducted using WHONET and QAAPT. Results: The highest proportion of positive cultures was from urine (47.5%), followed by blood (35.0%) and wound swabs/pus (10.1%). The most common isolates were Escherichia coli (37.2%), Salmonella typhi (25.7%), and Klebsiella sp. (11.5%). Gram-negative bacteria showed high resistance to commonly used antibiotics such as amoxicillin/clavulanic acid, cefixime, and ceftriaxone, while the resistance rates were lower for gentamicin, amikacin, and meropenem. However, Acinetobacter sp. exhibited alarming resistance to all tested antibiotics. Conclusions: This study highlights concerning resistance patterns among bacterial isolates, emphasizing the need for ongoing AMR surveillance to inform treatment strategies and improve patient care in Bangladesh.