Antimicrobial Resistance Data Research Articles

The Unit Omega Distribution, Properties and Its Application

Dombi et al. introduced the omega distribution with three positive parameters and proved that its asymptotic distribution is the Weibull model. We propose the unit omega distribution with support in ( 0 , 1 ) , and obtain a linear representation for its density function. The maximum likelihood and Bayesian methods are adopted for estimating the model parameters. It is conducted Monte Carlo simulations to examine the means, biases, and square roots of the mean square errors of the maximum likelihood estimators. The importance of the new distribution is proved by means of antimicrobial resistance data.

Global antimicrobial resistance and use surveillance system (GLASS 2022): Investigating the relationship between antimicrobial resistance and antimicrobial consumption data across the participating countries.

For the first time since 2015, the World Health Organization's (WHO) global Antimicrobial Resistance and Use Surveillance (GLASS) featured both global reports for antimicrobial resistance (AMR) and antimicrobial consumption (AMC) data in its annual reports. In this study we investigated the relationship of AMR with AMC within participating countries reported in the GLASS 2022 report. Our analysis found a statistically significant correlation between beta-lactam/cephalosporin and fluoroquinolones consumption and AMR to these antimicrobials associated with bloodstream E. coli and Klebsiella pneumoniae among the participating countries (P<0.05). We observed that for every 1 unit increase in defined daily dose DDD of beta-lactam/cephalosporins and quinolone consumptions among the countries, increased the recoveries of bloodstream-associated beta-lactam/cephalosporins-resistant E. coli/Klebsiella spp. by 11-22% and quinolone-resistant E. coli/Klebsiella spp. by 31-40%. When we compared the antimicrobial consumptions between the antimicrobial ATC (Alphanumeric codes developed by WHO) groups and countries, we observed a statistically significant higher daily consumption of beta-lactam-penicillins (J01C, DDD difference range: 5.23-8.13) and cephalosporins (J01D, DDD difference range: 2.57-5.13) compared to other antimicrobial groups among the countries (adjusted for multiple comparisons using Tukey's method). Between the participating countries, we observed a statistically significant higher daily consumption of antimicrobial groups in Iran (DDD difference range: 3.63-4.84) and Uganda (DDD difference range: 3.79-5.01) compared to other participating countries (adjusted for multiple comparisons using Tukey's method). Understanding AMC and how it relates to AMR at the global scale is critical in the global AMR policy development and implementation of global antimicrobial stewardship.

The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2021-2022.

This report by the European Food Safety Authority and the European Centre for Disease prevention and Control, provides an overview of the main findings of the 2021-2022 harmonised Antimicrobial Resistance (AMR) monitoring in Salmonella spp., Campylobacter jejuni and C. coli from humans and food-producing animals (broilers, laying hens and fattening turkeys, fattening pigs and cattle under one year of age) and relevant meat thereof. For animals and meat thereof, AMR data on indicator commensal Escherichia coli, presumptive extended-spectrum beta-lactamases (ESBL)-/AmpC beta-lactamases (AmpC)-/carbapenemase (CP)-producing E. coli, and the occurrence of methicillin-resistant Staphylococcus aureus (MRSA) are also analysed. Generally, resistance levels differed greatly between reporting countries and antimicrobials. Resistance to commonly used antimicrobials was frequently found in Salmonella and Campylobacter isolates from humans and animals. In humans, increasing trends in resistance to one of two critically antimicrobials (CIA) for treatment was observed in poultry-associated Salmonella serovars and Campylobacter, in at least half of the reporting countries. Combined resistance to CIA was however observed at low levels except in some Salmonella serovars and in C. coli from humans and animals in some countries. While CP-producing Salmonella isolates were not detected in animals in 2021-2022, nor in 2021 for human cases, in 2022 five human cases of CP-producing Salmonella were reported (four harbouring bla OXA-48 or bla OXA-48-like genes). The reporting of a number of CP-producing E. coli isolates (harbouring bla OXA-48, bla OXA-181, bla NDM-5 and bla VIM-1 genes) in fattening pigs, cattle under 1 year of age, poultry and meat thereof by a limited number of MSs (5) in 2021 and 2022, requires a thorough follow-up. The temporal trend analyses in both key outcome indicators (rate of complete susceptibility and prevalence of ESBL-/AmpC-producers in E. coli) showed an encouraging progress in reducing AMR in food-producing animals in several EU MSs over the last 7 years.

Evaluation of three protocols for direct susceptibility testing for gram negative-Enterobacteriaceae from patient samples in Uganda with SMS reporting

In Uganda, the challenge of generating and timely reporting essential antimicrobial resistance (AMR) data has led to overreliance on empirical antibiotic therapy, exacerbating the AMR crisis. To address this issue, this study aimed to adapt a one-step AMR testing protocol alongside an SMS (Short Message Service) result relay system (SRRS), with the potential to reduce the turnaround time for AMR testing and result communication from 4 days or more to 1 day in Ugandan clinical microbiology laboratories. Out of the 377 samples examined, 54 isolates were obtained. Notably, E. coli (61%) and K. pneumoniae (33%) were the most frequently identified, majority testing positive for ESBL. Evaluation of three AMR testing protocols revealed varying sensitivity and specificity, with Protocol A (ChromID ESBL-based) demonstrating high sensitivity (100%) but no calculable specificity, Protocol B (ceftazidime-based) showing high sensitivity (100%) and relatively low specificity (7.1%), and Protocol C (cefotaxime-based) exhibiting high sensitivity (97.8%) but no calculable specificity. ESBL positivity strongly correlated with resistance to specific antibiotics, including cefotaxime, ampicillin, and aztreonam (100%), cefuroxime (96%), ceftriaxone (93%), and trimethoprim sulfamethoxazole (87%). The potential of integrating an SRRS underscored the crucial role this could have in enabling efficient healthcare communication in AMR management. This study underscores the substantial potential of the tested protocols for accurately detecting ESBL production in clinical samples, potentially, providing a critical foundation for predicting and reporting AMR patterns. Although considerations related to specificity warrant careful assessment before widespread clinical adoption.

Responding to the AMR threat: data and information needs of stakeholders working in regional and remote Australia.

Our qualitative analysis of interviews with remote Australian healthcare professionals found that they require reliable, local antimicrobial resistance (AMR) data reflecting the geographical diversity of the population they serve. The optimal use of AMR data must consider challenges within this setting, including high staff turnover, limited diagnostic capacity, and antibiotic shortages.

Comparative Genomic Analysis of Bacterial Data in BV-BRC: An Example Exploring Antimicrobial Resistance.

As genomic and related data continue to expand, research biologists are often hampered by the computational hurdles required to analyze their data. The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Centers (BRC) to assist researchers with their analysis of genome sequence and other omics-related data. Recently, the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD), and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs merged to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) at https://www.bv-brc.org/ . The combined BV-BRC leverages the functionality of the original resources for bacterial and viral research communities with a unified data model, enhanced web-based visualization and analysis tools, and bioinformatics services.Here we demonstrate how antimicrobial resistance data can be analyzed in the new resource.

Navigating the network: a narrative overview of AMR surveillance and data flow in the United States.

The antimicrobial resistance (AMR) surveillance landscape in the United States consists of a data flow that starts in the clinical setting and is maintained by a network of national and state public health laboratories. These organizations are well established, with robust methodologies to test and confirm antimicrobial susceptibility. Still, the bridge that guides the flow of data is often one directional and caught in a constant state of rush hour that can only be refined with improvements to infrastructure and automation in the data flow. Moreover, there is an absence of information in the literature explaining the processes clinical laboratories use to coalesce and share susceptibility test data for AMR surveillance, further complicated by variability in testing procedures. This knowledge gap limits our understanding of what is needed to improve and streamline data sharing from clinical to public health laboratories. Successful models of AMR surveillance display attributes like 2-way communication between clinical and public health laboratories, centralized databases, standardized data, and the use of electronic health records or data systems, highlighting areas of opportunity and improvement. This article explores the roles and processes of the organizations involved in AMR surveillance in the United States and identifies current knowledge gaps and opportunities to improve communication between them through standardization, communication, and modernization of data flow.

Protocol for surveillance of antimicrobial-resistant bacteria causing community-acquired urinary tract infections in low-income countries.

The spread of drug-resistant bacteria into the community is an urgent threat. In most low-middle-income countries (LMICs) settings, community-acquired infection (CAI) is empirically treated with no data to support the choice of antibiotics, hence contributing to resistance development. Continuous antimicrobial resistance (AMR) data on community-acquired pathogens are needed to draft empirical treatment guidelines, especially for areas with limited culture and susceptibility testing. Despite the importance of addressing antibiotic-resistant pathogens in the community setting, protocols for the surveillance of AMR bacterial infections are lacking in most (LMICs). We present a protocol for surveillance of AMR in LMICs using urinary tract infection (UTI) as a proxy for CAI to enable users to quantify and establish the drivers of AMR bacteria causing UTI. The protocol intends to assist users in designing a sustainable surveillance program for AMR in the community involving children above two years of age and adults presenting to a primary health facility for healthcare. Implementation of the protocol requires initial preparation of the laboratories to be involved, surveillance areas, selection of priority bacteria and antimicrobials to be used, and the design of a coordinated sampling plan. Recruitment should occur continuously in selected health facilities for at least 12 months to observe seasonal trends of AMR. At least 10 mL of clean-catch mid-stream urine must be collected into 20 mL calibrated sterile screw-capped universal bottles lined with 0.2 mg boric acid and transported to the testing laboratory. Utilise the data system that generates standard reports for patient care to be shared internally and externally in the regions and the world through global platforms such as the Global Antimicrobial Resistance Surveillance System.

Standardization of an antimicrobial resistance surveillance network through data management.

The rapid spread of COVID-19 worldwide within 2 months demonstrated the vulnerability of the world's population to infectious diseases. In 2015, the Global Antimicrobial Resistance and Use Surveillance System (GLASS) was launched to combat antimicrobial resistance (AMR). However, there has been no comprehensive assessment of the decade-long global battle against AMR based on GLASS data. South Korea established Kor-GLASS (Korean-GLASS) to proactively monitor data quality and enable international collaborations. A unique feature of Kor-GLASS is the quality control center (QCC), which uses network hubs and ensures standardized, high-quality data through interlaboratory proficiency testing (IPT) and external quality assessment (EQA). In addition, the QCC multifaceted endeavors for integrated data quality management. Since 2020, high-quality AMR data have indicated fluctuating antibiotic resistance rates in South Korea. This trend does not align with the decrease in antibiotic usage seen in humans but coincides with non-human antibiotic sales, indicating a need for greater monitoring of non-human antibiotic resistance. Comprehensive and robust management taking account of the intricate interplay among humans, animals, and the environment is essential. Kor-GLASS has been expanded into a "One Health" multiagency collaborative initiative. Although a standardized solution is not suitable for all countries, it must align with the local context and international standards. A centralized top-down management structure such as that of the QCC is essential to ensure continuous data quality coordination. Sustained efforts and surveillance systems are crucial for monitoring and managing AMR and safeguarding human health.

Manual for reporting 2023 antimicrobial resistance data under Directive 2003/99/EC and Commission Implementing Decision (EU) 2020/1729

Manual for reporting 2023 antimicrobial resistance data under Directive 2003/99/EC and Commission Implementing Decision (EU) 2020/1729

Assessment of Challenges Faced by Healthcare Professionals in Reporting Heath Related Data: Antimicrobial Resistance (AMR) Data Using District Health Information System Version Two (DHIS 2)

Introduction: Antimicrobial resistance poses a growing threat to public health worldwide, demanding comprehensive strategies for monitoring, surveillance, and intervention. In Rwanda, a country that has made remarkable strides in healthcare, the effective reporting of AMR data is crucial to ensure the judicious use of antibiotics, prevent the spread of resistant pathogens, and safeguard public health. Two prominent E-Health systems, DHIS 2 and Open Clinic, have been implemented in Rwanda's healthcare infrastructure, each with its unique features and capabilities. Therefore, this study seeks to evaluate the strengths and weaknesses of these systems in the context of AMR reporting within Rwanda's hospital network. Methods: The research utilized a quantitative approach and it was conducted at CHUB, a teaching hospital in Rwanda's Southern Province. Participants included clinicians, administrative staff, and decision-makers, offering a comprehensive understanding of system usage where convenience sampling over a month yielded 50 participants while on data collection a questionnaire, with structured forms for end users, administrators, and ICT personnel. Ethical considerations were strictly followed, and finally with approval from the University's Institutional Review Board, informed consent, and confidentiality measures. Results: The study involved diverse healthcare roles, with experience ranging from under a year to over ten years. All participants were familiar with DHIS 2 and Open Clinic. Most received training on both systems, and 31.3% preferred Open Clinic. DHIS 2's interface was considered user-friendly by 75% of users. DHIS 2 was more efficient in reporting time. Challenges included technical issues (22.9%), time-consuming data entry (14.6%), and data accuracy concerns (14.6%), with 41.7% facing a combination of these challenges. In conclusion, participants were proficient with both systems, but addressing technical issues, data entry, and accuracy challenges is vital for effective AMR data reporting. The choice of reporting platform and usability significantly enhances efficiency. Conclusion: This study contributes to the enhancement of AMR surveillance and reporting mechanisms in Rwanda's healthcare system, aiming to strengthen the fight against AMR and improve healthcare outcomes. The acknowledgment of authors within the references section underscores the importance of ethical research practices and transparency in academic endeavors.

Antimicrobial susceptibility in Neisseria gonorrhoeae and epidemiological data of gonorrhoea patients in five cities across Ethiopia, 2021-22.

Antimicrobial resistance (AMR) in Neisseria gonorrhoeae is a global public health concern and enhanced global gonococcal AMR surveillance is imperative. As in many African countries, regular, representative and quality-assured gonococcal AMR is lacking in Ethiopia. We describe the AMR in gonococcal isolates from five cities across Ethiopia, 2021-22, and patient epidemiological data. Urethral discharge from males and cervical discharge from females were collected from October 2021 to September 2022. Epidemiological data were collected using a questionnaire. MIC determination (ETEST; eight antimicrobials) was performed on gonococcal isolates and EUCAST breakpoints (v13.1) were used. From 1142 urogenital swab samples, 299 species-identified gonococcal isolates were identified; 78.3% were from males and 21.7% from females. The median age for males and females was 25 and 23 years, respectively. Most isolates (61.2%) were identified in Addis Ababa, followed by Gondar (11.4%), Adama (10.4%), Bahir Dar (10.0%) and Jimma (7.0%). The resistance level to ciprofloxacin, tetracycline and benzylpenicillin was 97.0%, 97.0% and 87.6%, respectively, and 87.6% of isolates were producing β-lactamase. All isolates were susceptible to ceftriaxone, cefixime, azithromycin and spectinomycin. Recommended therapy [ceftriaxone (250 mg) plus azithromycin (1 g)] was used for 84.2% of patients. We present the first national quality-assured gonococcal AMR data from Ethiopia. Resistance levels to ciprofloxacin, tetracycline and benzylpenicillin were exceedingly high. However, all isolates were susceptible to ceftriaxone, cefixime, azithromycin and spectinomycin. In Ethiopia, it is essential to strengthen the gonococcal AMR surveillance by including further epidemiological data, more isolates from different cities, and WGS.

(Invited) Magnetofluidic Platforms for Point-of-Care Detection of Infectious Diseases

Commercialized rapid POC PCR technologies are either too slow, lack antimicrobial resistance data, or are too costly for widespread adoption in resource-limited settings. This talk discusses the use of magnetofluidic platforms coupled with inexpensive disposable assay cartridges to automate, accelerate, and simplify PCR tests of infectious diseases. Instead of traditional fluidic strategies for sample handling and assay automation, magnetofluidic technologies use the movement of magnetic beads through discrete droplets of reagents to capture, purify, and transfer analytes for amplification and/or detection, eliminating the need for large, complex instrumentation and fluidics typically associated with clinical laboratory PCR tests. Miniaturized and focused thermal cycling enabled by magnetofluidic PCR significantly shortens the turnaround time of a DNA/RNA test to <15 min. We demonstrated the versatile use of portable magnetofluidic platforms for various infectious disease diagnostic applications, including POC detection of sexually transmitted infections and antimicrobial susceptibility, multiplex detection of SARS-CoV-2 and respiratory pathogens, and HIV viral load testing.

Methodological Approach to Identify and Expand the Volume of Antimicrobial Resistance (AMR) Data in the Human Health Sector in Low- and Middle-Income Countries in Asia: Implications for Local and Regional AMR Surveillance Systems Strengthening.

Antimicrobial resistance (AMR) is a multifaceted global health problem disproportionately affecting low- and middle-income countries (LMICs). The Capturing data on Antimicrobial resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project was tasked to expand the volume of AMR and antimicrobial use data in Asia. The CAPTURA project used 2 data-collection streams: facility data and project metadata. Project metadata constituted information collected to map out data sources and assess data quality, while facility data referred to the retrospective data collected from healthcare facilities. A down-selection process, labelled "the funnel approach" by the project, was adopted to use the project metadata in prioritizing and selecting laboratories for retrospective AMR data collection. Moreover, the metadata served as a guide for understanding the AMR data once they were collected. The findings from CAPTURA's metadata add to the current discourse on the limitation of AMR data in LMICs. There is generally a low volume of AMR data generated as there is a lack of microbiology laboratories with sufficient antimicrobial susceptibility testing capacity. Many laboratories in Asia are still capturing data on paper, resulting in scattered or unused data not readily accessible or shareable for analyses. There is also a lack of clinical and epidemiological data captured, impeding interpretation and in-depth understanding of the AMR data. CAPTURA's experience in Asia suggests that there is a wide spectrum of capacity and capability of microbiology laboratories within a country and region. As local AMR surveillance is a crucial instrument to inform context-specific measures to combat AMR, it is important to understand and assess current capacity-building needs while implementing activities to enhance surveillance systems.

Effective Stakeholder Engagement for Collation, Analysis and Expansion of Antimicrobial Resistance (AMR) Data: A CAPTURA Experience.

An effective implementation of antimicrobial resistance (AMR) surveillance projects requires sustainable and multidisciplinary engagement with stakeholders from various backgrounds, interests and aims. The "Capturing Data on Antimicrobial resistance Patterns and Trends in Use in Regions of Asia" (CAPTURA) project, funded by the Fleming Fund, initially targeted 12 countries in South Asia (SA) and Southeast Asia (SEA) to "expand the volume of historical and current data on AMR and antimicrobial usage" and support local agencies through capacity building activities. In this article, we focus on early stakeholder engagement activities and present overall statistics on AMR data collated from 72 laboratories across seven countries. This included 2.3 million records of antimicrobial susceptibility testing (AST) data, which were curated, analyzed, and shared back to the facilities for informed decision making. Approximately 98% of the data collated by CAPTURA originated from laboratories based in SA countries. Furthermore, country-wide data were analyzed to identify commonly reported pathogens in each country, followed by descriptions of AST practices and multidrug-resistant (MDR) pathogens. Overall, we found meager adherence to standard guidelines to perform and record AST results, and a significant number of MDR pathogens were reported. We conclude that close collaboration with the existing national mechanisms for identifying AMR data sources was crucial for the project's success. Although we show a vast retrospective dataset on AMR is available for data sharing in Asia, there remain critical gaps in data generation/management practice and analysis capacity for AMR data at most facilities.

The Reality of Antimicrobial Resistance and Antibiotic Usage Data in Asia: The CAPTURA Experience.

Antimicrobial resistance (AMR), particularly in low- and middle-income countries, is threatening to undermine advances in health and development. Scarce technical and human resources in these countries limit the collection of quality AMR data for evidence-based decision-making. The CAPTURA consortium, funded by the Fleming Fund, was implemented across 7 countries in the South and Southeast Asian region. The program focused on collating historical bacteriological data for qualitative and quantitative analyses. The team gathered standard data on the quality of laboratories and clinics and the quality and quantity of retrospective historical AMR data. In addition, retrospective data on antimicrobial use and consumption were analyzed. While standard protocols guided the project, a tailored approach for stakeholder engagement was implemented to work with countries and secure data-sharing agreements. The program also had to navigate the challenges of the COVID-19 pandemic, making some innovative adaptations to overcome logistical barriers. From 2018 through 2022, a large body of data was collected that was used to base a series of recommended key measures for strengthening the development of standardized national surveillance programs and to support alignment with international efforts.

Recording and Reporting of Antimicrobial Resistance (AMR) Priority Variables and Its Implication on Expanding Surveillance Sites in Nepal: A CAPTURA Experience.

Data on antimicrobial resistance (AMR) from sites not participating in the National AMR surveillance network, conducted by National Public Health Laboratory (NPHL), remain largely unknown in Nepal. The "Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia" (CAPTURA) assessed AMR data from previously untapped data sources in Nepal. A retrospective cross-sectional data review was carried out for the AMR data recorded between January 2017 and December 2019 to analyze AMR data from 26 hospital-based laboratories and 2 diagnostic laboratories in Nepal. Of the 56 health facilities initially contacted to participate in this project activity, 50.0% (28/56) signed a data-sharing agreement with CAPTURA. Eleven of the 28 hospitals were AMR surveillance sites, whereas the other 17, although not part of the National AMR surveillance network, recorded AMR-related data. Data for 663 602 isolates obtained from 580 038 patients were analyzed. A complete record of the 11 CAPTURA priority variables was obtained from 45.5% (5/11) of government hospitals, 63.6% (7/11) of private hospitals, and 54.6% (6/11) of public-private hospitals networked with NPHL for AMR surveillance. Similarly, 80% (8/10) of clinics and 54.6% (6/11) of laboratories outside the NPHL network recorded complete data for the 10 Global Antimicrobial Resistance and Use Surveillance System (GLASS) priority variables and 11/14 CAPTURA priority variables. Retrospective review of the data identified areas requiring additional resources and interventions to improve the quality of data on AMR in Nepal. Furthermore, we observed no difference in the priority variables reported by sites within or outside the NPHL network, thus suggesting that policies could be made to expand the surveillance system to include these sites without substantially affecting the government's budget.

Utility and Evaluation of Applied Project Management Processes Within a Large Multicountry Health Systems Development Project Conducted During the Coronavirus Disease 2019 (COVID-19) Pandemic.

The increasing trends in antimicrobial resistance (AMR) continue to pose a significant threat to human health, with grave consequences in low- and middle-income countries. In collaboration with local governments and microbiology laboratories in South Asian and Southeast Asian countries, the Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project worked to identify gaps and expand the volume of existing AMR data to inform decision-makers on how to best strengthen their national AMR surveillance capacity. This article describes overall project management processes and the strategies implemented to address the disruptive impact of the coronavirus disease 2019 (COVID-19) pandemic on the project activities across diverse contexts in different countries. Also, it assesses in-country team's feedback on the conduct of activities and their overall impact on project completion. The strategies employed were tailored to the specific context of each country and included increased communication and collaboration among consortium partners and in-country teams, as well as hiring of additional in-country team members. This paper highlights the importance of local representation and capacities as well as real-time (virtual) engagement with stakeholders, ensuring close monitoring of the local situation and ability to tailor context-specific mitigation strategies to continue project implementation during disruptive external circumstances.

Considerations for Expanding Antimicrobial Resistance Surveillance Networks.

Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) gained insight into the range of national antimicrobial resistance (AMR) stakeholders' long-term visions for AMR surveillance networks. As national AMR networks mature, stakeholders often contemplate adding laboratories to the network to achieve greater representativeness, boost data quantity, or meet other goals. Therefore, stakeholders should carefully select laboratories for expansion based on their goals and several practical criteria. Based on CAPTURA experience, the key criteria a national network may consider when expanding its AMR surveillance network include location, laboratory ownership, access to linked clinical and prescription databases, logistical ease, a laboratory's collaborative spirit, laboratory practices and equipment, laboratory staffing and quality assessments, laboratory methods and specimen types, data cleanliness and completeness, and the quantity of AMR data.

Key Recommendations for Antimicrobial Resistance Surveillance: Takeaways From the CAPTURA Project.

Antimicrobial resistance (AMR) is a growing global public health challenge associated with 4.95 million deaths in 2019 and an estimated 10 million deaths per year by 2050 in the absence of coordinated action. A robust AMR surveillance system is therefore required to avert such a scenario. Based on an analysis of country-level AMR data in 8 Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) countries, we present a list of key recommendations to strengthen AMR surveillance. We propose 10 primary considerations under 3 broad categories, including recommendations on (1) laboratory and testing practices, (2) data management and analysis, and (3) data use.