Predominance of multidrug-resistant bacteria causing urinary tract infections among symptomatic patients in East Africa: a call for action.

Background: In low- and middle-income countries, antibiotics are often prescribed for patients with symptoms of urinary tract infections (UTIs) without microbiological confirmation. Inappropriate antibiotic use can contribute to antimicrobial resistance (AMR) and the selection of MDR bacteria. Data on antibiotic susceptibility of cultured bacteria are important in drafting empirical treatment guidelines and monitoring resistance trends, which can prevent the spread of AMR. In East Africa, antibiotic susceptibility data are sparse. To fill the gap, this study reports common microorganisms and their susceptibility patterns isolated from patients with UTI-like symptoms in Kenya, Tanzania and Uganda. Within each country, patients were recruited from three sites that were sociodemographically distinct and representative of different populations. Methods: UTI was defined by the presence of >104 cfu/mL of one or two uropathogens in mid-stream urine samples. Identification of microorganisms was done using biochemical methods. Antimicrobial susceptibility testing was performed by the Kirby-Bauer disc diffusion assay. MDR bacteria were defined as isolates resistant to at least one agent in three or more classes of antimicrobial agents. Results: Microbiologically confirmed UTI was observed in 2653 (35.0%) of the 7583 patients studied. The predominant bacteria were Escherichia coli (37.0%), Staphylococcus spp. (26.3%), Klebsiella spp. (5.8%) and Enterococcus spp. (5.5%). E. coli contributed 982 of the isolates, with an MDR proportion of 52.2%. Staphylococcus spp. contributed 697 of the isolates, with an MDR rate of 60.3%. The overall proportion of MDR bacteria (n = 1153) was 50.9%. Conclusions: MDR bacteria are common causes of UTI in patients attending healthcare centres in East African countries, which emphasizes the need for investment in laboratory culture capacity and diagnostic algorithms to improve accuracy of diagnosis that will lead to appropriate antibiotic use to prevent and control AMR.

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

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

CAPTURA Regional Workshop Proceedings (28-30 June 2022, Virtual).

In response to the global threat of antimicrobial resistance (AMR), the Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project worked with microbiology laboratories, pharmacies, and local governments in South Asia and Southeast Asia to expand the volume of historical and current data available on AMR and antimicrobial use and to identify gaps in data and areas for quality improvement. When the CAPTURA project completed its country-level engagement in the first half of 2022, the consortium brought together local, regional, and global AMR stakeholders for a virtual regional workshop to review data outputs from the project and share strategies to inform national and regional efforts to combat AMR. This paper summarizes the main topics presented in the workshop held from 28 to 30 June 2022. As such, it highlights lessons learned from the project and strategies to fight AMR. Although CAPTURA has been invaluable to countries and information from the project is already being used, barriers concerning data quality and sharing remain. Regional-level initiatives should continue to build on the momentum gained from the CAPTURA project in supporting national-level surveillance and data quality improvements to inform critical decisions around planning, policies, and clinical care. Project findings have highlighted that issues with antimicrobial resistance and use are wide ranging across countries. Going forward, building on the current foundations and tailoring approaches to meet local needs and capacities will be fundamental in combatting AMR.

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.

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.

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.

Antimicrobial Resistance Surveillance Methods in Bangladesh: Present and Way Forward.

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.

Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA).

BACKGROUND: In 2015, the UK government established the Fleming Fund with the aim to address critical gaps in surveillance of antimicrobial resistance (AMR) in low- and middle-income countries in Asia and Africa. Among a large portfolio of grants, the Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project was awarded with the specific objective of expanding the volume of historical data on AMR, consumption (AMC), and use (AMU) in the human healthcare sector across 12 countries in South and Southeast Asia. METHODS: Starting in early 2019, the CAPTURA consortium began working with local governments and >100 relevant data-holding facilities across the region to identify, assess for quality, prioritize, and subsequently retrieve data on AMR, AMC, and AMU. Relevant and shared data were collated and analyzed to provide local overviews for national stakeholders as well as regional context, wherever possible. RESULTS: From the vast information resource generated on current surveillance capacity and data availability, the project has highlighted gaps and areas for quality improvement and supported comprehensive capacity-building activities to optimize local data-collection and -management practices. CONCLUSIONS: The project has paved the way for expansion of surveillance networks to include both the academic and private sector in several countries and has actively engaged in discussions to promote data sharing at the local, national, and regional levels. This paper describes the overarching approach to, and emerging lessons from, the CAPTURA project, and how it contributes to other ongoing efforts to strengthen national AMR surveillance in the region and globally.

Laboratory Surveillance, Quality Management, and Its Role in Addressing Antimicrobial Resistance in Africa: A Narrative Review.

AMR is a major public health concern that calls for extensive work and a multidisciplinary team approach. The high prevalence of infectious diseases in African nations leads to widespread antibiotic usage and eventual antimicrobial resistance, which has significant negative effects on people's health, the economy, and society. Additionally, inadequate or nonexistent antimicrobial drug regulations, inappropriate prescription practices, and restrictions on public health prevention initiatives such as immunization, water and sanitation, and sexual health may all contribute to the emergence of AMR. Despite the need for laboratory quality assurance, many African laboratories confront substantial difficulties in implementing efficient quality assurance programs. AMR surveillance in Africa is hampered by a lack of laboratory capacity, insufficient data collection and analysis, and poor stakeholder collaboration. Several initiatives and programs, including the World Health Organization's Global Antimicrobial Resistance and Use Surveillance System (GLASS), the Africa Centres for Disease Control and Prevention (Africa CDC) Antimicrobial Resistance Surveillance Network (AMRSNET), and the Fleming Fund, a UK government initiative aimed at tackling AMR in low- and middle-income countries, have been established to strengthen AMR surveillance in Africa and globally.

Evaluation of the diagnostic performance of the urine dipstick test for the detection of urinary tract infections in patients treated in Kenyan hospitals.

Introduction: Culture is the gold-standard diagnosis for urinary tract infections (UTIs). However, most hospitals in low-resource countries lack adequately equipped laboratories and relevant expertise to perform culture and, therefore, rely heavily on dipstick tests for UTI diagnosis. Research gap: In many Kenyan hospitals, routine evaluations are rarely done to assess the accuracy of popular screening tests such as the dipstick test. As such, there is a substantial risk of misdiagnosis emanating from inaccuracy in proxy screening tests. This may result in misuse, under-use or over-use of antimicrobials. Aim: The present study aimed to assess the accuracy of the urine dipstick test as a proxy for the diagnosis of UTIs in selected Kenyan hospitals. Methods: A hospital-based cross-sectional method was used. The utility of dipstick in the diagnosis of UTIs was assessed using midstream urine against culture as the gold standard. Results: The dipstick test predicted 1416 positive UTIs, but only 1027 were confirmed positive by culture, translating to a prevalence of 54.1 %. The sensitivity of the dipstick test was better when leucocytes and nitrite tests were combined (63.1 %) than when the two tests were separate (62.6 and 50.7 %, respectively). Similarly, the two tests combined had a better positive predictive value (87.0 %) than either test alone. The nitrite test had the best specificity (89.8 %) and negative predictive value (97.4 %) than leucocytes esterase (L.E) or both tests combined. In addition, sensitivity in samples from inpatients (69.2 %) was higher than from outpatients (62.7 %). Furthermore, the dipstick test had a better sensitivity and positive predictive value among female (66.0 and 88.6 %) than male patients (44.3 and 73.9 %). Among the various patient age groups, the dipstick test's sensitivity and positive predictive value were exceptionally high in patients ≥75 years old (87.5 and 93.3 %). Conclusion: Discrepancies in prevalence from the urine dipstick test and culture, the gold standard, indicate dipstick test inadequacy for accurate UTI diagnosis. The finding also demonstrates the need for urine culture for accurate UTI diagnosis. However, considering it is not always possible to perform a culture, especially in low-resource settings, future studies are needed to combine specific UTI symptoms and dipstick results to assess possible increases in the test's sensitivity. There is also a need to develop readily available and affordable algorithms that can detect UTIs where culture is not available.

Unravelling patient pathways in the context of antibacterial resistance in East Africa.

BACKGROUND: A key factor driving the development and maintenance of antibacterial resistance (ABR) is individuals' use of antibiotics (ABs) to treat illness. To better understand motivations and context for antibiotic use we use the concept of a patient treatment-seeking pathway: a treatment journey encompassing where patients go when they are unwell, what motivates their choices, and how they obtain antibiotics. This paper investigates patterns and determinants of patient treatment-seeking pathways, and how they intersect with AB use in East Africa, a region where ABR-attributable deaths are exceptionally high. METHODS: The Holistic Approach to Unravelling Antibacterial Resistance (HATUA) Consortium collected quantitative data from 6,827 adult outpatients presenting with urinary tract infection (UTI) symptoms in Kenya, Tanzania, and Uganda between February 2019- September 2020, and conducted qualitative in-depth patient interviews with a subset (n = 116). We described patterns of treatment-seeking visually using Sankey plots and explored explanations and motivations using mixed-methods. Using Bayesian hierarchical regression modelling, we investigated the associations between socio-demographic, economic, healthcare, and attitudinal factors and three factors related to ABR: self-treatment as a first step, having a multi-step treatment pathway, and consuming ABs. RESULTS: Although most patients (86%) sought help from medical facilities in the first instance, many (56%) described multi-step, repetitive treatment-seeking pathways, which further increased the likelihood of consuming ABs. Higher socio-economic status patients were more likely to consume ABs and have multi-step pathways. Reasons for choosing providers (e.g., cost, location, time) were conditioned by wider structural factors such as hybrid healthcare systems and AB availability. CONCLUSION: There is likely to be a reinforcing cycle between complex, repetitive treatment pathways, AB consumption and ABR. A focus on individual antibiotic use as the key intervention point in this cycle ignores the contextual challenges patients face when treatment seeking, which include inadequate access to diagnostics, perceived inefficient public healthcare and ease of purchasing antibiotics without prescription. Pluralistic healthcare landscapes may promote more complex treatment seeking and therefore inappropriate AB use. We recommend further attention to healthcare system factors, focussing on medical facilities (e.g., accessible diagnostics, patient-doctor interactions, information flows), and community AB access points (e.g., drug sellers).

Bacterial etiology of urinary tract infections in patients treated at Kenyan health facilities and their resistance towards commonly used antibiotics.

BACKGROUND: Evidence-based empirical antibiotic prescribing requires knowledge of local antimicrobial resistance patterns. The spectrum of pathogens and their susceptibility strongly influences guidelines for empirical therapies for urinary tract infections (UTI) management. OBJECTIVE: This study aimed to determine the prevalence of UTI causative bacteria and their corresponding antibiotic resistance profiles in three counties of Kenya. Such data could be used to determine the optimal empirical therapy. METHODS: In this cross-sectional study, urine samples were collected from patients who presented with symptoms suggestive of UTI in the following healthcare facilities; Kenyatta National Hospital, Kiambu Hospital, Mbagathi, Makueni, Nanyuki, Centre for Microbiology Research, and Mukuru Health Centres. Urine cultures were done on Cystine Lactose Electrolyte Deficient (CLED) to isolate UTI bacterial etiologies, while antibiotic sensitivity testing was done using the Kirby-Bauer disk diffusion using CLSI guidelines and interpretive criteria. RESULTS: A total of 1,027(54%) uropathogens were isolated from the urine samples of 1898 participants. Staphylococcus spp. and Escherichia coli were the main uropathogens at 37.6% and 30.9%, respectively. The percentage resistance to commonly used drugs for the treatment of UTI were as follows: trimethoprim (64%), sulfamethoxazole (57%), nalidixic acid(57%), ciprofloxacin (27%), amoxicillin-clavulanic acid (5%), and nitrofurantoin (9%) and cefixime (9%). Resistance rates to broad-spectrum antimicrobials, such as ceftazidime, gentamicin, and ceftriaxone, were 15%, 14%, and 11%, respectively. Additionally, the proportion of Multidrug-resistant (MDR) bacteria was 66%. CONCLUSION: High resistance rates toward fluoroquinolones, sulfamethoxazole, and trimethoprim were reported. These antibiotics are commonly used drugs as they are inexpensive and readily available. Based on these findings, more robust standardised surveillance is needed to confirm the patterns observed while recognising the potential impact of sampling biases on observed resistance rates.

The role of multidimensional poverty in antibiotic misuse: a mixed-methods study of self-medication and non-adherence in Kenya, Tanzania, and Uganda.

BACKGROUND: Poverty is a proposed driver of antimicrobial resistance, influencing inappropriate antibiotic use in low-income and middle-income countries (LMICs). However, at subnational levels, studies investigating multidimensional poverty and antibiotic misuse are sparse, and the results are inconsistent. We aimed to investigate the relationship between multidimensional poverty and antibiotic use in patient populations in Kenya, Tanzania, and Uganda. METHODS: In this mixed-methods study, the Holistic Approach to Unravelling Antimicrobial Resistance (HATUA) Consortium collected data from 6827 outpatients (aged 18 years and older, or aged 14-18 years and pregnant) with urinary tract infection (UTI) symptoms in health-care facilities in Kenya, Tanzania, and Uganda. We used Bayesian hierarchical modelling to investigate the association between multidimensional poverty and self-reported antibiotic self-medication and non-adherence (ie, skipping a dose and not completing the course). We analysed linked qualitative in-depth patient interviews and unlinked focus-group discussions with community members. FINDINGS: Between Feb 10, 2019, and Sept 10, 2020, we collected data on 6827 outpatients, of whom 6345 patients had complete data; most individuals were female (5034 [79·2%]), younger than 35 years (3840 [60·5%]), worked in informal employment (2621 [41·3%]), and had primary-level education (2488 [39·2%]). Antibiotic misuse was more common among those least deprived, and lowest among those living in severe multidimensional poverty. Regardless of poverty status, difficulties in affording health care, and more familiarity with antibiotics, were related to more antibiotic misuse. Qualitative data from linked qualitative in-depth patient interviews (n=82) and unlinked focus-group discussions with community members (n=44 groups) suggested that self-medication and treatment non-adherence were driven by perceived inconvenience of the health-care system, financial barriers, and ease of unregulated antibiotic access. INTERPRETATION: We should not assume that higher deprivation drives antibiotic misuse. Structural barriers such as inefficiencies in public health care, combined with time and financial constraints, fuel alternative antibiotic access points and treatment non-adherence across all levels of deprivation. In designing interventions to reduce antibiotic misuse and address antimicrobial resistance, greater attention is required to these structural barriers that discourage optimal antibiotic use at all levels of the socioeconomic hierarchy in LMICs. FUNDING: UK National Institute for Health Research, UK Medical Research Council, and the Department of Health and Social Care.

Utilising cumulative antibiogram data to enhance antibiotic stewardship capacity in the Cape Coast Teaching Hospital, Ghana.

BACKGROUND: Antimicrobial resistance (AMR) is a major public health challenge with its impact felt disproportionately in Western Sub-Saharan Africa. Routine microbiology investigations serve as a rich source of AMR monitoring and surveillance data. Geographical variations in susceptibility patterns necessitate regional and institutional tracking of resistance patterns to aid in tailored Antimicrobial Stewardship (AMS) interventions to improve antibiotic use in such settings. This study focused on developing a cumulative antibiogram of bacterial isolates from clinical samples at the Cape Coast Teaching Hospital (CCTH). This was ultimately to improve AMS by guiding empiric therapy. METHODS: A hospital-based longitudinal study involving standard microbiological procedures was conducted from 1st January to 31st December 2020. Isolates from routine diagnostic aerobic cultures were identified by colony morphology, Gram staining, and conventional biochemical tests. Isolates were subjected to antibiotic susceptibility testing using Kirby-Bauer disc diffusion. Inhibitory zone diameters were interpreted per the Clinical and Laboratory Standards Institute guidelines and were entered and analysed on the WHONET software using the "first isolate only" principle. RESULTS: Overall, low to moderate susceptibility was observed in most pathogen-antibiotic combinations analysed in the study. Amikacin showed the highest susceptibility (86%, n = 537/626) against all Gram-negatives with ampicillin exhibiting the lowest (6%, n = 27/480). Among the Gram-positives, the highest susceptibilities were exhibited by gentamicin (78%, n = 124/159), with clindamycin having the lowest susceptibility (27%, n = 41/154). Among the Gram-negatives, 66% (n = 426/648) of the isolates were identified phenotypically as potential extended-spectrum beta-lactamase producers. Multiple multidrug-resistant isolates were also identified among both Gram-positive and Gram-negative isolates. Low to moderate susceptibility was found against first- and second-line antibiotics recommended in the National standard treatment guidelines (NSTG). Laboratory quality management deficiencies and a turnaround time of 3.4 days were the major AMS barriers identified. CONCLUSIONS: Low to moderate susceptibilities coupled with high rates of phenotypic resistance warrant tailoring NSTGs to fit local contexts within CCTH even after considering the biases in these results. The cumulative antibiogram proved a key AMS programme component after its communication to clinicians and subsequent monitoring of its influence on prescribing indicators. This should be adopted to enhance such programmes across the country.

Genomic surveillance of Salmonella spp. in the Philippines during 2013-2014.

BACKGROUND: Increasing antimicrobial resistance (AMR) in Salmonella has been observed in the Philippines. We aimed to characterise the population and AMR mechanisms of Salmonella with whole genome sequencing (WGS) and compare it with laboratory surveillance methods. METHODS: The serotype, multilocus sequence type, AMR genes and relatedness between isolates were determined from the genomes of 148 Salmonella Typhi (S. Typhi) and 65 non-typhoidal Salmonella (NTS) collected by the Antimicrobial Resistance Surveillance Program during 2013-2014. Genotypic serotypes and AMR prediction were compared with phenotypic data. RESULTS: AMR rates in S. Typhi were low, with sparse acquisition of mutations associated with reduced susceptibility to fluoroquinolones or extended-spectrum beta-lactamases (ESBL) genes. By contrast, 75% of NTS isolates were insusceptible to at least one antimicrobial, with more than half carrying mutations and/or genes linked to fluoroquinolone resistance. ESBL genes were detected in five genomes, which also carried other AMR determinants. The population of S. Typhi was dominated by likely endemic genotype 3.0, which caused a putative local outbreak. The main NTS clades were global epidemic S. Enteritidis ST11 and S. Typhimurium monophasic variant (I,4,[5],12: i: -) ST34. CONCLUSION: We provide the first genomic characterisation of Salmonella from the Philippines and evidence of WGS utility for ongoing surveillance.

What's New in Antibiograms? Updating CLSI M39 Guidance with Current Trends.

A vast amount of antimicrobial susceptibility test (AST) data is generated from routine testing in diagnostic laboratories for the primary purpose of guiding clinicians in antimicrobial therapy decisions for their patients. However, there is additional value for these data when they are compiled at the local, regional, national, and global levels. Cumulative AST data can be used to prepare antibiograms at the individual health care facility level. These reports can be used to gain insight into appropriate empirical therapy options prior to the availability of AST results on an individual patient's isolate. Different types of cumulative AST data reports can also be compiled at the regional, national, and global levels to estimate susceptibility rates in geographic regions, document trends in evolving microbial populations, and recognize the appearance and spread of emerging antimicrobial resistance threats. The first CLSI M39 Guideline for Analysis and Presentation of Cumulative AST Data was published in 2000. Since that time, there have been changes to AST and reporting recommendations as well as the introduction of advanced informatics technologies to analyze and present data. The 5th edition of M39 has taken into consideration these changes to assist those who analyze, present, and utilize routine antibiograms and other types of cumulative AST data reports as well as those who design information systems for the capturing and analyzing of AST data. Furthermore, antimicrobial stewardship programs (ASPs) have expanded considerably, and uses of the antibiogram by ASPs have been addressed. This minireview will remind users of the basic recommendations for analysis and presentation of antibiograms and provide new suggestions to enhance these reports.

Automated detection of hospital outbreaks of multi-drug resistant pathogens in one Italian region.

BACKGROUND: Automated tools for antimicrobial resistance surveillance are critical for improving detection of drug-resistant organisms and informing prevention and control interventions. In this study, the WHONET-SaTScan software was used at a multihospital level in Tuscany, Italy, to identify case clusters consistent with hospital outbreaks caused by drug-resistant pathogens. METHODS: Antimicrobial resistance surveillance data from all Tuscany hospitals between January 2018 and December 2020 were analyzed using WHONET. The SaTScan package was used to detect case clusters applying a simulated prospective approach and the space-time permutation algorithm. Clusters were identified using resistance profiles and two distinct spatial variables: single medical services ('service') or groups of related services ('metaservice'). RESULTS: Data from eight bacterial pathogens were provided from 49 hospitals for 312,779 isolates from 158,809 patients. Single service-based analysis detected 693 hospital clusters, while metaservice-based analysis identified 635. There was no evidence for a difference between the two methods in terms of cluster length, cluster size, recurrence intervals, number of alerts, distribution across years or hospitals. Among clusters involving multiple services identified by both analyses, metaservice-detected clusters were usually larger and more statistically significant. CONCLUSIONS: WHONET-SaTScan proved to be a valuable multi-facility cluster detection tool that can be implemented for real-time surveillance.

The Impact of Coronavirus Disease 2019 (COVID-19) on Healthcare-Associated Infections.

BACKGROUND: The profound changes wrought by coronavirus disease 2019 (COVID-19) on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). We aimed to evaluate the association between COVID-19 surges and HAI and cluster rates. METHODS: In 148 HCA Healthcare-affiliated hospitals, from 1 March 2020 to 30 September 2020, and a subset of hospitals with microbiology and cluster data through 31 December 2020, we evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month. RESULTS: Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased. There were 60% (95% confidence interval [CI]: 23-108%) more CLABSI, 43% (95% CI: 8-90%) more CAUTI, and 44% (95% CI: 10-88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus, and Gram-negative organisms, were each significantly associated with COVID-19 surges. Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased. CONCLUSIONS: COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention.

Genome Sequencing Identifies Previously Unrecognized Klebsiella pneumoniae Outbreaks in Neonatal Intensive Care Units in the Philippines.

BACKGROUND: Klebsiella pneumoniae is a critically important pathogen in the Philippines. Isolates are commonly resistant to at least 2 classes of antibiotics, yet mechanisms and spread of its resistance are not well studied. METHODS: A retrospective sequencing survey was performed on carbapenem-, extended spectrum beta-lactam-, and cephalosporin-resistant Klebsiella pneumoniae isolated at 20 antimicrobial resistance (AMR) surveillance sentinel sites from 2015 through 2017. We characterized 259 isolates using biochemical methods, antimicrobial susceptibility testing, and whole-genome sequencing (WGS). Known AMR mechanisms were identified. Potential outbreaks were investigated by detecting clusters from epidemiologic, phenotypic, and genome-derived data. RESULTS: Prevalent AMR mechanisms detected include blaCTX-M-15 (76.8%) and blaNDM-1 (37.5%). An epidemic IncFII(Yp) plasmid carrying blaNDM-1 was also detected in 46 isolates from 6 sentinel sites and 14 different sequence types (STs). This plasmid was also identified as the main vehicle of carbapenem resistance in 2 previously unrecognized local outbreaks of ST348 and ST283 at 2 different sentinel sites. A third local outbreak of ST397 was also identified but without the IncFII(Yp) plasmid. Isolates in each outbreak site showed identical STs and K- and O-loci, and similar resistance profiles and AMR genes. All outbreak isolates were collected from blood of children aged < 1 year. CONCLUSION: WGS provided a better understanding of the epidemiology of multidrug resistant Klebsiella in the Philippines, which was not possible with only phenotypic and epidemiologic data. The identification of 3 previously unrecognized Klebsiella outbreaks highlights the utility of WGS in outbreak detection, as well as its importance in public health and in implementing infection control programs.

Genomic surveillance of Pseudomonas aeruginosa in the Philippines, 2013-2014.

Pseudomonas aeruginosa is an opportunistic pathogen that often causes nosocomial infections resistant to treatment. Rates of antimicrobial resistance (AMR) are increasing, as are rates of multidrug-resistant (MDR) and possible extensively drug-resistant (XDR) infections. Our objective was to characterize the molecular epidemiology and AMR mechanisms of this pathogen. We sequenced the whole genome for each of 176 P. aeruginosa isolates collected in the Philippines in 2013-2014; derived the multilocus sequence type (MLST), presence of AMR determinants and relatedness between isolates; and determined concordance between phenotypic and genotypic resistance. Carbapenem resistance was associated with loss of function of the OprD porin and acquisition of the metallo-ß-lactamase (MBL) gene bla VIM. Concordance between phenotypic and genotypic resistance was 93.27% overall for six antibiotics in three classes, but varied among aminoglycosides. The population of P. aeruginosa was diverse, with clonal expansions of XDR genomes belonging to MLSTs ST235, ST244, ST309 and ST773. We found evidence of persistence or reintroduction of the predominant clone ST235 in one hospital, and of transfer between hospitals. Most of the ST235 genomes formed a distinct lineage from global genomes, thus raising the possibility that they may be unique to the Philippines. In addition, long-read sequencing of one representative XDR ST235 isolate identified an integron carrying multiple resistance genes (including bla VIM-2), with differences in gene composition and synteny from the P. aeruginosa class 1 integrons described previously. The survey bridges the gap in genomic data from the Western Pacific Region and will be useful for ongoing surveillance; it also highlights the importance of curtailing the spread of ST235 within the Philippines.