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Surveys in low- and middle-income countries reveal emerging hotspots of resistance Misuse and overuse of antimicrobial agents, such as antibiotics, in humans, animals, and plants is leading to increasing antimicrobial resistance (AMR). AMR is an urgent global priority necessitating international collaboration through a “One Health” response (across humans, animals, plants, and their shared environment). Efforts have focused on AMR and antimicrobial use (AMU) in human infections; however, animals, plants, and the environment also contribute to AMR. More antibiotics are consumed by animals produced for food, to promote growth or disease prevention, than by humans. The increasing demand for animal protein, predominantly in low- and middle-income countries (LMICs), and links between AMU and AMR remains uncertain, particularly in LMICs where microbiology laboratories are scarce and antimicrobial drug availability remains largely unregulated ( 1 , 2 ). On page 1266 of this issue, Van Boeckel et al. ( 3 ) map AMR in animals for food production in LMICs, with implications for One Health strategies.

Bloodstream infections (BSIs) produced by antibiotic-resistant bacteria (ARB) cause a substantial disease burden worldwide. However, most estimates come from high-income settings and thus are not globally representative. This study quantifies the excess mortality, length of hospital stay (LOS), intensive care unit (ICU) admission, and economic costs associated with ARB BSIs, compared to antibiotic-sensitive bacteria (ASB), among adult inpatients in low- and middle-income countries (LMICs). We conducted a systematic review by searching 4 medical databases (PubMed, SCIELO, Scopus, and WHO's Global Index Medicus; initial search n = 13,012 from their inception to August 1, 2022). We only included quantitative studies. Our final sample consisted of n = 109 articles, excluding studies from high-income countries, without our outcomes of interest, or without a clear source of bloodstream infection. Crude mortality, ICU admission, and LOS were meta-analysed using the inverse variance heterogeneity model for the general and subgroup analyses including bacterial Gram type, family, and resistance type. For economic costs, direct medical costs per bed-day were sourced from WHO-CHOICE. Mortality costs were estimated based on productivity loss from years of potential life lost due to premature mortality. All costs were in 2020 USD. We assessed studies' quality and risk of publication bias using the MASTER framework. Multivariable meta-regressions were employed for the mortality and ICU admission outcomes only. Most included studies showed a significant increase in crude mortality (odds ratio (OR) 1.58, 95% CI [1.35 to 1.80], p < 0.001), total LOS (standardised mean difference \"SMD\" 0.49, 95% CI [0.20 to 0.78], p < 0.001), and ICU admission (OR 1.96, 95% CI [1.56 to 2.47], p < 0.001) for ARB versus ASB BSIs. Studies analysing Enterobacteriaceae, Acinetobacter baumanii, and Staphylococcus aureus in upper-middle-income countries from the African and Western Pacific regions showed the highest excess mortality, LOS, and ICU admission for ARB versus ASB BSIs per patient. Multivariable meta-regressions indicated that patients with resistant Acinetobacter baumanii BSIs had higher mortality odds when comparing ARB versus ASB BSI patients (OR 1.67, 95% CI [1.18 to 2.36], p 0.004). Excess direct medical costs were estimated at $12,442 (95% CI [$6,693 to $18,191]) for ARB versus ASB BSI per patient, with an average cost of $41,103 (95% CI [$30,931 to $51,274]) due to premature mortality. Limitations included the poor quality of some of the reviewed studies regarding the high risk of selective sampling or failure to adequately account for relevant confounders. We provide an overview of the impact ARB BSIs in limited resource settings derived from the existing literature. Drug resistance was associated with a substantial disease and economic burden in LMICs. Although, our results show wide heterogeneity between WHO regions, income groups, and pathogen-drug combinations. Overall, there is a paucity of BSI data from LMICs, which hinders implementation of country-specific policies and tracking of health progress.

Klebsiella pneumoniae is rapidly becoming untreatable using last-line antibiotics. It is especially problematic in hospitals, where it causes a range of acute infections. To approach controlling such a bacterium, we first must define what it is and how it varies genetically. Here we have determined the DNA sequence of K . pneumoniae isolates from around the world and present a detailed analysis of these data. We show that there is a wide spectrum of diversity, including variation within shared sequences and gain and loss of whole genes. Using this detailed blueprint, we show that there is an unrecognized association between the possession of specific gene profiles associated with virulence and antibiotic resistance and the differing disease outcomes seen for K . pneumoniae . Klebsiella pneumoniae is now recognized as an urgent threat to human health because of the emergence of multidrug-resistant strains associated with hospital outbreaks and hypervirulent strains associated with severe community-acquired infections. K . pneumoniae is ubiquitous in the environment and can colonize and infect both plants and animals. However, little is known about the population structure of K . pneumoniae , so it is difficult to recognize or understand the emergence of clinically important clones within this highly genetically diverse species. Here we present a detailed genomic framework for K . pneumoniae based on whole-genome sequencing of more than 300 human and animal isolates spanning four continents. Our data provide genome-wide support for the splitting of K . pneumoniae into three distinct species, KpI ( K . pneumoniae ), KpII ( K . quasipneumoniae ), and KpIII ( K . variicola ). Further, for K . pneumoniae (KpI), the entity most frequently associated with human infection, we show the existence of >150 deeply branching lineages including numerous multidrug-resistant or hypervirulent clones. We show K . pneumoniae has a large accessory genome approaching 30,000 protein-coding genes, including a number of virulence functions that are significantly associated with invasive community-acquired disease in humans. In our dataset, antimicrobial resistance genes were common among human carriage isolates and hospital-acquired infections, which generally lacked the genes associated with invasive disease. The convergence of virulence and resistance genes potentially could lead to the emergence of untreatable invasive K . pneumoniae infections; our data provide the whole-genome framework against which to track the emergence of such threats.

Background Reliable estimates of the current and future disease burden of antimicrobial resistance (AMR) are essential to combat the global drug-resistant infection crisis [1, 2]. Yet, despite considerable global efforts, our understanding of the burden of resistant infections remains disturbingly sparse [3]. More reliable, detailed and dynamic information is essential to successfully address an apparent rise in resistant infections, enabling policymakers and healthcare providers to implement national AMR action plans, and efficiently allocate resources. Major, recent efforts to estimate AMR burden include the Global Burden of Disease (GBD) 2016 study [4], the Review on AMR [1], and a 2015 study conducted by the European Centre for Disease Prevention and Control (ECDC) [5]. However, these provide insufficiently precise or comprehensive estimates to inform effective policies. The figure of 700,000 annual deaths from resistant infections often cited from the Review on AMR suffers from methodological limitations and statistical uncertainty. GBD 2016 focuses exclusively on multi-drug-resistant and extensively drug-resistant tuberculosis, and covers only a fraction of global AMR burden. The ECDC publication focuses only on the European Union and European Economic Area, and depends on European Antimicrobial Resistance Surveillance Network (EARS-Net) data. Challenges in AMR surveillance More accurately measuring AMR burden requires a fully described scientific measurement framework [3]. The global scientific community is responding to this call through the Global Research on Antimicrobial Resistance (GRAM) project, led by the University of Washington’s Institute for Health Metrics and Evaluation, and the University of Oxford’s Big Data Institute. GRAM will be the first study to quantify the incidence, prevalence, excess mortality risk, and overall disease burden attributable to key antibiotic resistant bacteria at the global, national and – where possible – sub-national levels. It will enable direct comparison of AMR burden with other global health threats, and provide an invaluable evidence base to guide policy. The accuracy of AMR burden estimates depends on the quality and availability of input data [3]. Present global surveillance systems remain disconnected and underdeveloped, with recent recommendations from the United Nations highlighting the urgent need to strengthen AMR surveillance globally [2]. Only 70 countries have enrolled in the World Health Organization (WHO)’s Global Antimicrobial Resistance Surveillance System (GLASS); fewer than 50 reported AMR rates in its most recent call-out [6]. Data are self-reported, heterogeneous, and based on few isolates from a handful of surveillance sites. The development of GLASS is a step in the right direction, but it is at an early stage [7]. GLASS limitations reflect broader global data insufficiencies that hinder the quantification of AMR burden; many nations lack the laboratory and data management capacities to support effective surveillance [7]. Microbiology data may be available electronically, but clinical datasets are frequently archived in laboratory books and patient notes, creating barriers to analysis. Electronic data also suffers from entry error caused by staffing constraints and a lack of reporting uniformity. Necessarily stringent privacy concerns further limit data sharing. Linked data that matches clinical bacteria to patient mortality outcomes, patient information and comorbid conditions, are essential to measure the excess mortality risk of resistant infections – and they are virtually non-existent. In the absence of comprehensive and diverse datasets from various regions and income-bases, GBD estimates rely heavily on modeling, which increases uncertainty. This is particularly concerning in low-income regions, where surveillance data is almost non-existent, access to essential antimicrobials is limited, and substandard antibiotics are widely available [2, 3]. High-income nations face their own challenges. An evaluation of Australia’s AMR response highlighted the need for a more robust animal surveillance system, and better One Health integration [8]. Although data-linking is a priority, the absence of consistent antimicrobial susceptibility testing and reporting standards impedes comparison of subnational datasets. Meanwhile, poor documentation and passive extraction methods limit the utility of community antibiotic prescribing data. Australia is one of many countries yet to contribute surveillance data to GLASS. Global surveillance initiatives Despite its shortcomings, Australia’s model of integrating AMR surveillance into system-wide risk-mitigation strategies may offer valuable lessons. The national Antimicrobial Use and Resistance in Australia network has identified alarming trends in resistance and antimicrobial use (AMU) [9]. Surveillance initiatives have gained jurisdictional and national support, with whole genome sequencing identifying the spread of specific resistant bacteria and resistance-causing genes. AMU surveillance initiatives in Australian tertiary and aged care facilities have facilitated the inclusion of antimicrobial stewardship standards within national medication safety and quality frameworks [9]. Overuse and misuse of antimicrobials is a considerable precursor to increasing resistance; to successfully limit AMR, behavior change strategies must be incorporated into policy schemes. While methodological barriers exist to data integration, efforts to embed AMU surveillance in overarching monitoring frameworks must continue. Better surveillance infrastructure requires ongoing funding and support from key donors and policymakers. The UK’s £265 million Fleming Fund for surveillance initiatives in low and middle-income countries is a welcome display of global leadership [1]. Likewise, the Australian Government has made $300 million AUD available to address regional infectious disease threats, with AMR earmarked as a key concern [10]. Such funding commitments should be used to support surveillance infrastructure-building efforts, both domestically and in vulnerable regions. Regional capacity-building must be part of a broad, coordinated international response. Governing bodies must assist countries to build AMR surveillance systems, while supporting the development and funding of national action plans in fragile states – currently, only one-fifth of national action plans are properly funded [7]. To effectively inform the burden of AMR, surveillance systems must coordinate comprehensive, globally consistent datasets through a One Health approach. Mechanisms facilitating increased data sharing, such as WHO’s GLASS initiative, must be supported. Improved public–private collaborations and open data sharing are essential to this goal, enabling greater utilization of vital private sector data.

The pipeline of new antibiotics is insufficient to keep pace with the growing global burden of drug-resistant infections. Substantial economic challenges discourage private investment in antibiotic research and development (R&D), with a decline in the number of companies and researchers working in the field. Compounding these issues, many countries (from low income to high income) face a growing crisis of antibiotic shortages and inequitable access to existing and emerging treatments. This has led to an increasing role for public and philanthropic funding in supporting antibiotic R&D via the creation of nonprofit public–private partnerships, including Combating Antibiotic-Resistant Bacteria Biopharmaceutical Accelerator (CARB-X) and the Global Antibiotic Research and Development Partnership (GARDP), industry support for the AMR Action Fund, and pilot schemes to evaluate and reimburse antibiotics in innovative ways. Now is the time to raise the urgency, ambition and commitments of the world’s leaders to fully support the antibiotic R&D ecosystem, incentivizing all sectors to conduct public health-driven antibiotic R&D and make effective antibiotics accessible to all who need them. Tackling antimicrobial resistance will require a sustainable research and development ecosystem for antibiotic development, alongside strategies for responsible use and global access.

Background Antimicrobial resistance (AMR) is an increasing threat to global health. There are > 14 million cases of enteric fever every year and > 135,000 deaths. The disease is primarily controlled by antimicrobial treatment, but this is becoming increasingly difficult due to AMR. Our objectives were to assess the prevalence and geographic distribution of AMR in Salmonella enterica serovars Typhi and Paratyphi A infections globally, to evaluate the extent of the problem, and to facilitate the creation of geospatial maps of AMR prevalence to help targeted public health intervention. Methods We performed a systematic review of the literature by searching seven databases for studies published between 1990 and 2018. We recategorised isolates to allow the analysis of fluoroquinolone resistance trends over the study period. The prevalence of multidrug resistance (MDR) and fluoroquinolone non-susceptibility (FQNS) in individual studies was illustrated by forest plots, and a random effects meta-analysis was performed, stratified by Global Burden of Disease (GBD) region and 5-year time period. Heterogeneity was assessed using the I 2 statistics. We present a descriptive analysis of ceftriaxone and azithromycin resistance. Findings We identified 4557 articles, of which 384, comprising 124,347 isolates (94,616 S . Typhi and 29,731 S . Paratyphi A) met the pre-specified inclusion criteria. The majority (276/384; 72%) of studies were from South Asia; 40 (10%) articles were identified from Sub-Saharan Africa. With the exception of MDR S . Typhi in South Asia, which declined between 1990 and 2018, and MDR S . Paratyphi A, which remained at low levels, resistance trends worsened for all antimicrobials in all regions. We identified several data gaps in Africa and the Middle East. Incomplete reporting of antimicrobial susceptibility testing (AST) and lack of quality assurance were identified. Interpretation Drug-resistant enteric fever is widespread in low- and middle-income countries, and the situation is worsening. It is essential that public health and clinical measures, which include improvements in water quality and sanitation, the deployment of S . Typhi vaccination, and an informed choice of treatment are implemented. However, there is no licenced vaccine for S . Paratyphi A. The standardised reporting of AST data and rollout of external quality control assessment are urgently needed to facilitate evidence-based policy and practice. Trial registration PROSPERO CRD42018029432 .

Despite a global epidemiological transition towards increased burden of non-communicable diseases, communicable diseases continue to cause substantial morbidity and mortality worldwide. Understanding the burden of a wide range of infectious diseases, and its variation by geography and age, is pivotal to research priority setting and resource mobilisation globally. We estimated disability-adjusted life-years (DALYs) associated with 85 pathogens in 2019, globally, regionally, and for 204 countries and territories. The term pathogen included causative agents, pathogen groups, infectious conditions, and aggregate categories. We applied a novel methodological approach to account for underlying, immediate, and intermediate causes of death, which counted every death for which a pathogen had a role in the pathway to death. We refer to this measure as the burden associated with infection, which was estimated by combining different sources of information. To compare the burden among all pathogens, we used pathogen-specific ratios to incorporate the burden of immediate and intermediate causes of death for pathogens modelled previously by the GBD. We created the ratios by using multiple cause of death data, hospital discharge data, linkage data, and minimally invasive tissue sampling data to estimate the fraction of deaths coming from the pathway to death chain. We multiplied the pathogen-specific ratios by age-specific years of life lost (YLLs), calculated with GBD 2019 methods, and then added the adjusted YLLs to age-specific years lived with disability (YLDs) from GBD 2019 to produce adjusted DALYs to account for deaths in the chain. We used standard GBD methods to calculate 95% uncertainty intervals (UIs) for final estimates of DALYs by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. We provided burden estimates pertaining to all ages and specifically to the under 5 years age group. Globally in 2019, an estimated 704 million (95% UI 610–820) DALYs were associated with 85 different pathogens, including 309 million (250–377; 43·9% of the burden) in children younger than 5 years. This burden accounted for 27·7% (and 65·5% in those younger than 5 years) of the previously reported total DALYs from all causes in 2019. Comparing super-regions, considerable differences were observed in the estimated pathogen-associated burdens in relation to DALYs from all causes, with the highest burden observed in sub-Saharan Africa (314 million [270–368] DALYs; 61·5% of total regional burden) and the lowest in the high-income super-region (31·8 million [25·4–40·1] DALYs; 9·8%). Three leading pathogens were responsible for more than 50 million DALYs each in 2019: tuberculosis (65·1 million [59·0–71·2]), malaria (53·6 million [27·0–91·3]), and HIV or AIDS (52·1 million [46·6–60·9]). Malaria was the leading pathogen for DALYs in children younger than 5 years (37·2 million [17·8–64·2]). We also observed substantial burden associated with previously less recognised pathogens, including Staphylococcus aureus and specific Gram-negative bacterial species (ie, Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, Acinetobacter baumannii, and Helicobacter pylori). Conversely, some pathogens had a burden that was smaller than anticipated. Our detailed breakdown of DALYs associated with a comprehensive list of pathogens on a global, regional, and country level has revealed the magnitude of the problem and helps to indicate where research funding mismatch might exist. Given the disproportionate impact of infection on low-income and middle-income countries, an essential next step is for countries and relevant stakeholders to address these gaps by making targeted investments. Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

Estimating the global burden of disease from infections caused by pathogens that have acquired antimicrobial resistance (AMR) is essential for resource allocation and to inform AMR action plans at national and global levels. However, the scarcity of robust and accepted methods to determine burden is widely acknowledged. In this Personal View, we discuss the underlying assumptions, characteristics, limitations, and comparability of the approaches used to quantify mortality from AMR bacterial infections. We show that the global burdens of AMR estimated in previous studies are not comparable because of their different methodological approaches, assumptions, and data used to generate the estimates. The analytical frameworks from previous studies are inadequate, and we conclude that a new approach to the estimation of deaths caused by AMR infection is needed. The innovation of a new approach will require the development of mechanisms to systematically collect a clinical dataset of substantial breadth and quality to support the accurate assessment of burden, combined with decision-making and resource allocation for interventions against AMR. We define key actions required and call for innovative thinking and solutions to address these problems.

Background and Objectives: The increase in antimicrobial resistance (AMR) across countries has seriously impacted the effective management of infectious diseases, with subsequent impact on morbidity, mortality and costs. This includes Pakistan. Antimicrobial surveillance activities should be mandatory to continually assess the extent of multidrug-resistant bacteria and the implications for future empiric prescribing. The objective of this retrospective observational study was to monitor the susceptibility pattern of microbes in Pakistan. Materials and Methods: Clinical samples from seven laboratories in Punjab, Pakistan were collected between January 2018 and April 2019, with Punjab being the most populous province in Pakistan. The isolates were identified and their antimicrobial susceptibility was tested using the Kirby-Bauer disc diffusion assay and micro broth dilution methods. The antibiotics assessed were those typically prescribed in Pakistan. Results: In total, 2523 bacterial cultural reports were studied. The most frequently isolated pathogens were Staphylococcus aureus (866, 34.3%), followed by Escherichia coli (814, 32.2%), Pseudomonas aeruginosa (454, 18.0%) and Klebsiella pneumoniae (269, 10.7%). Most pathogens were isolated from pus (1464, 58.0%), followed by urine (718, 28.5%), blood (164, 6.5%) and sputum (81, 3.2%). Conclusions: The findings suggest that current antimicrobial options are severally restricted in Pakistan due to the emergence of multidrug-resistant pathogens. This calls for urgent actions including initiating antimicrobial stewardship programs to enhance prudent prescribing of antibiotics. This includes agreeing on appropriate empiric therapy as part of agreed guidelines, in line with the WHO EML and AWaRe book, whilst awaiting culture reports. This is alongside other measures to reduce inappropriate antimicrobial prescribing and reverse the threat of rising AMR.

The mcr-1-associated plasmid in the study by Liu and colleagues, pHNSHP45, is an approximate 64 kb IncI plasmid with substantial sequence homology (>=80% sequence identity over >=80% of the query) to only four other plasmid sequences in GenBank (Accession numbers: