{"topic":"infectious-disease-amr","sort":"top","limit":25,"offset":0,"count":25,"papers":[{"id":"doi:10.1016/s0140-6736(21)02724-0","kind":"review","title":"Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis","authors":["Christopher J L Murray","Kevin Shunji Ikuta","Fablina Sharara","Lucien R Swetschinski","Gisela Robles Aguilar","Authia P Gray","Chieh Han","Catherine Bisignano","Puja C Rao","Eve E Wool","Sarah Charlotte Johnson","Annie J. Browne","Michael Give Chipeta","Frederick Fell","Sean C. Hackett","Georgina Haines–Woodhouse","Bahar H. Kashef Hamadani","Emmanuelle A. P. Kumaran","Barney McManigal","Sureeruk Achalapong","Ramesh K. Agarwal","Samuel Akech","Samuel B Albertson","John Amuasi","Jason Randolph Andrews"],"author_count":100,"year":2022,"published":"2022-01-19","venue":"The Lancet","cited_by":16288,"doi":"10.1016/s0140-6736(21)02724-0","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/s0140-6736(21)02724-0","archive_url":"https://space-kitty.com/papers/doi:10.1016/s0140-6736(21)02724-0","updated":null,"pmid":"35065702","pmcid":"PMC8841637","openalex_id":"W4206677002","pdf_url":"http://www.thelancet.com/article/S0140673621027240/pdf","abstract":"BACKGROUND: Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen-drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. METHODS: We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen-drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. FINDINGS: On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62-6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911-1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9-35·3), and lowest in Australasia, at 6·5 deaths (4·3-9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000-1 270 000) deaths attributable to AMR and 3·57 million (2·62-4·78) deaths associated with AMR in 2019. One pathogen-drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000-100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. INTERPRETATION: To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen-drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. FUNDING: Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex+europepmc","attribution":"Abstract of \"Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis\" by Christopher J L Murray, Kevin Shunji Ikuta, Fablina Sharara et al., https://doi.org/10.1016/s0140-6736(21)02724-0, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/s0140-6736(24)01867-1","kind":"article","title":"Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050","authors":["Mohsen Naghavi","Stein Emil Vollset","Kevin Shunji Ikuta","Lucien R Swetschinski","Authia P Gray","Eve E Wool","Gisela Robles Aguilar","Tomislav Meštrović","Georgia Smith","Chieh Han","Rebecca L. Hsu","Julian Chalek","Daniel T Araki","Erin Chung","Catalina Raggi","Anna Gershberg Hayoon","Nicole Davis Weaver","Paulina A Lindstedt","Amanda Elizabeth Smith","Umut Altay","Natalia V. Bhattacharjee","Konstantinos Giannakis","Frederick Fell","Barney McManigal","Nattwut Ekapirat"],"author_count":100,"year":2024,"published":"2024-09-01","venue":"The Lancet","cited_by":3903,"doi":"10.1016/s0140-6736(24)01867-1","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/s0140-6736(24)01867-1","archive_url":"https://space-kitty.com/papers/doi:10.1016/s0140-6736(24)01867-1","updated":null,"pmid":"39299261","pmcid":"PMC11718157","openalex_id":"W4402557213","pdf_url":"https://europepmc.org/articles/PMC11718157/pdf","abstract":"BACKGROUND: Antimicrobial resistance (AMR) poses an important global health challenge in the 21st century. A previous study has quantified the global and regional burden of AMR for 2019, followed with additional publications that provided more detailed estimates for several WHO regions by country. To date, there have been no studies that produce comprehensive estimates of AMR burden across locations that encompass historical trends and future forecasts. METHODS: We estimated all-age and age-specific deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 22 pathogens, 84 pathogen-drug combinations, and 11 infectious syndromes in 204 countries and territories from 1990 to 2021. We collected and used multiple cause of death data, hospital discharge data, microbiology data, literature studies, single drug resistance profiles, pharmaceutical sales, antibiotic use surveys, mortality surveillance, linkage data, outpatient and inpatient insurance claims data, and previously published data, covering 520 million individual records or isolates and 19 513 study-location-years. We used statistical modelling to produce estimates of AMR burden for all locations, including those with no data. Our approach leverages the estimation of five broad component quantities: the number of deaths involving sepsis; the proportion of infectious deaths attributable to a given infectious syndrome; the proportion of infectious syndrome deaths attributable to a given pathogen; the percentage of a given pathogen resistant to an antibiotic of interest; and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden attributable to and associated with AMR, which we define based on two counterfactuals; respectively, an alternative scenario in which all drug-resistant infections are replaced by drug-susceptible infections, and an alternative scenario in which all drug-resistant infections were replaced by no infection. Additionally, we produced global and regional forecasts of AMR burden until 2050 for three scenarios: a reference scenario that is a probabilistic forecast of the most likely future; a Gram-negative drug scenario that assumes future drug development that targets Gram-negative pathogens; and a better care scenario that assumes future improvements in health-care quality and access to appropriate antimicrobials. We present final estimates aggregated to the global, super-regional, and regional level. FINDINGS: In 2021, we estimated 4·71 million (95% UI 4·23-5·19) deaths were associated with bacterial AMR, including 1·14 million (1·00-1·28) deaths attributable to bacterial AMR. Trends in AMR mortality over the past 31 years varied substantially by age and location. From 1990 to 2021, deaths from AMR decreased by more than 50% among children younger than 5 years yet increased by over 80% for adults 70 years and older. AMR mortality decreased for children younger than 5 years in all super-regions, whereas AMR mortality in people 5 years and older increased in all super-regions. For both deaths associated with and deaths attributable to AMR, meticillin-resistant Staphylococcus aureus increased the most globally (from 261 000 associated deaths [95% UI 150 000-372 000] and 57 200 attributable deaths [34 100-80 300] in 1990, to 550 000 associated deaths [500 000-600 000] and 130 000 attributable deaths [113 000-146 000] in 2021). Among Gram-negative bacteria, resistance to carbapenems increased more than any other antibiotic class, rising from 619 000 associated deaths (405 000-834 000) in 1990, to 1·03 million associated deaths (909 000-1·16 million) in 2021, and from 127 000 attributable deaths (82 100-171 000) in 1990, to 216 000 (168 000-264 000) attributable deaths in 2021. There was a notable decrease in non-COVID-related infectious disease in 2020 and 2021. Our forecasts show that an estimated 1·91 million (1·56-2·26) deaths attributable to AMR and 8·22 million (6·85-9·65) deaths associated with AMR could occur globally in 2050. Super-regions with the highest all-age AMR mortality rate in 2050 are forecasted to be south Asia and Latin America and the Caribbean. Increases in deaths attributable to AMR will be largest among those 70 years and older (65·9% [61·2-69·8] of all-age deaths attributable to AMR in 2050). In stark contrast to the strong increase in number of deaths due to AMR of 69·6% (51·5-89·2) from 2022 to 2050, the number of DALYs showed a much smaller increase of 9·4% (-6·9 to 29·0) to 46·5 million (37·7 to 57·3) in 2050. Under the better care scenario, across all age groups, 92·0 million deaths (82·8-102·0) could be cumulatively averted between 2025 and 2050, through better care of severe infections and improved access to antibiotics, and under the Gram-negative drug scenario, 11·1 million AMR deaths (9·08-13·2) could be averted through the development of a Gram-negative drug pipeline to prevent AMR deaths. INTERPRETATION: This study presents the first comprehensive assessment of the global burden of AMR from 1990 to 2021, with results forecasted until 2050. Evaluating changing trends in AMR mortality across time and location is necessary to understand how this important global health threat is developing and prepares us to make informed decisions regarding interventions. Our findings show the importance of infection prevention, as shown by the reduction of AMR deaths in those younger than 5 years. Simultaneously, our results underscore the concerning trend of AMR burden among those older than 70 years, alongside a rapidly ageing global community. The opposing trends in the burden of AMR deaths between younger and older individuals explains the moderate future increase in global number of DALYs versus number of deaths. Given the high variability of AMR burden by location and age, it is important that interventions combine infection prevention, vaccination, minimisation of inappropriate antibiotic use in farming and humans, and research into new antibiotics to mitigate the number of AMR deaths that are forecasted for 2050. FUNDING: UK Department of Health and Social Care's Fleming Fund using UK aid, and the Wellcome Trust.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex+europepmc","attribution":"Abstract of \"Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050\" by Mohsen Naghavi, Stein Emil Vollset, Kevin Shunji Ikuta et al., https://doi.org/10.1016/s0140-6736(24)01867-1, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/s0140-6736(22)02185-7","kind":"article","title":"Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019","authors":["Kevin Shunji Ikuta","Lucien R Swetschinski","Gisela Robles Aguilar","Fablina Sharara","Tomislav Meštrović","Authia P Gray","Nicole Davis Weaver","Eve E Wool","Chieh Han","Anna Gershberg Hayoon","Amirali Aali","Semagn Mekonnen Abate","Mohsen Abbasi‐Kangevari","Zeinab Abbasi-Kangevari","Sherief Mohamed Abd-Elsalam","Getachew Abebe","Aidin Abedi","Amir Parsa Abhari","Hassan Abidi","Richard Gyan Aboagye","Abdorrahim Absalan","Hiwa Abubaker Ali","Juan Manuel Acuna","Tigist Demssew Adane","Isaac Yeboah Addo"],"author_count":100,"year":2022,"published":"2022-11-21","venue":"The Lancet","cited_by":2232,"doi":"10.1016/s0140-6736(22)02185-7","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/s0140-6736(22)02185-7","archive_url":"https://space-kitty.com/papers/doi:10.1016/s0140-6736(22)02185-7","updated":null,"pmid":"36423648","pmcid":"PMC9763654","openalex_id":"W4309503005","pdf_url":"http://www.thelancet.com/article/S0140673622021857/pdf","abstract":"BACKGROUND: Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes. METHODS: We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. FINDINGS: From an estimated 13·7 million (95% UI 10·9-17·1) infection-related deaths in 2019, there were 7·7 million deaths (5·7-10·2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13·6% (10·2-18·1) of all global deaths and 56·2% (52·1-60·1) of all sepsis-related deaths in 2019. Five leading pathogens-Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa-were responsible for 54·9% (52·9-56·9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185-285) per 100 000 population, and lowest in the high-income super-region, with 52·2 deaths (37·4-71·5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths. INTERPRETATION: The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development. FUNDING: Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care, using UK aid funding managed by the Fleming Fund.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex+europepmc","attribution":"Abstract of \"Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019\" by Kevin Shunji Ikuta, Lucien R Swetschinski, Gisela Robles Aguilar et al., https://doi.org/10.1016/s0140-6736(22)02185-7, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/s1473-3099(25)00118-5","kind":"article","title":"The WHO Bacterial Priority Pathogens List 2024: a prioritisation study to guide research, development, and public health strategies against antimicrobial resistance","authors":["Hatim F. Sati","Elena Carrara","Alessia Savoldi","Paul Hansen","Jacopo Garlasco","Enrica Campagnaro","Simone Boccia","Juan Antonio Castillo-Polo","Eugenia Magrini","Pilar García-Vello","Eve E Wool","Valeria Gigante","Erin M Duffy","Alessandro Cassini","Benedikt David Huttner","Pilar Ramón-Pardo","Mohsen Naghavi","Fuad Mirzayev","Matteo Zignol E","Alexandra Cameron","Evelina Tacconelli","Aaron Aboderin","Majed Al Ghoribi","Jameela Al-Salman","Afreenish Amir"],"author_count":41,"year":2025,"published":"2025-04-14","venue":"The Lancet Infectious Diseases","cited_by":947,"doi":"10.1016/s1473-3099(25)00118-5","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/s1473-3099(25)00118-5","archive_url":"https://space-kitty.com/papers/doi:10.1016/s1473-3099(25)00118-5","updated":null,"pmid":"40245910","pmcid":"PMC12367593","openalex_id":"W4409430637","pdf_url":"https://europepmc.org/articles/PMC12367593/pdf","abstract":"BACKGROUND: The 2017 WHO Bacterial Priority Pathogens List (BPPL) has been instrumental in guiding global policy, research and development, and investments to address the most urgent threats from antibiotic-resistant pathogens, and it is a key public health tool for the prevention and control of antimicrobial resistance (AMR). Since its release, at least 13 new antibiotics targeting bacterial priority pathogens have been approved. The 2024 WHO BPPL aims to refine and build on the previous list by incorporating new data and evidence, addressing previous limitations, and improving pathogen prioritisation to better guide global efforts in combating AMR. METHODS: The 2024 WHO BPPL followed a similar approach to the first prioritisation exercise, using a multicriteria decision analysis framework. 24 antibiotic-resistant bacterial pathogens were scored based on eight criteria, including mortality, non-fatal burden, incidence, 10-year resistance trends, preventability, transmissibility, treatability, and antibacterial pipeline status. Pathogens were assessed on each of the criteria on the basis of available evidence and expert judgement. A preferences survey using a pairwise comparison was administered to 100 international experts (among whom 79 responded and 78 completed the survey) to determine the relative weights of the criteria. Applying these weights, the final ranking of pathogens was determined by calculating a total score in the range of 0-100% for each pathogen. Subgroup and sensitivity analyses were conducted to assess the impact of experts' consistency, background, and geographical origin on the stability of the rankings. An independent advisory group reviewed the final list, and pathogens were subsequently streamlined and grouped into three priority tiers based on a quartile scoring system: critical (highest quartile), high (middle quartiles), and medium (lowest quartile). FINDINGS: The pathogens' total scores ranged from 84% for the top-ranked bacterium (carbapenem-resistant Klebsiella pneumoniae) to 28% for the bottom-ranked bacterium (penicillin-resistant group B streptococci). Antibiotic-resistant Gram-negative bacteria (including K pneumoniae, Acinetobacter spp, and Escherichia coli), as well as rifampicin-resistant Mycobacterium tuberculosis, were ranked in the highest quartile. Among the bacteria commonly responsible for community-acquired infections, the highest rankings were for fluoroquinolone-resistant Salmonella enterica serotype Typhi (72%), Shigella spp (70%), and Neisseria gonorrhoeae (64%). Other important pathogens on the list include Pseudomonas aeruginosa and Staphylococcus aureus. The results of the preferences survey showed a strong inter-rater agreement, with Spearman's rank correlation coefficient and Kendall's coefficient of concordance both at 0·9. The final ranking showed high stability, with clustering of the pathogens based on experts' backgrounds and origins not resulting in any substantial changes to the ranking. INTERPRETATION: The 2024 WHO BPPL is a key tool for prioritising research and development investments and informing global public health policies to combat AMR. Gram-negative bacteria and rifampicin-resistant M tuberculosis remain critical priority pathogens, underscoring their persistent threat and the limitations of the current antibacterial pipeline. Focused efforts and sustained investments in novel antibacterials are needed to address AMR priority pathogens, which include high-burden antibiotic-resistant bacteria such as Salmonella and Shigella spp, N gonorrhoeae, and S aureus. Beyond research and development, efforts to address these pathogens should also include expanding equitable access to existing drugs, enhancing vaccine coverage, and strengthening infection prevention and control measures. FUNDING: This work is based on the development of the 2024 WHO BPPL, which was conducted by the WHO AMR Division through grants from the Government of Austria, the Government of Germany, the Government of Saudi Arabia, and the European Commission's Health Emergency Preparedness and Response Authority. TRANSLATIONS: For the Arabic, French, Italian, Japanese and Spanish translations of the abstract see Supplementary Materials section.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex+europepmc","attribution":"Abstract of \"The WHO Bacterial Priority Pathogens List 2024: a prioritisation study to guide research, development, and public health strategies against antimicrobial resistance\" by Hatim F. Sati, Elena Carrara, Alessia Savoldi et al., https://doi.org/10.1016/s1473-3099(25)00118-5, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.12688/wellcomeopenres.14826.1","kind":"article","title":"Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications","authors":["Jolley KA","Bray JE","Maiden MCJ"],"author_count":3,"year":2018,"published":"2018-09-24","venue":"Wellcome open research","cited_by":3086,"doi":"10.12688/wellcomeopenres.14826.1","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.12688/wellcomeopenres.14826.1","archive_url":"https://space-kitty.com/papers/doi:10.12688/wellcomeopenres.14826.1","updated":null,"pmid":"30345391","pmcid":"PMC6192448","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC6192448/pdf","abstract":"The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera. Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes. Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications. The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation. Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes. There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question. In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications\" by Jolley KA, Bray JE, Maiden MCJ, https://doi.org/10.12688/wellcomeopenres.14826.1, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/j.glmedi.2024.100081","kind":"article","title":"Antimicrobial resistance: Impacts, challenges, and future prospects","authors":["Sirwan Khalid Ahmed","Safin Hassan Hussein","Karzan Qurbani","Radhwan Hussein Ibrahim","Abdulmalik Fareeq","Kochr Ali Mahmood","Mona Gamal Mohamed"],"author_count":7,"year":2024,"published":"2024-03-02","venue":"Journal of Medicine Surgery and Public Health","cited_by":1252,"doi":"10.1016/j.glmedi.2024.100081","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.glmedi.2024.100081","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.glmedi.2024.100081","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W4392349824","pdf_url":null,"abstract":"Antimicrobial resistance (AMR) is a critical global health issue driven by antibiotic misuse and overuse in various sectors, leading to the emergence of resistant microorganisms. The history of AMR dates back to the discovery of penicillin, with the rise of multidrug-resistant pathogens posing significant challenges to healthcare systems worldwide. The misuse of antibiotics in human and animal health, as well as in agriculture, contributes to the spread of resistance genes, creating a \"Silent Pandemic\" that could surpass other causes of mortality by 2050. AMR affects both humans and animals, with resistant pathogens posing challenges in treating infections. Various mechanisms, such as enzymatic modification and biofilm formation, enable microbes to withstand the effects of antibiotics. The lack of effective antibiotics threatens routine medical procedures and could lead to millions of deaths annually if left unchecked. The economic impact of AMR is substantial, with projected losses in the trillions of dollars and significant financial burdens on healthcare systems and agriculture. Artificial intelligence is being explored as a tool to combat AMR by improving diagnostics and treatment strategies, although challenges such as data quality and algorithmic biases exist. To address AMR effectively, a One Health approach that considers human, animal, and environmental factors is crucial. This includes enhancing surveillance systems, promoting stewardship programs, and investing in research and development for new antimicrobial options. Public awareness, education, and international collaboration are essential for combating AMR and preserving the efficacy of antibiotics for future generations.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex","attribution":"Abstract of \"Antimicrobial resistance: Impacts, challenges, and future prospects\" by Sirwan Khalid Ahmed, Safin Hassan Hussein, Karzan Qurbani et al., https://doi.org/10.1016/j.glmedi.2024.100081, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1093/nar/gkz935","kind":"article","title":"CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database","authors":["Alcock BP","Raphenya AR","Lau TTY","Tsang KK","Bouchard M","Edalatmand A","Huynh W","Nguyen AV","Cheng AA","Liu S","Min SY","Miroshnichenko A","Tran HK","Werfalli RE","Nasir JA","Oloni M","Speicher DJ","Florescu A","Singh B","Faltyn M","Hernandez-Koutoucheva A","Sharma AN","Bordeleau E","Pawlowski AC","Zubyk HL"],"author_count":34,"year":2020,"published":"2020-01-01","venue":"Nucleic acids research","cited_by":2855,"doi":"10.1093/nar/gkz935","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1093/nar/gkz935","archive_url":"https://space-kitty.com/papers/doi:10.1093/nar/gkz935","updated":null,"pmid":"31665441","pmcid":"PMC7145624","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC7145624/pdf","abstract":"The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database\" by Alcock BP, Raphenya AR, Lau TTY et al., https://doi.org/10.1093/nar/gkz935, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1128/cmr.00181-19","kind":"review","title":"Antimicrobial Resistance in ESKAPE Pathogens","authors":["David M. P. De Oliveira","Brian M. Forde","Timothy J. Kidd","Patrick N. A. Harris","Mark A. Schembri","Scott A. Beatson","David Leslie Paterson","Mark J. Walker"],"author_count":8,"year":2020,"published":"2020-05-12","venue":"Clinical Microbiology Reviews","cited_by":2102,"doi":"10.1128/cmr.00181-19","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1128/cmr.00181-19","archive_url":"https://space-kitty.com/papers/doi:10.1128/cmr.00181-19","updated":null,"pmid":"32404435","pmcid":null,"openalex_id":"W3024693033","pdf_url":"https://cmr.asm.org/content/cmr/33/3/e00181-19.full.pdf","abstract":null,"abstract_license":null,"license":null,"is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Resistance in Bacteria"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"doi:10.3390/healthcare11131946","kind":"review","title":"Antimicrobial Resistance: A Growing Serious Threat for Global Public Health","authors":["Salam MA","Al-Amin MY","Salam MT","Pawar JS","Akhter N","Rabaan AA","Alqumber MAA"],"author_count":7,"year":2023,"published":"2023-07-05","venue":"Healthcare (Basel, Switzerland)","cited_by":1428,"doi":"10.3390/healthcare11131946","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.3390/healthcare11131946","archive_url":"https://space-kitty.com/papers/doi:10.3390/healthcare11131946","updated":null,"pmid":"37444780","pmcid":null,"openalex_id":null,"pdf_url":null,"abstract":"Antibiotics are among the most important discoveries of the 20th century, having saved millions of lives from infectious diseases. Microbes have developed acquired antimicrobial resistance (AMR) to many drugs due to high selection pressure from increasing use and misuse of antibiotics over the years. The transmission and acquisition of AMR occur primarily via a human-human interface both within and outside of healthcare facilities. A huge number of interdependent factors related to healthcare and agriculture govern the development of AMR through various drug-resistance mechanisms. The emergence and spread of AMR from the unrestricted use of antimicrobials in livestock feed has been a major contributing factor. The prevalence of antimicrobial-resistant bacteria has attained an incongruous level worldwide and threatens global public health as a silent pandemic, necessitating urgent intervention. Therapeutic options of infections caused by antimicrobial-resistant bacteria are limited, resulting in significant morbidity and mortality with high financial impact. The paucity in discovery and supply of new novel antimicrobials to treat life-threatening infections by resistant pathogens stands in sharp contrast to demand. Immediate interventions to contain AMR include surveillance and monitoring, minimizing over-the-counter antibiotics and antibiotics in food animals, access to quality and affordable medicines, vaccines and diagnostics, and enforcement of legislation. An orchestrated collaborative action within and between multiple national and international organizations is required urgently, otherwise, a postantibiotic era can be a more real possibility than an apocalyptic fantasy for the 21st century. This narrative review highlights on this basis, mechanisms and factors in microbial resistance, and key strategies to combat antimicrobial resistance.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Antimicrobial Resistance: A Growing Serious Threat for Global Public Health\" by Salam MA, Al-Amin MY, Salam MT et al., https://doi.org/10.3390/healthcare11131946, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/s1473-3099(18)30605-4","kind":"article","title":"Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis","authors":["Cassini A","Högberg LD","Plachouras D","Quattrocchi A","Hoxha A","Simonsen GS","Colomb-Cotinat M","Kretzschmar ME","Devleesschauwer B","Cecchini M","Ouakrim DA","Oliveira TC","Struelens MJ","Suetens C","Monnet DL"],"author_count":15,"year":2019,"published":"2018-11-05","venue":"The Lancet. Infectious diseases","cited_by":2136,"doi":"10.1016/s1473-3099(18)30605-4","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/s1473-3099(18)30605-4","archive_url":"https://space-kitty.com/papers/doi:10.1016/s1473-3099(18)30605-4","updated":null,"pmid":"30409683","pmcid":"PMC6300481","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC6300481/pdf","abstract":"Background Infections due to antibiotic-resistant bacteria are threatening modern health care. However, estimating their incidence, complications, and attributable mortality is challenging. We aimed to estimate the burden of infections caused by antibiotic-resistant bacteria of public health concern in countries of the EU and European Economic Area (EEA) in 2015, measured in number of cases, attributable deaths, and disability-adjusted life-years (DALYs). Methods We estimated the incidence of infections with 16 antibiotic resistance-bacterium combinations from European Antimicrobial Resistance Surveillance Network (EARS-Net) 2015 data that was country-corrected for population coverage. We multiplied the number of bloodstream infections (BSIs) by a conversion factor derived from the European Centre for Disease Prevention and Control point prevalence survey of health-care-associated infections in European acute care hospitals in 2011-12 to estimate the number of non-BSIs. We developed disease outcome models for five types of infection on the basis of systematic reviews of the literature. Findings From EARS-Net data collected between Jan 1, 2015, and Dec 31, 2015, we estimated 671 689 (95% uncertainty interval [UI] 583 148-763 966) infections with antibiotic-resistant bacteria, of which 63·5% (426 277 of 671 689) were associated with health care. These infections accounted for an estimated 33 110 (28 480-38 430) attributable deaths and 874 541 (768 837-989 068) DALYs. The burden for the EU and EEA was highest in infants (aged <1 year) and people aged 65 years or older, had increased since 2007, and was highest in Italy and Greece. Interpretation Our results present the health burden of five types of infection with antibiotic-resistant bacteria expressed, for the first time, in DALYs. The estimated burden of infections with antibiotic-resistant bacteria in the EU and EEA is substantial compared with that of other infectious diseases, and has increased since 2007. Our burden estimates provide useful information for public health decision-makers prioritising interventions for infectious diseases. Funding European Centre for Disease Prevention and Control.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis\" by Cassini A, Högberg LD, Plachouras D et al., https://doi.org/10.1016/s1473-3099(18)30605-4, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.3389/bjbs.2023.11387","kind":"review","title":"Antimicrobial Resistance (AMR)","authors":["Ka Wah Kelly Tang","Beverley Cherie Millar","John Edmund Moore"],"author_count":3,"year":2023,"published":"2023-06-28","venue":"British Journal of Biomedical Science","cited_by":1038,"doi":"10.3389/bjbs.2023.11387","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.3389/bjbs.2023.11387","archive_url":"https://space-kitty.com/papers/doi:10.3389/bjbs.2023.11387","updated":null,"pmid":"37448857","pmcid":"PMC10336207","openalex_id":"W4382585357","pdf_url":"https://www.frontierspartnerships.org/articles/10.3389/bjbs.2023.11387/pdf","abstract":"Antimicrobial resistance (AMR) has now emerged as a chronic public health problem globally, with the forecast of 10 million deaths per year globally by 2050. AMR occurs when viruses, bacteria, fungi and parasites do not respond to antimicrobial treatments in humans and animals, thus allowing the survival of the microorganism within the host. The prominent cause contributing to the current crisis remains to be the overuse and misuse of antimicrobials, particularly the inappropriate usage of antibiotics, increasing the global burden of antimicrobial resistance. The global consumption and usage of antibiotics are therefore closely monitored at all times. This review provides a current overview of the implications of strategies used by international governmental organisations, including the UN’s 17 Sustainable Development Goals (SDGs), to address the problem of antibiotic resistance, as well as the “ One Health Approach ,” a system incorporating a multidisciplinary effort to achieve the best possible health outcome by acknowledging the clear connections between humans, animals and their shared environment. The importance of public awareness and health literacy of lay audiences still needs to be further emphasised as part of global and local action plans. Antimicrobial resistance continues to be a major global public health dilemma of the 21st century. Already this topic is receiving substantial political input from the G7 countries and continues to be on the agenda of numerous political conferences. The consequences of failure to adequately address AMR are profound, with estimations of a return to the pre-antibiotic era, where everyday infections relating to childbirth, surgery and open fractured limbs could be potentially life-threatening. AMR itself represents a microcosm of factors, including social anthropology, civil unrest/war, diasporas, ethnic displacement, political systems, healthcare, economics, societal behaviour both at a population and individual level, health literacy, geoclimatic events, global travel and pharmaceutical innovation and investment, thus finding a solution that adequately addresses AMR and which helps stem further AMR emergence is complicated. Success will involve individuals, communities and nations all working together to ensure that the world continues to possess a sufficient armamentarium of effective antimicrobials that will sustain human and animal health, both now and in the future.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex+europepmc","attribution":"Abstract of \"Antimicrobial Resistance (AMR)\" by Ka Wah Kelly Tang, Beverley Cherie Millar, John Edmund Moore, https://doi.org/10.3389/bjbs.2023.11387, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/s0140-6736(17)30938-8","kind":"review","title":"Global, regional, and national disease burden estimates of acute lower respiratory infections due to respiratory syncytial virus in young children in 2015: a systematic review and modelling study","authors":["Shi T","McAllister DA","O'Brien KL","Simoes EAF","Madhi SA","Gessner BD","Polack FP","Balsells E","Acacio S","Aguayo C","Alassani I","Ali A","Antonio M","Awasthi S","Awori JO","Azziz-Baumgartner E","Baggett HC","Baillie VL","Balmaseda A","Barahona A","Basnet S","Bassat Q","Basualdo W","Bigogo G","Bont L"],"author_count":122,"year":2017,"published":"2017-07-07","venue":"Lancet (London, England)","cited_by":1997,"doi":"10.1016/s0140-6736(17)30938-8","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/s0140-6736(17)30938-8","archive_url":"https://space-kitty.com/papers/doi:10.1016/s0140-6736(17)30938-8","updated":null,"pmid":"28689664","pmcid":"PMC5592248","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC5592248/pdf","abstract":"Background We have previously estimated that respiratory syncytial virus (RSV) was associated with 22% of all episodes of (severe) acute lower respiratory infection (ALRI) resulting in 55 000 to 199 000 deaths in children younger than 5 years in 2005. In the past 5 years, major research activity on RSV has yielded substantial new data from developing countries. With a considerably expanded dataset from a large international collaboration, we aimed to estimate the global incidence, hospital admission rate, and mortality from RSV-ALRI episodes in young children in 2015. Methods We estimated the incidence and hospital admission rate of RSV-associated ALRI (RSV-ALRI) in children younger than 5 years stratified by age and World Bank income regions from a systematic review of studies published between Jan 1, 1995, and Dec 31, 2016, and unpublished data from 76 high quality population-based studies. We estimated the RSV-ALRI incidence for 132 developing countries using a risk factor-based model and 2015 population estimates. We estimated the in-hospital RSV-ALRI mortality by combining in-hospital case fatality ratios with hospital admission estimates from hospital-based (published and unpublished) studies. We also estimated overall RSV-ALRI mortality by identifying studies reporting monthly data for ALRI mortality in the community and RSV activity. Findings We estimated that globally in 2015, 33·1 million (uncertainty range [UR] 21·6-50·3) episodes of RSV-ALRI, resulted in about 3·2 million (2·7-3·8) hospital admissions, and 59 600 (48 000-74 500) in-hospital deaths in children younger than 5 years. In children younger than 6 months, 1·4 million (UR 1·2-1·7) hospital admissions, and 27 300 (UR 20 700-36 200) in-hospital deaths were due to RSV-ALRI. We also estimated that the overall RSV-ALRI mortality could be as high as 118 200 (UR 94 600-149 400). Incidence and mortality varied substantially from year to year in any given population. Interpretation Globally, RSV is a common cause of childhood ALRI and a major cause of hospital admissions in young children, resulting in a substantial burden on health-care services. About 45% of hospital admissions and in-hospital deaths due to RSV-ALRI occur in children younger than 6 months. An effective maternal RSV vaccine or monoclonal antibody could have a substantial effect on disease burden in this age group. Funding The Bill & Melinda Gates Foundation.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Global, regional, and national disease burden estimates of acute lower respiratory infections due to respiratory syncytial virus in young children in 2015: a systematic review and modelling study\" by Shi T, McAllister DA, O'Brien KL et al., https://doi.org/10.1016/s0140-6736(17)30938-8, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1038/s41598-021-91456-0","kind":"article","title":"AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence","authors":["Feldgarden M","Brover V","Gonzalez-Escalona N","Frye JG","Haendiges J","Haft DH","Hoffmann M","Pettengill JB","Prasad AB","Tillman GE","Tyson GH","Klimke W"],"author_count":12,"year":2021,"published":"2021-06-16","venue":"Scientific reports","cited_by":1516,"doi":"10.1038/s41598-021-91456-0","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1038/s41598-021-91456-0","archive_url":"https://space-kitty.com/papers/doi:10.1038/s41598-021-91456-0","updated":null,"pmid":"34135355","pmcid":"PMC8208984","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC8208984/pdf","abstract":"Antimicrobial resistance (AMR) is a significant public health threat. With the rise of affordable whole genome sequencing, in silico approaches to assessing AMR gene content can be used to detect known resistance mechanisms and potentially identify novel mechanisms. To enable accurate assessment of AMR gene content, as part of a multi-agency collaboration, NCBI developed a comprehensive AMR gene database, the Bacterial Antimicrobial Resistance Reference Gene Database and the AMR gene detection tool AMRFinder. Here, we describe the expansion of the Reference Gene Database, now called the Reference Gene Catalog, to include putative acid, biocide, metal, stress resistance genes, in addition to virulence genes and species-specific point mutations. Genes and point mutations are classified by broad functions, as well as more detailed functions. As we have expanded both the functional repertoire of identified genes and functionality, NCBI released a new version of AMRFinder, known as AMRFinderPlus. This new tool allows users the option to utilize only the core set of AMR elements, or include stress response and virulence genes, too. AMRFinderPlus can detect acquired genes and point mutations in both protein and nucleotide sequence. In addition, the evidence used to identify the gene has been expanded to include whether nucleotide or protein sequence was used, its location in the contig, and presence of an internal stop codon. These database improvements and functional expansions will enable increased precision in identifying AMR genes, linking AMR genotypes and phenotypes, and determining possible relationships between AMR, virulence, and stress response.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence\" by Feldgarden M, Brover V, Gonzalez-Escalona N et al., https://doi.org/10.1038/s41598-021-91456-0, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1371/journal.pmed.1002184","kind":"article","title":"Will 10 Million People Die a Year due to Antimicrobial Resistance by 2050?","authors":["Marlieke E.A. de Kraker","Andrew James Stewardson","Stéphan Harbarth"],"author_count":3,"year":2016,"published":"2016-11-29","venue":"PLoS Medicine","cited_by":1608,"doi":"10.1371/journal.pmed.1002184","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1371/journal.pmed.1002184","archive_url":"https://space-kitty.com/papers/doi:10.1371/journal.pmed.1002184","updated":null,"pmid":"27898664","pmcid":"PMC5127510","openalex_id":"W2558941103","pdf_url":"https://journals.plos.org/plosmedicine/article/file?id=10.1371/journal.pmed.1002184&type=printable","abstract":"Points• A recent high profile report estimates that, by 2050, 10 million people will die every year due to antimicrobial resistance (AMR) unless a global response to the problem of AMR is mounted.• There is undoubtedly a large clinical and public health burden associated with AMR, but it is challenging to quantify the associated excess morbidity and mortality.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex+europepmc","attribution":"Abstract of \"Will 10 Million People Die a Year due to Antimicrobial Resistance by 2050?\" by Marlieke E.A. de Kraker, Andrew James Stewardson, Stéphan Harbarth, https://doi.org/10.1371/journal.pmed.1002184, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/s0140-6736(15)00474-2","kind":"review","title":"Access to effective antimicrobials: a worldwide challenge","authors":["Ramanan Laxminarayan","Precious Matsoso","Suraj Pant","Charles H. Brower","John‐Arne Røttingen","Keith P. Klugman","Sally C. Davies"],"author_count":7,"year":2015,"published":"2015-11-18","venue":"The Lancet","cited_by":1461,"doi":"10.1016/s0140-6736(15)00474-2","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/s0140-6736(15)00474-2","archive_url":"https://space-kitty.com/papers/doi:10.1016/s0140-6736(15)00474-2","updated":null,"pmid":"26603918","pmcid":null,"openalex_id":"W2180752973","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"doi:10.1038/s41467-019-08853-3","kind":"article","title":"Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage","authors":["René S. Hendriksen","Patrick Munk","Patrick Murigu Kamau Njage","Bram A. D. van Bunnik","Luke McNally","Oksana Lukjančenko","Timo Röder","David F. Nieuwenhuijse","Susanne Karlsmose Pedersen","Jette Sejer Kjeldgaard","Rolf Sommer Kaas","Philip T. L. C. Clausen","Josef Korbinian Vogt","Pimlapas Leekitcharoenphon","Milou G.M. van de Schans","T. Zuidema","Ana Maria de Roda Husman","Simon Rasmussen","Bent Petersen","Artan Bego","Catherine A. Rees","Susan Cassar","Kris Coventry","Peter Collignon","Franz J. Allerberger"],"author_count":100,"year":2019,"published":"2019-03-08","venue":"Nature Communications","cited_by":1196,"doi":"10.1038/s41467-019-08853-3","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1038/s41467-019-08853-3","archive_url":"https://space-kitty.com/papers/doi:10.1038/s41467-019-08853-3","updated":null,"pmid":"30850636","pmcid":"PMC6408512","openalex_id":"W2921342657","pdf_url":"https://www.nature.com/articles/s41467-019-08853-3.pdf","abstract":"Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Pharmaceutical and Antibiotic Environmental Impacts"],"details":null,"provenance":"openalex+europepmc","attribution":"Abstract of \"Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage\" by René S. Hendriksen, Patrick Munk, Patrick Murigu Kamau Njage et al., https://doi.org/10.1038/s41467-019-08853-3, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/j.mib.2019.10.008","kind":"review","title":"Antibiotics: past, present and future","authors":["Hutchings MI","Truman AW","Wilkinson B"],"author_count":3,"year":2019,"published":"2019-10-01","venue":"Current opinion in microbiology","cited_by":1374,"doi":"10.1016/j.mib.2019.10.008","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.mib.2019.10.008","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.mib.2019.10.008","updated":null,"pmid":"31733401","pmcid":null,"openalex_id":null,"pdf_url":null,"abstract":"The first antibiotic, salvarsan, was deployed in 1910. In just over 100 years antibiotics have drastically changed modern medicine and extended the average human lifespan by 23 years. The discovery of penicillin in 1928 started the golden age of natural product antibiotic discovery that peaked in the mid-1950s. Since then, a gradual decline in antibiotic discovery and development and the evolution of drug resistance in many human pathogens has led to the current antimicrobial resistance crisis. Here we give an overview of the history of antibiotic discovery, the major classes of antibiotics and where they come from. We argue that the future of antibiotic discovery looks bright as new technologies such as genome mining and editing are deployed to discover new natural products with diverse bioactivities. We also report on the current state of antibiotic development, with 45 drugs currently going through the clinical trials pipeline, including several new classes with novel modes of action that are in phase 3 clinical trials. Overall, there are promising signs for antibiotic discovery, but changes in financial models are required to translate scientific advances into clinically approved antibiotics.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Antibiotics: past, present and future\" by Hutchings MI, Truman AW, Wilkinson B, https://doi.org/10.1016/j.mib.2019.10.008, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1038/s41392-022-01056-1","kind":"review","title":"Pseudomonas aeruginosa: pathogenesis, virulence factors, antibiotic resistance, interaction with host, technology advances and emerging therapeutics","authors":["Qin S","Xiao W","Zhou C","Pu Q","Deng X","Lan L","Liang H","Song X","Wu M"],"author_count":9,"year":2022,"published":"2022-06-25","venue":"Signal transduction and targeted therapy","cited_by":1047,"doi":"10.1038/s41392-022-01056-1","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1038/s41392-022-01056-1","archive_url":"https://space-kitty.com/papers/doi:10.1038/s41392-022-01056-1","updated":null,"pmid":"35752612","pmcid":"PMC9233671","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC9233671/pdf","abstract":"Pseudomonas aeruginosa (P. aeruginosa) is a Gram-negative opportunistic pathogen that infects patients with cystic fibrosis, burn wounds, immunodeficiency, chronic obstructive pulmonary disorder (COPD), cancer, and severe infection requiring ventilation, such as COVID-19. P. aeruginosa is also a widely-used model bacterium for all biological areas. In addition to continued, intense efforts in understanding bacterial pathogenesis of P. aeruginosa including virulence factors (LPS, quorum sensing, two-component systems, 6 type secretion systems, outer membrane vesicles (OMVs), CRISPR-Cas and their regulation), rapid progress has been made in further studying host-pathogen interaction, particularly host immune networks involving autophagy, inflammasome, non-coding RNAs, cGAS, etc. Furthermore, numerous technologic advances, such as bioinformatics, metabolomics, scRNA-seq, nanoparticles, drug screening, and phage therapy, have been used to improve our understanding of P. aeruginosa pathogenesis and host defense. Nevertheless, much remains to be uncovered about interactions between P. aeruginosa and host immune responses, including mechanisms of drug resistance by known or unannotated bacterial virulence factors as well as mammalian cell signaling pathways. The widespread use of antibiotics and the slow development of effective antimicrobials present daunting challenges and necessitate new theoretical and practical platforms to screen and develop mechanism-tested novel drugs to treat intractable infections, especially those caused by multi-drug resistance strains. Benefited from has advancing in research tools and technology, dissecting this pathogen's feature has entered into molecular and mechanistic details as well as dynamic and holistic views. Herein, we comprehensively review the progress and discuss the current status of P. aeruginosa biophysical traits, behaviors, virulence factors, invasive regulators, and host defense patterns against its infection, which point out new directions for future investigation and add to the design of novel and/or alternative therapeutics to combat this clinically significant pathogen.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Pseudomonas aeruginosa: pathogenesis, virulence factors, antibiotic resistance, interaction with host, technology advances and emerging therapeutics\" by Qin S, Xiao W, Zhou C et al., https://doi.org/10.1038/s41392-022-01056-1, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/s2542-5196(21)00280-1","kind":"article","title":"Global antibiotic consumption and usage in humans, 2000–18: a spatial modelling study","authors":["Annie J. Browne","Michael Give Chipeta","Georgina Haines–Woodhouse","Emmanuelle A. P. Kumaran","Bahar H. Kashef Hamadani","Sabra Zaraa","Nathaniel J Henry","Aniruddha Deshpande","Robert C. Reiner","Nicholas Day","Alan D López","Susanna Jane Dunachie","Catrin E. Moore","Andy S. Stergachis","Simon Iain Hay","Christiane Dolecek"],"author_count":16,"year":2021,"published":"2021-11-11","venue":"The Lancet Planetary Health","cited_by":865,"doi":"10.1016/s2542-5196(21)00280-1","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/s2542-5196(21)00280-1","archive_url":"https://space-kitty.com/papers/doi:10.1016/s2542-5196(21)00280-1","updated":null,"pmid":"34774223","pmcid":"PMC8654683","openalex_id":"W3211444262","pdf_url":"http://www.thelancet.com/article/S2542519621002801/pdf","abstract":"BACKGROUND: Antimicrobial resistance (AMR) is a serious threat to global public health. WHO emphasises the need for countries to monitor antibiotic consumption to combat AMR. Many low-income and middle-income countries (LMICs) lack surveillance capacity; we aimed to use multiple data sources and statistical models to estimate global antibiotic consumption. METHODS: In this spatial modelling study, we used individual-level data from household surveys to inform a Bayesian geostatistical model of antibiotic usage in children (aged <5 years) with lower respiratory tract infections in LMICs. Antibiotic consumption data were obtained from multiple sources, including IQVIA, WHO, and the European Surveillance of Antimicrobial Consumption Network (ESAC-Net). The estimates of the antibiotic usage model were used alongside sociodemographic and health covariates to inform a model of total antibiotic consumption in LMICs. This was combined with a single model of antibiotic consumption in high-income countries to produce estimates of antibiotic consumption covering 204 countries and 19 years. FINDINGS: We analysed 209 surveys done between 2000 and 2018, covering 284 045 children with lower respiratory tract infections. We identified large national and subnational variations of antibiotic usage in LMICs, with the lowest levels estimated in sub-Saharan Africa and the highest in eastern Europe and central Asia. We estimated a global antibiotic consumption rate of 14·3 (95% uncertainty interval 13·2-15·6) defined daily doses (DDD) per 1000 population per day in 2018 (40·2 [37·2-43·7] billion DDD), an increase of 46% from 9·8 (9·2-10·5) DDD per 1000 per day in 2000. We identified large spatial disparities, with antibiotic consumption rates varying from 5·0 (4·8-5·3) DDD per 1000 per day in the Philippines to 45·9 DDD per 1000 per day in Greece in 2018. Additionally, we present trends in consumption of different classes of antibiotics for selected Global Burden of Disease study regions using the IQVIA, WHO, and ESAC-net input data. We identified large increases in the consumption of fluoroquinolones and third-generation cephalosporins in North Africa and Middle East, and south Asia. INTERPRETATION: To our knowledge, this is the first study that incorporates antibiotic usage and consumption data and uses geostatistical modelling techniques to estimate antibiotic consumption for 204 countries from 2000 to 2018. Our analysis identifies both high rates of antibiotic consumption and a lack of access to antibiotics, providing a benchmark for future interventions. FUNDING: Fleming Fund, UK Department of Health and Social Care; Wellcome Trust; and Bill & Melinda Gates Foundation.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex+europepmc","attribution":"Abstract of \"Global antibiotic consumption and usage in humans, 2000–18: a spatial modelling study\" by Annie J. Browne, Michael Give Chipeta, Georgina Haines–Woodhouse et al., https://doi.org/10.1016/s2542-5196(21)00280-1, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1093/nar/gkx343","kind":"article","title":"IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets","authors":["Bertelli C","Laird MR","Williams KP","Lau BY","Hoad G","Winsor GL","Brinkman FSL"],"author_count":7,"year":2017,"published":"2017-07-01","venue":"Nucleic acids research","cited_by":1258,"doi":"10.1093/nar/gkx343","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1093/nar/gkx343","archive_url":"https://space-kitty.com/papers/doi:10.1093/nar/gkx343","updated":null,"pmid":"28472413","pmcid":"PMC5570257","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC5570257/pdf","abstract":"IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets\" by Bertelli C, Laird MR, Williams KP et al., https://doi.org/10.1093/nar/gkx343, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.3389/fmicb.2019.00539","kind":"review","title":"Emerging Strategies to Combat ESKAPE Pathogens in the Era of Antimicrobial Resistance: A Review","authors":["Mulani MS","Kamble EE","Kumkar SN","Tawre MS","Pardesi KR"],"author_count":5,"year":2019,"published":"2019-04-01","venue":"Frontiers in microbiology","cited_by":1076,"doi":"10.3389/fmicb.2019.00539","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.3389/fmicb.2019.00539","archive_url":"https://space-kitty.com/papers/doi:10.3389/fmicb.2019.00539","updated":null,"pmid":"30988669","pmcid":"PMC6452778","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC6452778/pdf","abstract":"The acronym ESKAPE includes six nosocomial pathogens that exhibit multidrug resistance and virulence: Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa , and Enterobacter spp. Persistent use of antibiotics has provoked the emergence of multidrug resistant (MDR) and extensively drug resistant (XDR) bacteria, which render even the most effective drugs ineffective. Extended spectrum β-lactamase (ESBL) and carbapenemase producing Gram negative bacteria have emerged as an important therapeutic challenge. Development of novel therapeutics to treat drug resistant infections, especially those caused by ESKAPE pathogens is the need of the hour. Alternative therapies such as use of antibiotics in combination or with adjuvants, bacteriophages, antimicrobial peptides, nanoparticles, and photodynamic light therapy are widely reported. Many reviews published till date describe these therapies with respect to the various agents used, their dosage details and mechanism of action against MDR pathogens but very few have focused specifically on ESKAPE. The objective of this review is to describe the alternative therapies reported to treat ESKAPE infections, their advantages and limitations, potential application in vivo , and status in clinical trials. The review further highlights the importance of a combinatorial approach, wherein two or more therapies are used in combination in order to overcome their individual limitations, additional studies on which are warranted, before translating them into clinical practice. These advances could possibly give an alternate solution or extend the lifetime of current antimicrobials.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Emerging Strategies to Combat ESKAPE Pathogens in the Era of Antimicrobial Resistance: A Review\" by Mulani MS, Kamble EE, Kumkar SN et al., https://doi.org/10.3389/fmicb.2019.00539, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1002/imt2.36","kind":"article","title":"Sangerbox: A comprehensive, interaction-friendly clinical bioinformatics analysis platform","authors":["Shen W","Song Z","Zhong X","Huang M","Shen D","Gao P","Qian X","Wang M","He X","Wang T","Li S","Song X"],"author_count":12,"year":2022,"published":"2022-07-08","venue":"iMeta","cited_by":953,"doi":"10.1002/imt2.36","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1002/imt2.36","archive_url":"https://space-kitty.com/papers/doi:10.1002/imt2.36","updated":null,"pmid":"38868713","pmcid":"PMC10989974","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC10989974/pdf","abstract":"In recent decades, with the continuous development of high-throughput sequencing technology, data volume in medical research has increased, at the same time, almost all clinical researchers have their own independent omics data, which provided a better condition for data mining and a deeper understanding of gene functions. However, for these large amounts of data, many common and cutting-edge effective bioinformatics research methods still cannot be widely used. This has encouraged the establishment of many analytical platforms, a portion of databases or platforms were designed to solve the special analysis needs of users, for instance, MG RAST, IMG/M, Qiita, BIGSdb, and TRAPR were developed for specific omics research, and some databases or servers provide solutions for special problems solutions. Metascape was designed to only provide functional annotations of genes as well as function enrichment analysis; BioNumerics and RidomSeqSphere+ perform multilocus sequence typing; CARD provides only antimicrobial resistance annotations. Additionally, some web services are outdated, and inefficient interaction often fails to meet the needs of researchers, such as our previous versions of the platform. Therefore, the demand to complete massive data processing tasks urgently requires a comprehensive bioinformatics analysis platform. Hence, we have developed a website platform, Sangerbox 3.0 (http://vip.sangerbox.com/), a web-based tool platform. On a user-friendly interface that also supports differential analysis, the platform provides interactive customizable analysis tools, including various kinds of correlation analyses, pathway enrichment analysis, weighted correlation network analysis, and other common tools and functions, users only need to upload their own corresponding data into Sangerbox 3.0, select required parameters, submit, and wait for the results after the task has been completed. We have also established a new interactive plotting system that allows users to adjust the parameters in the image; moreover, optimized plotting performance enables users to adjust large-capacity vector maps on the web site. At the same time, we have integrated GEO, TCGA, ICGC, and other databases and processed data in batches, greatly reducing the difficulty to obtain data and improving the efficiency of bioimformatics study for users. Finally, we also provide users with rich sources of bioinformatics analysis courses, offering a platform for researchers to share and exchange knowledge.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Sangerbox: A comprehensive, interaction-friendly clinical bioinformatics analysis platform\" by Shen W, Song Z, Zhong X et al., https://doi.org/10.1002/imt2.36, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1093/trstmh/trw048","kind":"article","title":"Antibiotic resistance is the quintessential One Health issue","authors":["Timothy P. Robinson","Dengpan Bu","Juan J. Carrique-Mas","Eric Maurice Fèvre","Marius Gilbert","Delia Grace","Simon Iain Hay","Jatesada Jiwakanon","Manish Kakkar","Samuel Kariuki","Ramanan Laxminarayan","Juan Lubroth","Ulf Magnusson","Pham Thi Ngoc","Thomas P. Van Boeckel","Mark E. J. Woolhouse"],"author_count":16,"year":2016,"published":"2016-07-01","venue":"Transactions of the Royal Society of Tropical Medicine and Hygiene","cited_by":838,"doi":"10.1093/trstmh/trw048","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1093/trstmh/trw048","archive_url":"https://space-kitty.com/papers/doi:10.1093/trstmh/trw048","updated":null,"pmid":"27475987","pmcid":null,"openalex_id":"W2498603190","pdf_url":"https://academic.oup.com/trstmh/article-pdf/110/7/377/18156081/trw048.pdf","abstract":null,"abstract_license":null,"license":"cc-by-nc","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"doi:10.1155/2016/2475067","kind":"review","title":"Mechanisms of Antimicrobial Resistance in ESKAPE Pathogens","authors":["Santajit S","Indrawattana N"],"author_count":2,"year":2016,"published":"2016-05-05","venue":"BioMed research international","cited_by":1022,"doi":"10.1155/2016/2475067","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1155/2016/2475067","archive_url":"https://space-kitty.com/papers/doi:10.1155/2016/2475067","updated":null,"pmid":"27274985","pmcid":"PMC4871955","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC4871955/pdf","abstract":"The ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) are the leading cause of nosocomial infections throughout the world. Most of them are multidrug resistant isolates, which is one of the greatest challenges in clinical practice. Multidrug resistance is amongst the top three threats to global public health and is usually caused by excessive drug usage or prescription, inappropriate use of antimicrobials, and substandard pharmaceuticals. Understanding the resistance mechanisms of these bacteria is crucial for the development of novel antimicrobial agents or other alternative tools to combat these public health challenges. Greater mechanistic understanding would also aid in the prediction of underlying or even unknown mechanisms of resistance, which could be applied to other emerging multidrug resistant pathogens. In this review, we summarize the known antimicrobial resistance mechanisms of ESKAPE pathogens.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Mechanisms of Antimicrobial Resistance in ESKAPE Pathogens\" by Santajit S, Indrawattana N, https://doi.org/10.1155/2016/2475067, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1073/pnas.2411919121","kind":"article","title":"Global trends in antibiotic consumption during 2016–2023 and future projections through 2030","authors":["Eili Y. Klein","Isabella Impalli","Suprena Poleon","Philippe Denoël","Mariateresa Cipriano","Thomas P. Van Boeckel","Simone Pecetta","David E. Bloom","Arindam Nandi"],"author_count":9,"year":2024,"published":"2024-11-18","venue":"Proceedings of the National Academy of Sciences","cited_by":453,"doi":"10.1073/pnas.2411919121","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1073/pnas.2411919121","archive_url":"https://space-kitty.com/papers/doi:10.1073/pnas.2411919121","updated":null,"pmid":"39556760","pmcid":null,"openalex_id":"W4404470077","pdf_url":"https://www.pnas.org/doi/pdf/10.1073/pnas.2411919121","abstract":"Antibiotic resistance is a global public health threat. Many factors contribute to this issue, with human antibiotic consumption being significant among them. Analyzing trends and patterns in consumption can aid in developing policies to mitigate the burden of antimicrobial resistance and global disparities in access to antibiotics. Using pharmaceutical sales data licensed from IQVIA, we estimate national-level trends in antibiotic consumption in 67 countries during 2016-2023 and analyze the effects of economic growth and the COVID-19 pandemic. Finally, we estimate global human consumption and project growth through 2030 assuming current trends. We find that estimated antibiotic consumption in reported countries increased 16.3% from 29.5 to 34.3 billion defined daily doses (DDDs) from 2016 to 2023, reflecting a 10.6% increase in the consumption rate from 13.7 to 15.2 DDDs per 1,000 inhabitants per day. Increases were most pronounced in upper-middle- and lower-middle-income countries. While the COVID-19 pandemic significantly reduced consumption globally, this was most pronounced in high-income countries, and in these countries, reductions in antibiotic use in 2020 were sharper, and lasted longer, than in other countries. By 2030, we project that, without reductions in rapidly developing nations, such as investments to improve infrastructure, particularly water and sanitation, along with improved access to vaccination, global antibiotic consumption will increase by 52.3% from an estimated 49.3 billion in 2023 to 75.1 billion DDDs.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Antibiotic Use and Resistance"],"details":null,"provenance":"openalex","attribution":"Abstract of \"Global trends in antibiotic consumption during 2016–2023 and future projections through 2030\" by Eili Y. Klein, Isabella Impalli, Suprena Poleon et al., https://doi.org/10.1073/pnas.2411919121, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."}],"next":"https://space-kitty.com/api/v1/topics/infectious-disease-amr/papers?sort=top&limit=25&offset=25"}