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Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis
Christopher J L Murray,Kevin S Ikuta,Fablina Sharara,Lucien Swetschinski,Gisela Robles Aguilar,Authia Gray,Chieh Han,Catherine Bisignano,Puja C Rao,Eve E. Wool,Sarah Charlotte Johnson,Annie J Browne,Michael Give Chipeta,Frederick Fell,Sean Hackett,Ruchi Nanavati,Sushma Nangia,Paul N. Newton,Chanpheaktra Ngoun,Amanda Novotney,Davis Nwakanma,Christina W Obiero,Antonio Olivas-Martinez,Piero Olliaro,Ednah Ooko,Edgar Ortiz-Brizuela,Anton Yariv Peleg,Carlo Perrone,Nishad Plakkal,Alfredo Ponce-de-Leon,Mathieu Raad,Tanusha Ramdin,Amy Riddell,Tamalee Roberts,Julie V. Robotham,Anna Roca,Kristina E. Rudd,Neal Russell,Jesse Schnall,John Anthony Gerard Scott,Madhusudhan Shivamallappa,Jose Sifuentes-Osornio,Nicolas Steenkeste,Andrew J. Stewardson,Temenuga Stoeva,Nidanuch Tasak,Areerat Thaiprakong,Guy Thwaites,Claudia Turner,Paul Turner,H. Rogier van Doorn,Sithembiso Velaphi,Avina Vongpradith,Huong Vu,Timothy R. Walsh,Seymour Waner,Tri Wangrangsimakul,Teresa Wozniak,Peng Zheng,Benn Sartorius,Alan D. Lopez,Andy Stergachis,Catrin E. Moore,Christiane Dolecek,Mohsen Naghavi,Georgina Haines-Woodhouse,Bahar H Kashef Hamadani,Emmanuelle A P Kumaran,Barney McManigal,Ramesh Agarwal,Samuel Akech,Samuel B. Albertson,John Amuasi,Jason Andrews,Aleksandr Y. Aravkin,David A. B. Dance,Freddie Bailey,Stephen Baker,Buddha Basnyat,Adrie Bekker,Rose G Bender,Adhisivam Bethou,Julia Bielicki,Suppawat Boonkasidecha,James Bukosia,Cristina Carvalheiro,Carlos A Castañeda-Orjuela,Vilada Chansamouth,Suman Chaurasia,Sara Chiurchiù,Fazle Chowdhury,Aislinn J Cook,Ben Cooper,Tim R Cressey,Elia Criollo-Mora,Matthew Cunningham,Saffiatou Darboe,Nicholas P. J. Day,Maia De Luca,Klara Dokova,Angela Dramowski,Susanna Dunachie,Tim Eckmanns,Daniel Eibach,Amir Emami,Nicholas A. Feasey,Natasha Fisher-Pearson,Karen Forrest,Denise Garrett,Petra Gastmeier,Ababi Zergaw Giref,Rachel Claire Greer,Vipin Gupta,Sebastian Haller,Andrea Haselbeck,Simon I. Hay,Marianne Holm,Susan Hopkins,Kenneth C Iregbu,Jan Jacobs,Daniel Jarovsky,Fatemeh Javanmardi,Meera Khorana,Niranjan Kissoon,Elsa Kobeissi,Tomislav Kostyanev,Fiorella Krapp,Ralf Krumkamp,Ajay Kumar,Hmwe H Kyu,Cherry Lim,Direk Limmathurotsakul,Michael James Loftus,Miles Lunn,Jianing Ma,Neema Mturi,Tatiana Munera-Huertas,Patrick Musicha,Marisa Marcia Mussi-Pinhata,Tomoka Nakamura
<h2>Summary</h2><h3>Background</h3> 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. <h3>Methods</h3> 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. <h3>Findings</h3> 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 (<i>Escherichia coli</i>, followed by <i>Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii</i>, and <i>Pseudomonas aeruginosa</i>) 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 <i>S aureus</i>, 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 <i>E coli, carbapenem-resistant</i> A baumannii, <i>fluoroquinolone-resistant E coli</i>, carbapenem-resistant <i>K pneumoniae</i>, and third-generation cephalosporin-resistant <i>K pneumoniae</i>. <h3>Interpretation</h3> 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. <h3>Funding</h3> Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
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Cited 403 times
Restricting the use of antibiotics in food-producing animals and its associations with antibiotic resistance in food-producing animals and human beings: a systematic review and meta-analysis
Antibiotic use in human medicine, veterinary medicine, and agriculture has been linked to the rise of antibiotic resistance globally. We did a systematic review and meta-analysis to summarise the effect that interventions to reduce antibiotic use in food-producing animals have on the presence of antibiotic-resistant bacteria in animals and in humans.On July 14, 2016, we searched electronic databases (Agricola, AGRIS, BIOSIS Previews, CAB Abstracts, MEDLINE, Embase, Global Index Medicus, ProQuest Dissertations, Science Citation Index) and the grey literature. The search was updated on Jan 27, 2017. Inclusion criteria were original studies that reported on interventions to reduce antibiotic use in food-producing animals and compared presence of antibiotic-resistant bacteria between intervention and comparator groups in animals or in human beings. We extracted data from included studies and did meta-analyses using random effects models. The main outcome assessed was the risk difference in the proportion of antibiotic-resistant bacteria.A total of 181 studies met inclusion criteria. Of these, 179 (99%) described antibiotic resistance outcomes in animals, and 81 (45%) of these studies were included in the meta-analysis. 21 studies described antibiotic resistance outcomes in humans, and 13 (62%) of these studies were included in the meta-analysis. The pooled absolute risk reduction of the prevalence of antibiotic resistance in animals with interventions that restricted antibiotic use commonly ranged between 10 and 15% (total range 0-39), depending on the antibiotic class, sample type, and bacteria under assessment. Similarly, in the human studies, the pooled prevalence of antibiotic resistance reported was 24% lower in the intervention groups compared with control groups, with a stronger association seen for humans with direct contact with food-producing animals.Interventions that restrict antibiotic use in food-producing animals are associated with a reduction in the presence of antibiotic-resistant bacteria in these animals. A smaller body of evidence suggests a similar association in the studied human populations, particularly those with direct exposure to food-producing animals. The implications for the general human population are less clear, given the low number of studies. The overall findings have directly informed the development of WHO guidelines on the use of antibiotics in food-producing animals.World Health Organization.
¤ Open Access
Cited 151 times
The role of vaccines in preventing bacterial antimicrobial resistance
Antimicrobial resistance (AMR) and the associated morbidity and mortality due to bacterial pathogens have been increasing globally to alarming levels. The World Health Organization (WHO) has called for global action on AMR, supported worldwide by governments, health ministries and health agencies. Many potential solutions to stem AMR are being discussed and implemented. These include increases in antimicrobial stewardship, investment in research and development to design new classes of antibiotics, and reduction of antibiotic use in rearing of livestock. However, vaccines as tools to reduce AMR have historically been under-recognized in these discussions, even though their effectiveness in reducing disease and AMR is well documented. This review article seeks to highlight the value of vaccines as an additional modality to combat AMR globally, using select examples. It also will provide perspectives on how vaccines could be more effectively used in this effort.
¤ Open Access
Cited 98 times
Clinical bacteriology in low-resource settings: today's solutions
Low-resource settings are disproportionately burdened by infectious diseases and antimicrobial resistance. Good quality clinical bacteriology through a well functioning reference laboratory network is necessary for effective resistance control, but low-resource settings face infrastructural, technical, and behavioural challenges in the implementation of clinical bacteriology. In this Personal View, we explore what constitutes successful implementation of clinical bacteriology in low-resource settings and describe a framework for implementation that is suitable for general referral hospitals in low-income and middle-income countries with a moderate infrastructure. Most microbiological techniques and equipment are not developed for the specific needs of such settings. Pending the arrival of a new generation diagnostics for these settings, we suggest focus on improving, adapting, and implementing conventional, culture-based techniques. Priorities in low-resource settings include harmonised, quality assured, and tropicalised equipment, consumables, and techniques, and rationalised bacterial identification and testing for antimicrobial resistance. Diagnostics should be integrated into clinical care and patient management; clinically relevant specimens must be appropriately selected and prioritised. Open-access training materials and information management tools should be developed. Also important is the need for onsite validation and field adoption of diagnostics in low-resource settings, with considerable shortening of the time between development and implementation of diagnostics. We argue that the implementation of clinical bacteriology in low-resource settings improves patient management, provides valuable surveillance for local antibiotic treatment guidelines and national policies, and supports containment of antimicrobial resistance and the prevention and control of hospital-acquired infections.
¤ Open Access
Cited 36 times
An inventory of supranational antimicrobial resistance surveillance networks involving low- and middle-income countries since 2000
Low- and middle-income countries (LMICs) shoulder the bulk of the global burden of infectious diseases and drug resistance. We searched for supranational networks performing antimicrobial resistance (AMR) surveillance in LMICs and assessed their organization, methodology, impacts and challenges. Since 2000, 72 supranational networks for AMR surveillance in bacteria, fungi, HIV, TB and malaria have been created that have involved LMICs, of which 34 are ongoing. The median (range) duration of the networks was 6 years (1-70) and the number of LMICs included was 8 (1-67). Networks were categorized as WHO/governmental (n = 26), academic (n = 24) or pharma initiated (n = 22). Funding sources varied, with 30 networks receiving public or WHO funding, 25 corporate, 13 trust or foundation, and 4 funded from more than one source. The leading global programmes for drug resistance surveillance in TB, malaria and HIV gather data in LMICs through periodic active surveillance efforts or combined active and passive approaches. The biggest challenges faced by these networks has been achieving high coverage across LMICs and complying with the recommended frequency of reporting. Obtaining high quality, representative surveillance data in LMICs is challenging. Antibiotic resistance surveillance requires a level of laboratory infrastructure and training that is not widely available in LMICs. The nascent Global Antimicrobial Resistance Surveillance System (GLASS) aims to build up passive surveillance in all member states. Past experience suggests complementary active approaches may be needed in many LMICs if representative, clinically relevant, meaningful data are to be obtained. Maintaining an up-to-date registry of networks would promote a more coordinated approach to surveillance.
¤ Open Access
Cited 475 times
Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016
A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016.Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita.In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8-98·1) in Iceland, followed by 96·6 (94·9-97·9) in Norway and 96·1 (94·5-97·3) in the Netherlands, to values as low as 18·6 (13·1-24·4) in the Central African Republic, 19·0 (14·3-23·7) in Somalia, and 23·4 (20·2-26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1-93·6) in Beijing to 48·0 (43·4-53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6-68·8) in Goa to 34·0 (30·3-38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries.GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view-and subsequent provision-of quality health care for all populations.Bill & Melinda Gates Foundation.
¤ Open Access
Cited 90 times
Measuring and mapping the global burden of antimicrobial resistance
The increasing number and global distribution of pathogens resistant to antimicrobial drugs is potentially one of the greatest threats to global health, leading to health crises arising from infections that were once easy to treat. Infections resistant to antimicrobial treatment frequently result in longer hospital stays, higher medical costs, and increased mortality. Despite the long-standing recognition of antimicrobial resistance (AMR) across many settings, there is surprisingly poor information about its geographical distribution over time and trends in its population prevalence and incidence. This makes reliable assessments of the health burden attributable to AMR difficult, weakening the evidence base to drive forward research and policy agendas to combat AMR. The inclusion of mortality and morbidity data related to drug-resistant infections into the annual Global Burden of Disease Study should help fill this policy void.
¤ Open Access
Cited 254 times
Estimating the burden of antimicrobial resistance: a systematic literature review
Accurate estimates of the burden of antimicrobial resistance (AMR) are needed to establish the magnitude of this global threat in terms of both health and cost, and to paramaterise cost-effectiveness evaluations of interventions aiming to tackle the problem. This review aimed to establish the alternative methodologies used in estimating AMR burden in order to appraise the current evidence base.MEDLINE, EMBASE, Scopus, EconLit, PubMed and grey literature were searched. English language studies evaluating the impact of AMR (from any microbe) on patient, payer/provider and economic burden published between January 2013 and December 2015 were included. Independent screening of title/abstracts followed by full texts was performed using pre-specified criteria. A study quality score (from zero to one) was derived using Newcastle-Ottawa and Philips checklists. Extracted study data were used to compare study method and resulting burden estimate, according to perspective. Monetary costs were converted into 2013 USD.Out of 5187 unique retrievals, 214 studies were included. One hundred eighty-seven studies estimated patient health, 75 studies estimated payer/provider and 11 studies estimated economic burden. 64% of included studies were single centre. The majority of studies estimating patient or provider/payer burden used regression techniques. 48% of studies estimating mortality burden found a significant impact from resistance, excess healthcare system costs ranged from non-significance to $1 billion per year, whilst economic burden ranged from $21,832 per case to over $3 trillion in GDP loss. Median quality scores (interquartile range) for patient, payer/provider and economic burden studies were 0.67 (0.56-0.67), 0.56 (0.46-0.67) and 0.53 (0.44-0.60) respectively.This study highlights what methodological assumptions and biases can occur dependent on chosen outcome and perspective. Currently, there is considerable variability in burden estimates, which can lead in-turn to inaccurate intervention evaluations and poor policy/investment decisions. Future research should utilise the recommendations presented in this review.This systematic review is registered with PROSPERO (PROSPERO CRD42016037510).
¤ Open Access
Cited 68 times
Estimating the number of infections caused by antibiotic-resistant Escherichia coli and Klebsiella pneumoniae in 2014: a modelling study
The number of infections caused by resistant organisms is largely unknown. We estimated the number of infections worldwide that are caused by the WHO priority pathogens third-generation cephalosporin-resistant and carbapenem-resistant Escherichia coli and Klebsiella pneumoniae.We calculated a uniform weighted mean incidence of serious infections caused by antibiotic-susceptible E coli and K pneumoniae using data from 17 countries. Using this uniform incidence, as well as population sizes and country-specific resistance levels, we estimated the number of infections caused by third-generation cephalosporin-resistant and carbapenem-resistant E coli and K pneumoniae in 193 countries in 2014. We also calculated interval estimates derived from changing the fixed incidence of susceptible infections to 1 SD below and above the weighted mean. We compared an additive model with combination models in which resistant infections were replaced by susceptible infections. We distinguished between higher-certainty regions (those with good-quality data sources for resistance levels and resistance ≤30%), moderate-certainty regions (those with good-quality data sources for resistance levels and including some countries with resistance >30%), and low-certainty regions (those in which good-quality data sources for resistance levels were unavailable for countries comprising at least 20% of the region's population, regardless of resistance level).Using the additive model, we estimated that third-generation cephalosporin-resistant E coli and K pneumoniae caused 6·4 million (interval estimate 3·5-9·2) bloodstream infections and 50·1 million (27·5-72·8) serious infections in 2014; estimates were 5·5 million (3·0-7·9) bloodstream infections and 43·1 million (23·6-62·2) serious infections in the 25% replacement model, 4·6 million (2·5-6·6) bloodstream infections and 36·0 million (19·7-52·2) serious infections in the 50% replacement model, and 3·7 million (2·0-5·3) bloodstream infections and 28·9 million (15·8-41·9) serious infections in the 75% replacement model. Carbapenem-resistant strains caused 0·5 million (0·3-0·7) bloodstream infections and 3·1 million (1·8-4·5) serious infections based on the additive model, 0·5 million (0·3-0·7) bloodstream infections and 3·0 million (1·7-4·3) serious infections based on the 25% replacement model, 0·4 million (0·2-0·6) bloodstream infections and 2·8 million (1·6-4·1) serious infections based on the 50% replacement model, and 0·4 million (0·2-0·6) bloodstream infections and 2·7 million (1·5-3·8) serious infections based on the 75% replacement model.To our knowledge, this study is the first to report estimates of the global number of infections caused by antibiotic-resistant priority pathogens. Uncertainty stems from scant data on resistance levels from low-income and middle-income countries and insufficient knowledge regarding resistance dynamics when resistance is high.Innovative Medicines Initiative.
¤ Open Access
Cited 307 times
Anthropological and socioeconomic factors contributing to global antimicrobial resistance: a univariate and multivariable analysis
Background Understanding of the factors driving global antimicrobial resistance is limited. We analysed antimicrobial resistance and antibiotic consumption worldwide versus many potential contributing factors. Methods Using three sources of data (ResistanceMap, the WHO 2014 report on antimicrobial resistance, and contemporary publications), we created two global indices of antimicrobial resistance for 103 countries using data from 2008 to 2014: Escherichia coli resistance—the global average prevalence of E coli bacteria that were resistant to third-generation cephalosporins and fluoroquinolones, and aggregate resistance—the combined average prevalence of E coli and Klebsiella spp resistant to third-generation cephalosporins, fluoroquinolones, and carbapenems, and meticillin-resistant Staphylococcus aureus. Antibiotic consumption data were obtained from the IQVIA MIDAS database. The World Bank DataBank was used to obtain data for governance, education, gross domestic product (GDP) per capita, health-care spending, and community infrastructure (eg, sanitation). A corruption index was derived using data from Transparency International. We examined associations between antimicrobial resistance and potential contributing factors using simple correlation for a univariate analysis and a logistic regression model for a multivariable analysis. Findings In the univariate analysis, GDP per capita, education, infrastructure, public health-care spending, and antibiotic consumption were all inversely correlated with the two antimicrobial resistance indices, whereas higher temperatures, poorer governance, and the ratio of private to public health expenditure were positively correlated. In the multivariable regression analysis (confined to the 73 countries for which antibiotic consumption data were available) considering the effect of changes in indices on E coli resistance (R2 0·54) and aggregate resistance (R2 0·75), better infrastructure (p=0·014 and p=0·0052) and better governance (p=0·025 and p<0·0001) were associated with lower antimicrobial resistance indices. Antibiotic consumption was not significantly associated with either antimicrobial resistance index in the multivariable analysis (p=0·64 and p=0·070). Interpretation Reduction of antibiotic consumption will not be sufficient to control antimicrobial resistance because contagion—the spread of resistant strains and resistance genes—seems to be the dominant contributing factor. Improving sanitation, increasing access to clean water, and ensuring good governance, as well as increasing public health-care expenditure and better regulating the private health sector are all necessary to reduce global antimicrobial resistance.
¤ Open Access
Cited 1,347 times
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
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).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.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.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.European Centre for Disease Prevention and Control.
¤ Open Access
Cited 96 times
Impact of existing vaccines in reducing antibiotic resistance: Primary and secondary effects
Vaccines impact antibiotic-resistant infections in two ways: through a direct reduction in the organisms and strains carrying resistant genes that are specifically targeted by the vaccine and also via a secondary effect through a reduction in febrile illnesses that often lead to the use of antibiotics. We review here the impact of pneumococcal conjugate vaccines (PCVs) on the prevalence of antibiotic-resistant disease and antibiotic usage as an example of the direct effect of vaccines on antibiotic resistance and the impact of influenza vaccination on antibiotic usage as an example of a secondary effect. A prelicensure study of a PCV in Africa demonstrated 67% fewer penicillin-resistant invasive disease episodes in the PCV group compared with controls. Similar studies in the United States and Europe demonstrated reductions in antibiotic use consistent with the vaccines’ impact on the risk of otitis media infections in children. Postlicensure reductions in the circulation of antibiotic-resistant strains targeted by the vaccines have been dramatic, with virtual elimination of these strains in children following vaccine introduction. In terms of a secondary effect, following influenza vaccination reductions of 13–50% have been observed in the use of antibiotics by individuals receiving influenza vaccine compared with controls. With the demonstrated effectiveness of vaccination programs in impacting the risk of antibiotic-resistant infections and the increasing threat to public health that these infections represent, more attention needs to be given to development and utilization of vaccines to address antibiotic resistance.
¤ Open Access
Cited 373 times
Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage
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.
¤ Open Access
Cited 79 times
Understanding and Addressing CLSI Breakpoint Revisions: a Primer for Clinical Laboratories
The Clinical and Laboratory Standards Institute (CLSI) has revised several breakpoints since 2010 for bacteria that grow aerobically. In 2019, these revisions include changes to the ciprofloxacin and levofloxacin breakpoints for the Enterobacteriaceae and Pseudomonas aeruginosa , daptomycin breakpoints for Enterococcus spp., and ceftaroline breakpoints for Staphylococcus aureus .
¤ Open Access
Cited 55 times
Improving the estimation of the global burden of antimicrobial resistant infections
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.
¤ Open Access
Cited 379 times
Global trends in antimicrobial resistance in animals in low- and middle-income countries
Livestock antibiotic resistance Most antibiotic use is for livestock, and it is growing with the increase in global demand for meat. It is unclear what the increase in demand for antibiotics means for the occurrence of drug resistance in animals and risk to humans. Van Boeckel et al. describe the global burden of antimicrobial resistance in animals on the basis of systematic reviews over the past 20 years (see the Perspective by Moore). There is a clear increase in the number of resistant bacterial strains occurring in chickens and pigs. The current study provides a much-needed baseline model for low- and middle-income countries and provides a “one health” perspective to which future data can be added. Science , this issue p. eaaw1944 ; see also p. 1251
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Cited 1,595 times
Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study
Sepsis is life-threatening organ dysfunction due to a dysregulated host response to infection. It is considered a major cause of health loss, but data for the global burden of sepsis are limited. As a syndrome caused by underlying infection, sepsis is not part of standard Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) estimates. Accurate estimates are important to inform and monitor health policy interventions, allocation of resources, and clinical treatment initiatives. We estimated the global, regional, and national incidence of sepsis and mortality from this disorder using data from GBD 2017.We used multiple cause-of-death data from 109 million individual death records to calculate mortality related to sepsis among each of the 282 underlying causes of death in GBD 2017. The percentage of sepsis-related deaths by underlying GBD cause in each location worldwide was modelled using mixed-effects linear regression. Sepsis-related mortality for each age group, sex, location, GBD cause, and year (1990-2017) was estimated by applying modelled cause-specific fractions to GBD 2017 cause-of-death estimates. We used data for 8·7 million individual hospital records to calculate in-hospital sepsis-associated case-fatality, stratified by underlying GBD cause. In-hospital sepsis-associated case-fatality was modelled for each location using linear regression, and sepsis incidence was estimated by applying modelled case-fatality to sepsis-related mortality estimates.In 2017, an estimated 48·9 million (95% uncertainty interval [UI] 38·9-62·9) incident cases of sepsis were recorded worldwide and 11·0 million (10·1-12·0) sepsis-related deaths were reported, representing 19·7% (18·2-21·4) of all global deaths. Age-standardised sepsis incidence fell by 37·0% (95% UI 11·8-54·5) and mortality decreased by 52·8% (47·7-57·5) from 1990 to 2017. Sepsis incidence and mortality varied substantially across regions, with the highest burden in sub-Saharan Africa, Oceania, south Asia, east Asia, and southeast Asia.Despite declining age-standardised incidence and mortality, sepsis remains a major cause of health loss worldwide and has an especially high health-related burden in sub-Saharan Africa.The Bill & Melinda Gates Foundation, the National Institutes of Health, the University of Pittsburgh, the British Columbia Children's Hospital Foundation, the Wellcome Trust, and the Fleming Fund.
¤ Open Access
Cited 14 times
Antibiotic use and hygiene interact to influence the distribution of antimicrobial-resistant bacteria in low-income communities in Guatemala
Abstract To examine the effects of poor sanitation and hygiene on the prevalence of antimicrobial-resistant bacteria, we surveyed households in two rural and two urban communities in Guatemala (N = 196 randomly selected households). One adult (≥ 18-years old) and, when available, one child (≤ 5 years-old) provided a stool sample. Up to 48 presumptive Escherichia coli isolates were collected from each stool sample (n = 21,256 total) and were subjected to breakpoint assays for ten antibiotics. Mixed-effects logistic models were used to identify potential factors influencing the likelihood of harboring antibiotic-resistant bacteria. For nine out of ten antibiotics, the odds of detecting resistant bacteria decreased by ~ 32% (odds ratios, OR 0.53–0.8, P < 0.001) for every unit of improvement of a hygiene scale. Hygiene differences between households had a greater impact on prevalence compared to antibiotic use differences. The likelihood of detecting resistant isolates was lower for five antibiotics among households that boiled raw milk before consumption (OR 0.31–0.69), and higher for nine antibiotics in urban households (OR > 1.89–9.6). Poor hygiene conditions likely obscure effects of individual antibiotic use, presumably due to enhanced microbial transmission. Consequently, efforts to improve antibiotic stewardship should be coupled with improving hygiene conditions.
¤ Open Access
Cited 13 times
Burden of Antimicrobial Resistance: Compared to What?
The increased focus on the public health burden of antimicrobial resistance (AMR) raises conceptual challenges, such as determining how much harm multidrug-resistant organisms do compared to what, or how to establish the burden. Here, we present a counterfactual framework and provide guidance to harmonize methodologies and optimize study quality. In AMR-burden studies, 2 counterfactual approaches have been applied: the harm of drug-resistant infections relative to the harm of the same drug-susceptible infections (the susceptible-infection counterfactual); and the total harm of drug-resistant infections relative to a situation where such infections were prevented (the no-infection counterfactual). We propose to use an intervention-based causal approach to determine the most appropriate counterfactual. We show that intervention scenarios, species of interest, and types of infections influence the choice of counterfactual. We recommend using purpose-designed cohort studies to apply this counterfactual framework, whereby the selection of cohorts (patients with drug-resistant, drug-susceptible infections, and those with no infection) should be based on matching on time to infection through exposure density sampling to avoid biased estimates. Application of survival methods is preferred, considering competing events. We conclude by advocating estimation of the burden of AMR by using the no-infection and susceptible-infection counterfactuals. The resulting numbers will provide policy-relevant information about the upper and lower bound of future interventions designed to control AMR. The counterfactuals should be applied in cohort studies, whereby selection of the unexposed cohorts should be based on exposure density sampling, applying methods avoiding time-dependent bias and confounding.
¤ Open Access
Cited 3,265 times
Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries.GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution.Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990-2010 time period, with the greatest annualised rate of decline occurring in the 0-9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10-24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10-24 years were also in the top ten in the 25-49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50-74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI.As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve.Bill & Melinda Gates Foundation.
¤ Open Access
Cited 1,780 times
Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease.GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk-outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk-outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk-outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden.The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51-12·1) deaths (19·2% [16·9-21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12-9·31) deaths (15·4% [14·6-16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253-350) DALYs (11·6% [10·3-13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0-9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10-24 years, alcohol use for those aged 25-49 years, and high systolic blood pressure for those aged 50-74 years and 75 years and older.Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public.Bill & Melinda Gates Foundation.
¤ Open Access
Cited 19 times
The challenges of estimating the human global burden of disease of antimicrobial resistant bacteria
• Current estimates of the global burden of AMR are limited by lack of data. • Choice of methodological approach for calculating AMR burden impacts on estimates. • Patient-focussed surveillance of drug-resistant infection is a priority. • International collaboration to build sustainable AMR surveillance is essential. Estimating the contribution of antimicrobial resistance (AMR) to global mortality and healthcare costs enables evaluation of interventions, informs policy decisions on resource allocation, and drives research priorities. However assembling the high quality, patient-level data required for global estimates is challenging. Capacity for accurate microbiology culture and antimicrobial susceptibility testing is woefully neglected in low and middle-income countries, and further surveillance and research on community antimicrobial usage, bias in blood culture sampling, and the contribution of co-morbidities such as diabetes is essential. International collaboration between governments, policy makers, academics, microbiologists, front-line clinicians, veterinarians, the food and agriculture industry and the public is critical to understand and tackle AMR.
¤ Open Access
Cited 13 times
Filling the gaps in the global prevalence map of clinical antimicrobial resistance
Significance While antimicrobial resistance is an urgent global problem, substantial clinical surveillance gaps exist in low- and middle-income countries (LMICs). We fill the gaps in the global prevalence map of nine pathogens, resistant to 19 (classes of) antibiotics (representing 75 unique combinations), based on the robust correlation between countries’ socioeconomic profiles and extensive surveillance data. Our estimates for carbapenem-resistant Acinetobacter baumannii and third-generation cephalosporin-resistant Escherichia coli benefit over 2.2 billion people in countries with currently insufficient diagnostic capacity. We show how structural surveillance investments can be prioritized based on the magnitude of prevalence estimated (Middle Eastern countries), the relative prevalence increase over 1998 to 2017 (sub-Saharan African countries), and the improvement of model performance achievable with new surveillance data (Pacific Islands).
¤ Open Access
Cited 15 times
Barriers to implementing antimicrobial stewardship programs in three low- and middle-income country tertiary care settings: findings from a multi-site qualitative study
Antimicrobial resistance has been named as one of the top ten threats to public health in the world. Hospital-based antimicrobial stewardship programs (ASPs) can help reduce antimicrobial resistance. The purpose of this study was to determine perceived barriers to the development and implementation of ASPs in tertiary care centers in three low- and middle-income countries (LMICs).Interviews were conducted with 45 physicians at tertiary care hospitals in Sri Lanka (n = 22), Kenya (12), and Tanzania (11). Interviews assessed knowledge of antimicrobial resistance and ASPs, current antimicrobial prescribing practices, access to diagnostics that inform antimicrobial use, receptiveness to ASPs, and perceived barriers to implementing ASPs. Two independent reviewers coded the interviews using principles of applied thematic analysis, and comparisons of themes were made across the three sites.Barriers to improving antimicrobial prescribing included prohibitively expensive antimicrobials, limited antimicrobial availability, resistance to changing current practices regarding antimicrobial prescribing, and limited diagnostic capabilities. The most frequent of these barriers in all three locations was limited drug availability. Many physicians in all three sites had not heard of ASPs before the interviews. Improved education was a suggested component of ASPs at all three sites. The creation of guidelines was also recommended, without prompting, by interviewees at all three sites. Although most participants felt microbiological results were helpful in tailoring antibiotic courses, some expressed distrust of laboratory culture results. Biomarkers like erythrocyte sedimentation rate and c-reactive protein were not felt to be specific enough to guide antimicrobial therapy. Despite limited or no prior knowledge of ASPs, most interviewees were receptive to implementing protocols that would include documentation and consultation with ASPs regarding antimicrobial prescribing.Our study highlighted several important barriers to implementing ASPs that were shared between three tertiary care centers in LMICs. Improving drug availability, enhancing availability of and trust in microbiologic data, creating local guidelines, and providing education to physicians regarding antimicrobial prescribing are important steps that could be taken by ASPs in these facilities.
¤ Open Access
Cited 63 times
Global antibiotic consumption and usage in humans, 2000–18: a spatial modelling study
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.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.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.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.Fleming Fund, UK Department of Health and Social Care; Wellcome Trust; and Bill & Melinda Gates Foundation.
“Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis” is a paper by Christopher J L Murray Kevin S Ikuta Fablina Sharara Lucien Swetschinski Gisela Robles Aguilar Authia Gray Chieh Han Catherine Bisignano Puja C Rao Eve E. Wool Sarah Charlotte Johnson Annie J Browne Michael Give Chipeta Frederick Fell Sean Hackett Ruchi Nanavati Sushma Nangia Paul N. Newton Chanpheaktra Ngoun Amanda Novotney Davis Nwakanma Christina W Obiero Antonio Olivas-Martinez Piero Olliaro Ednah Ooko Edgar Ortiz-Brizuela Anton Yariv Peleg Carlo Perrone Nishad Plakkal Alfredo Ponce-de-Leon Mathieu Raad Tanusha Ramdin Amy Riddell Tamalee Roberts Julie V. Robotham Anna Roca Kristina E. Rudd Neal Russell Jesse Schnall John Anthony Gerard Scott Madhusudhan Shivamallappa Jose Sifuentes-Osornio Nicolas Steenkeste Andrew J. Stewardson Temenuga Stoeva Nidanuch Tasak Areerat Thaiprakong Guy Thwaites Claudia Turner Paul Turner H. Rogier van Doorn Sithembiso Velaphi Avina Vongpradith Huong Vu Timothy R. Walsh Seymour Waner Tri Wangrangsimakul Teresa Wozniak Peng Zheng Benn Sartorius Alan D. Lopez Andy Stergachis Catrin E. Moore Christiane Dolecek Mohsen Naghavi Georgina Haines-Woodhouse Bahar H Kashef Hamadani Emmanuelle A P Kumaran Barney McManigal Ramesh Agarwal Samuel Akech Samuel B. Albertson John Amuasi Jason Andrews Aleksandr Y. Aravkin David A. B. Dance Freddie Bailey Stephen Baker Buddha Basnyat Adrie Bekker Rose G Bender Adhisivam Bethou Julia Bielicki Suppawat Boonkasidecha James Bukosia Cristina Carvalheiro Carlos A Castañeda-Orjuela Vilada Chansamouth Suman Chaurasia Sara Chiurchiù Fazle Chowdhury Aislinn J Cook Ben Cooper Tim R Cressey Elia Criollo-Mora Matthew Cunningham Saffiatou Darboe Nicholas P. J. Day Maia De Luca Klara Dokova Angela Dramowski Susanna Dunachie Tim Eckmanns Daniel Eibach Amir Emami Nicholas A. Feasey Natasha Fisher-Pearson Karen Forrest Denise Garrett Petra Gastmeier Ababi Zergaw Giref Rachel Claire Greer Vipin Gupta Sebastian Haller Andrea Haselbeck Simon I. Hay Marianne Holm Susan Hopkins Kenneth C Iregbu Jan Jacobs Daniel Jarovsky Fatemeh Javanmardi Meera Khorana Niranjan Kissoon Elsa Kobeissi Tomislav Kostyanev Fiorella Krapp Ralf Krumkamp Ajay Kumar Hmwe H Kyu Cherry Lim Direk Limmathurotsakul Michael James Loftus Miles Lunn Jianing Ma Neema Mturi Tatiana Munera-Huertas Patrick Musicha Marisa Marcia Mussi-Pinhata Tomoka Nakamura published in the journal The Lancet in 2022. It was published by Elsevier. It has an Open Access status of “hybrid”. You can read and download a PDF Full Text of this paper here.