Global burden of bacterial antimicrobial resistance in 2019

A systematic analysis

Bibliographic Data

ID23367190
AuthorsChristopher J L Murray (0000-0002-4930-9450), Kevin S Ikuta (0000-0002-3149-3907), Fablina Sharara, Lucien R Swetschinski, Lucien Swetschinski, Gisela Robles Aguilar (0000-0002-5472-8748), Authia Gray, Authia P Gray, Chieh Han, Catherine Bisignano, Puja C Rao, Puja Rao, Eve E Wool (0000-0003-2107-4538), Eve Wool, Sarah C Johnson (0000-0002-4640-4209), Annie J Browne, Michael G Chipeta (0000-0001-5882-9936), Frederick Fell, Sean Hackett (0000-0003-1048-8583), Georgina Haines-Woodhouse, Georgina Haines–Woodhouse, Bahar H Kashef Hamadani, Emmanuelle A P Kumaran (0000-0003-3074-0125), Barney McManigal, Sureeruk Achalapong, Ramesh Agarwal (0000-0001-6208-3057), Samuel Akech (0000-0001-5126-1225), Samuel B Albertson, Samuel Albertson, John Amuasi (0000-0002-8640-2662), Jason R Andrews (0000-0002-5967-251X), Jason Andrews, Aleskandr Aravkin, Elizabeth Ashley, Elizabeth A Ashley (0000-0002-7620-4822), François-Xavier Babin, Freddie Bailey (0000-0002-7206-3081), Stephen Baker (0000-0003-1308-5755), Buddha Basnyat (0000-0002-1125-2743), Adrie Bekker (0000-0003-3836-3432), Rose Bender (0000-0001-8169-0039), James A Berkley (0000-0002-1236-849X), Adhisivam Bethou, B Adhisivam (0000-0002-9808-2926), Julia Bielicki (0000-0002-3902-5489), Suppawat Boonkasidecha (0000-0001-6193-6492), James Bukosia, Cristina Carvalheiro, Cristina Gardonyi Carvalheiro (0000-0003-1248-472X), Carlos Castañeda Orjuela (0000-0002-8735-6223), Carlos Castañeda-Orjuela, Vilada Chansamouth (0000-0003-3049-784X), Suman Chaurasia (0000-0002-3871-5322), Sara Chiurchiù (0000-0003-1792-3584), Fazle Chowdhury, Fazle Rabbi Chowdhury (0000-0001-9579-0030), Rafai Clotaire Donatien, Aislinn Cook (0000-0002-9189-7815), Aislinn J Cook, Ben Cooper, Ben S Cooper (0000-0002-9445-7217), Tim R Cressey (0000-0002-8106-0974), Elia Criollo-Mora, Matthew Cunningham (0000-0002-7382-5260), Saffiatou Darboe (0000-0002-4711-3307), Nicholas Day (0000-0003-2309-1171), Nicholas P J Day, Maia De Luca (0000-0001-7549-3514), Клара Докова (0000-0002-0164-4903), Klara Dokova, Angela Dramowski (0000-0002-0161-9791), Susanna J Dunachie, Susanna Dunachie (0000-0001-5665-6293), Thuy Duong Bich, Tim Eckmanns (0000-0002-4022-4944), Daniel Eibach (0000-0002-6672-8147), Amir Emami (0000-0002-4510-1820), Nicholas Feasey (0000-0003-4041-1405), Natasha Fisher-Pearson, Karen Forrest (0000-0002-9484-0830), Coralith García (0000-0002-7933-1843), David Garrett (0000-0001-6411-3459), Denise Garrett, Petra Gastmeier (0000-0001-5520-4287), Ababi Zergaw Giref, Raquel C Greer (0000-0001-9327-0234), Rachel Claire Greer, Vikas Gupta (0000-0003-0975-336X), Sebastian Haller (0000-0001-8242-711X), Andrea Haselbeck (0000-0003-1740-0011), Simon I Hay (0000-0002-0611-7272), Marianne Holm (0000-0002-0747-4116), Shakita Hopkins (0000-0001-5179-5702), Susan Hopkins (0000-0003-1781-2382), Yingfen Hsia (0000-0002-7955-852X), Kenneth C Iregbu, Kenneth Iregbu (0000-0003-4780-0497), Jan Jacobs (0000-0002-8657-6777), Daniel Jarovsky (0000-0002-4825-7396), Fatemeh Javanmardi (0000-0001-8841-0861), Adam Jenney (0000-0002-5237-2506), Adam W J Jenney, Meera Khorana (0000-0001-7187-1338), Suwimon Khusuwan (0000-0001-6975-057X), Niranjan Kissoon (0000-0001-8847-9973), Elsa Kobeissi (0000-0003-2180-4481), Tomislav Kostyanev (0000-0002-1259-4876), Fiorella Krapp (0000-0002-8404-2827), Ralf Krumkamp (0000-0003-3053-476X), Ajay Kumar (0000-0003-1762-6627), Ajay M V Kumar (0000-0003-1011-8531), Hmwe Hmwe Kyu (0000-0002-0449-5691), Cherry Lim (0000-0003-2555-6980), Kruy Lim, Direk Limmathurotsakul (0000-0001-7240-5320), Michael J Loftus (0000-0001-6672-0578), Miles Lunn, Jianing Ma (0000-0002-6857-0718), Anand Manoharan (0000-0001-9130-8016), Florian Marks (0000-0002-6043-7170), Jürgen May (0000-0002-3252-6336), Juergen May (0000-0001-7831-8420), Mayfong Mayxay (0000-0002-6056-4516), Neema Mturi (0000-0002-6585-2074), Tatiana Munera-Huertas, Patrick Musicha, Lilian A Musila, Marisa Márcia Mussi-Pinhata, Ravi Narayan Naidu, Tomoka Nakamura (0000-0002-2623-2075), Ruchi Nanavati, Sushma Nangia (0000-0002-7664-2259), Paul Newton (0000-0001-5187-5665), Chanpheaktra Ngoun, Amanda Novotney (0000-0002-3615-9713), Davis Nwakanma, Christina W Obiero (0000-0002-9321-0183), Theresa J Ochoa (0000-0002-3227-3906), Antonio Olivas-Martinez, Piero Olliaro (0000-0003-1426-3680), Ednah Ooko, Edgar Ortiz-Brizuela, Pradthana Ounchanum (0009-0007-9005-2697), Gideok D Pak, José Luis Paredes (0000-0002-0547-1376), Anton Yariv Peleg, Carlo Perrone (0000-0001-9499-0399), Thong Phe, Koukeo Phommasone (0000-0002-3814-0522), Nishad Plakkal, Alfredo Ponce-de-Leon, Mathieu Raad, Tanusha Ramdin, Sayaphet Rattanavong, Amy Riddell, Tamalee Roberts (0000-0001-8599-737X), Julie Victoria Robotham, Anna Roca (0000-0001-6034-1868), Victor Daniel Rosenthal, Kristina E Rudd (0000-0002-6695-8401), Neal Russell (0000-0002-9538-7695), Helio S Sader, Weerawut Saengchan, Jesse Schnall (0000-0002-2018-3890), John Anthony Gerard Scott, Samroeng Seekaew, Mike Sharland (0000-0001-8626-8291), Madhusudhan Shivamallappa, José Sifuentes-Osornio, Andrew J Simpson, Nicolas Steenkeste, Andrew James Stewardson, Temenuga Stoeva (0000-0001-6202-4532), Nidanuch Tasak, Areerat Thaiprakong, Guy Thwaites (0000-0002-2858-2087), Caroline Tigoi (0000-0003-2750-7533), Claudia Turner (0000-0002-7588-7414), Paul Turner (0000-0001-9862-5161), H Rogier Van Doorn (0000-0002-9807-1821), Sithembiso Velaphi (0000-0002-9219-8485), Avina Vongpradith, Manivanh Vongsouvath (0000-0002-2249-7367), Hương Vũ (0009-0000-2469-5562), Timothy Walsh (0000-0002-3590-8540), Judd L Walson, Seymour Waner, Tri Wangrangsimakul, Prapass Wannapinij, Teresa Wozniak, Tracey E M W Young Sharma, Kalvin C Yu, Peng Zheng (0000-0002-8248-1826), Benn Sartorius (0000-0001-6761-2325), Alan D Lopez (0000-0001-5818-6512), Andy Stergachis (0000-0003-0057-6627), Catrin Moore, Christiane Dolecek (0000-0002-4635-9567), Mohsen Naghavi (0000-0003-3691-1458)
Year2022
Volume399
Issue10325
Pages629-655
Publication date2022-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe Lancet (JOURNAL)
Journal identifiersISSN: 0099-5355 • E-ISSN: 0140-6736
PublisherElsevier BV (PUBLISHER)
DOI10.1016/s0140-6736(21)02724-0
PMID35065702
OpenAlexW4206677002
LanguageEN
Citations received316
References cited41

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.

Antibiotic resistance · Antibiotics · Biology · Disease · Disease burden · Drug resistance · Incidence (geometry) · Infectious disease (medical specialty) · Intensive care medicine · Antibiotic Resistance in Bacteria · Antibiotic Use and Resistance · Internal Medicine · Medicine · Microbiology · Urinary Tract Infections Management