TY - JOUR
T1 - Global burden of bacterial antimicrobial resistance in 2019
T2 - A systematic analysis
AU - Antimicrobial Resistance Collaborators
AU - Murray, Christopher JL
AU - Ikuta, Kevin Shunji
AU - Sharara, Fablina
AU - Swetschinski, Lucien
AU - Robles Aguilar, Gisela
AU - Gray, Authia
AU - Han, Chieh
AU - Bisignano, Catherine
AU - Rao, Puja
AU - Wool, Eve
AU - Johnson, Sarah C.
AU - Browne, Annie J.
AU - Chipeta, Michael Give
AU - Fell, Frederick
AU - Hackett, Sean
AU - Haines-Woodhouse, Georgina
AU - Kashef Hamadani, Bahar H.
AU - Kumaran, Emmanuelle A.P.
AU - McManigal, Barney
AU - Agarwal, Ramesh
AU - Akech, Samuel
AU - Albertson, Samuel
AU - Amuasi, John
AU - Andrews, Jason
AU - Aravkin, Aleskandr
AU - Ashley, Elizabeth
AU - Bailey, Freddie
AU - Baker, Stephen
AU - Basnyat, Buddha
AU - Bekker, Adrie
AU - Bender, Rose
AU - Bethou, Adhisivam
AU - Bielicki, Julia
AU - Boonkasidecha, Suppawat
AU - Bukosia, James
AU - Carvalheiro, Cristina
AU - Castañeda-Orjuela, Carlos
AU - Chansamouth, Vilada
AU - Chaurasia, Suman
AU - Chiurchiù, Sara
AU - Chowdhury, Fazle
AU - Cook, Aislinn J.
AU - Cooper, Ben
AU - Cressey, Tim R.
AU - Criollo-Mora, Elia
AU - Cunningham, Matthew
AU - Darboe, Saffiatou
AU - Day, Nicholas P.J.
AU - De Luca, Maia
AU - Dokova, Klara
AU - Dramowski, Angela
AU - Dunachie, Susanna J.
AU - Eckmanns, Tim
AU - Eibach, Daniel
AU - Emami, Amir
AU - Feasey, Nicholas
AU - Fisher-Pearson, Natasha
AU - Forrest, Karen
AU - Garrett, Denise
AU - Gastmeier, Petra
AU - Giref, Ababi Zergaw
AU - Greer, Rachel Claire
AU - Gupta, Vikas
AU - Haller, Sebastian
AU - Haselbeck, Andrea
AU - Hay, Simon I.
AU - Holm, Marianne
AU - Hopkins, Susan
AU - Iregbu, Kenneth C.
AU - Jacobs, Jan
AU - Jarovsky, Daniel
AU - Javanmardi, Fatemeh
AU - Khorana, Meera
AU - Kissoon, Niranjan
AU - Kobeissi, Elsa
AU - Kostyanev, Tomislav
AU - Krapp, Fiorella
AU - Krumkamp, Ralf
AU - Kumar, Ajay
AU - Kyu, Hmwe Hmwe
AU - Lim, Cherry
AU - Limmathurotsakul, Direk
AU - Loftus, Michael James
AU - Lunn, Miles
AU - Ma, Jianing
AU - Mturi, Neema
AU - Munera-Huertas, Tatiana
AU - Musicha, Patrick
AU - Mussi-Pinhata, Marisa Marcia
AU - Nakamura, Tomoka
AU - Nanavati, Ruchi
AU - Nangia, Sushma
AU - Newton, Paul
AU - Ngoun, Chanpheaktra
AU - Novotney, Amanda
AU - Nwakanma, Davis
AU - Obiero, Christina W.
AU - Olivas-Martinez, Antonio
AU - Olliaro, Piero
AU - Ooko, Ednah
AU - Ortiz-Brizuela, Edgar
AU - Peleg, Anton Yariv
AU - Perrone, Carlo
AU - Plakkal, Nishad
AU - Ponce-de-Leon, Alfredo
AU - Raad, Mathieu
AU - Ramdin, Tanusha
AU - Riddell, Amy
AU - Roberts, Tamalee
AU - Robotham, Julie Victoria
AU - Roca, Anna
AU - Rudd, Kristina E.
AU - Russell, Neal
AU - Schnall, Jesse
AU - Scott, John Anthony Gerard
AU - Shivamallappa, Madhusudhan
AU - Sifuentes-Osornio, Jose
AU - Steenkeste, Nicolas
AU - Stewardson, Andrew James
AU - Stoeva, Temenuga
AU - Tasak, Nidanuch
AU - Thaiprakong, Areerat
AU - Thwaites, Guy
AU - Turner, Claudia
AU - Turner, Paul
AU - van Doorn, H. Rogier
AU - Velaphi, Sithembiso
AU - Vongpradith, Avina
AU - Vu, Huong
AU - Walsh, Timothy
AU - Waner, Seymour
AU - Wangrangsimakul, Tri
AU - Wozniak, Teresa
AU - Zheng, Peng
AU - Sartorius, Benn
AU - Lopez, Alan D.
AU - Stergachis, Andy
AU - Moore, Catrin
AU - Dolecek, Christiane
AU - Naghavi, Mohsen
N1 - Funding Information:
Funding was provided by the Bill & Melinda Gates Foundation (OPP1176062), the Wellcome Trust (A126042), and the UK Department of Health and Social Care using UK aid funding managed by the Fleming Fund (R52354 CN001). E Ashley acknowledges that Lao-Oxford-Mahosot Hospital–Wellcome Trust Research Unit receives core funding from Wellcome (20211/Z/20/Z). N Feasey acknowledges that the Malawi Liverpool Wellcome Trust Clinical Research Programme diagnostic microbiology service is funded by a Wellcome Asia and Africa Programme grant. S Dunachie acknowledges funding from NIHR Global Research Professorship (NIHR300791). F Krapp was supported by Framework Agreement Belgian Directorate of Development Cooperation-Institute of Tropical Medicine in Antwerp. M Khorana and S Boonkasidecha would like to acknowledge GARDP. A Peleg acknowledges the support from an Australian National Health and Medical Research Council Practitioner Fellowship. A Stewardson is supported by an Australian National Health and Medical Research Council Early Career Fellowship (GNT1141398). P Turner acknowledges that the Cambodia Oxford Medical Research Unit is part of the Mahidol-Oxford Tropical Medicine Research Unit Tropical Health Network and is core funded by Wellcome (220211/Z/20/Z). T Wangrangsimakul acknowledges funding from the Wellcome Trust, as part of the MORU Tropical Health Network institutional funding support. The Medical Research Council Unit—The Gambia at the LSHTM acknowledges all the staff in the microbiology clinical laboratory for their support. We acknowledge The Australian Group for Antimicrobial Resistance, and The Australian Commission on Safety and Quality in Healthcare, Sydney, Australia. We acknowledge John Murray, Becton, Dickinson and Company. We give thanks to the late Rattanaphone Phetsouvanh, the Lao Ministry of Health, and the Directorate of Mahosot Hospital who enabled the collection and sharing of Lao data, Vientiane, Lao People's Democratic Republic. We thank Sabrina Bacci, Liselotte Diaz Högberg, Marlena Kaczmarek, Maria Keramarou, Favelle Lamb, Dominique L Monnet, Gianfranco Spiteri, Carl Suetens, Therese Westrell and Klaus Weist at the ECDC, Solna, Sweden, for providing information on databases and discussions on data interpretation. We acknowledge Jennifer R Verani and team, CDC, Nairobi, Kenya; Allan Audi and team, Centre for Global Health Research, KEMRI, Kisumu, Kenya. We acknowledge Jephté Kaleb and Giscard Wilfried Koyaweda, National Laboratory of Clinical Biology and Public Health, Bangui, Central African Republic. We acknowledge Tien Viet Dung Vu and Nguyen Minh Trang Nghiem, Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital for Tropical Diseases, Hanoi, Vietnam; and the VINARES Consortium. We acknowledge the Department of Pathology and Laboratory Medicine, and Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan. We acknowledge Samuel Akech, Ednah Ooko, James Bukosia, Neema Mturi, J Anthony G Scott, Philip Bejon, Lynette Isabella Oyier, Salim Mwarumba, Esther Muthumbi, Christina Obiero, Robert Musyimi, Shebe Mohammed, Caroline Ogwang, Christopher Maronga, Ambrose Agweyu, KEMRI Wellcome Trust Research Programme, Kilifi, Kenya. We acknowledge scientific contributions to this work from the Pan American Health Organization. We would like to acknowledge the scientific contributions made from the GRAM advisory committee, specifically Neil Ferguson and Sharon Peacock. We would like to acknowledge Tomislav Mestrovic for his significant contributions to this manuscript and the overall research enterprise. We thank the Kenya Medical Research Institute, United States Army Medical Research Directorate-Africa, Kenya, Nairobi, Kenya; we acknowledge the International Nosocomial Infection Control Consortium, Buenos Aires, Argentina; we would like to thank the CHILDS Trust Medical Research Foundation, Chennai, India; we acknowledge the Childhood Acute Illness & Nutrition Network investigators; we thank Institut Pasteur and Laboratoire National de Biologie Clinique et de Santé Publique in Bangui, Central African Republic; we would like to acknowledge the Global Tuberculosis Programme of WHO, Geneva, Switzerland; we thank the SENTRY Antimicrobial Surveillance Program, JMI Laboratories, North Liberty, Iowa, USA; we acknowledge the Sihanouk Hospital Center of Hope, Phnom Penh, Cambodia.
Publisher Copyright:
© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2022/2
Y1 - 2022/2
N2 - 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 subSaharan Africa, at 27·3 deaths per 100000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100000.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 929000 (660 000–1270 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 50 000–100000 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.
AB - 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 subSaharan Africa, at 27·3 deaths per 100000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100000.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 929000 (660 000–1270 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 50 000–100000 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.
UR - http://www.scopus.com/inward/record.url?scp=85124016440&partnerID=8YFLogxK
U2 - 10.1016/S0140-6736(21)02724-0
DO - 10.1016/S0140-6736(21)02724-0
M3 - Article
C2 - 35065702
AN - SCOPUS:85124016440
VL - 399
SP - 629
EP - 655
JO - Lancet
JF - Lancet
SN - 0140-6736
IS - 10325
ER -