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Measuring and mapping the global burden of antimicrobial resistance

Measuring and mapping the global burden of antimicrobial resistance Hay et al. BMC Medicine (2018) 16:78 https://doi.org/10.1186/s12916-018-1073-z COMMENTARY Open Access Measuring and mapping the global burden of antimicrobial resistance 1,2 1 3,4 3,4 5 2,6* Simon I. Hay , Puja C. Rao , Christiane Dolecek , Nicholas P. J. Day , Andy Stergachis , Alan D. Lopez and Christopher J. L. Murray Abstract: 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. Keywords: Antimicrobial resistance, Drug-resistant infections, Microbial, Anti-infective agents, Antimicrobial drugs, Global health, Global burden of disease, Public health Background infection control, inadequate sanitary conditions, and Antimicrobial resistance (AMR) occurs when bacteria, inappropriate food handling may facilitate the spread of viruses, fungi, and parasites adapt to antimicrobial drugs, AMR within populations [9]. resulting in drug inefficiency and persistent infections, There are many challenges to estimating the burden of with a subsequent increase in the risks of severe disease AMR. Primarily, there is limited and unreliable current and transmission. AMR is a major global threat to the and historical information on the geographical distribu- health of populations, endangering the ability to prevent tion, prevalence, and incidence of AMR and its health and cure a wide range of infectious diseases [1–3]. While burden, making the burden of AMR difficult to measure AMR occurs naturally, the emergence and spread of new and limiting our ability to devise geographically explicit resistance mechanisms may have been greatly accelerated strategies for its control [10, 11]. Disparate data sources by the overuse and misuse of antimicrobials [4]. In many from public and private sectors are often not collated at countries, antibiotics are given without professional over- the national and international levels and contain little sight and are inappropriately used in both people and information on individual patients and their outcomes. animals; important examples of such misuse include the Furthermore, there are fundamental issues of selection consumption of antibiotics by people with common viral bias in terms of who is tested for AMR and whether or infections or when given to farm-raised fish or livestock as not that information is entered into facility-based labora- growth promoters [4–7]. Microbes that are resistant to tory data systems. Additionally, systematic efforts are yet antimicrobials are found in people, animals, food, and the to be made to quantify antimicrobial drug utilization environment, and can spread between humans and patterns, which would yield important data to address animals, and from person to person [8]. Further, poor AMR. Protocols for diagnostic methods and data collec- tion need to be standardized to allow an accurate depic- tion of the true health burden of AMR to be constructed. * Correspondence: alan.lopez@unimelb.edu.au These problems are exacerbated in low- and middle- Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford OX3 7LF, UK income countries, where there is often inadequate surveil- Melbourne School of Population and Global Health, The University of lance, minimal laboratory capacity, and limited access to Melbourne, Level 5, 207 Bouverie St, Carlton, VIC 3053, Australia essential antimicrobials. Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Hay et al. BMC Medicine (2018) 16:78 Page 2 of 3 As the threat of AMR continues to grow, more work is feedback on data, modelling, and results from existing needed to supplement current surveillance and methodo- partnerships and collaborations. Perhaps more import- logically inconsistent research regarding the global epidemi- antly, including AMR in the GBD will ensure that the ology and impact of AMR. Some studies have addressed resulting estimates comply with the rigorous, evidence- the challenges to measuring the burden of AMR and also based framework that characterizes the GBD effort. provide estimates of prevalence of resistance for particular Annual updates to data and results enable ongoing, pathogen-antimicrobial drug combinations in various loca- improved annual assessment of the AMR burden. tions [1, 3, 12]. However, major gaps in data on prevalence The strategy we will pursue in estimating the burden and incidence as well as on types of resistance, treatment of AMR has several dimensions. First, because of the failures, and studies on the attributable mortality and important role of sepsis involving a drug-resistant organ- morbidity of AMR, particularly in low- and middle-income ism as an intermediate pathway to death from AMR, we countries, have made it nearly impossible to reliably esti- will analyze the burden of all forms of sepsis in the mate the global impact of AMR. To combat AMR, policy- GBD. Second, we will collate and analyze the data makers and other stakeholders have issued calls to action, gathered by the public and private sectors on resistant including a focus on broad improvements to surveillance of bacteria present in various human samples (blood, urine, the current global resistance situation, support for and stool, wounds, etc.). Third, we will systematically review prioritization of new diagnostics, antimicrobials and vac- published and unpublished sources on the relative cines, and improved stewardship of existing antimicrobials case-fatality rate for drug-resistant versus drug-sensitive to avoid further selection and emergence of resistant infections for different clinical syndromes. These compo- bacteria [1, 2, 12, 13]. As a critical input to these actions, a nents will allow estimation of the burden of resistance for high-quality evidence base is needed to support surveillance different drug-organism combinations. Over time, we will and data collection efforts, as well as to inform global systematically expand the number of combinations policy priorities, set clear international standards and included in the GBD assessment. The initial objective of guidelines, establish intervention priorities, and support the burden of disease assessment for AMR will include a investment decisions. comprehensive synthesis of existing global AMR data on selected bacterial pathogens (listed in Table 1), developing Quantifying the global burden of AMR analytical methods to estimate the fraction of burden from Here, we present a new project (“AMR project”)to causes is attributable to AMR, and producing disease provide rigorous quantitative evidence of the burden of burden estimates and incorporating them into interactive AMR, to increase awareness of AMR, to support better visualizations and maps for public access. surveillance of AMR, and to foster the rational use of antimicrobials around the world. An important aspect of Conclusions this AMR project is the integration of AMR burden with Results from this effort will contribute to the assessment of the larger Global Burden of Diseases, Injuries, and Risk theburdenof AMR over time,allowinganevaluationof Factors (GBD) Study at the Institute for Health Metrics and Evaluation. Table 1 Geospatial maps of the prevalence and incidence of The GBD is an ongoing comprehensive global research resistance of selected bacteria-antibacterial drug combinations program that provides comparable estimates of mortality will be created and disability resulting from 328 disease and injury Bacteria Antibacterial drug(s) causes, as well as from 84 risk factors, across age and Escherichia coli Third-generation cephalosporins, sex groups, over time and space [14–17]. This AMR fluoroquinolones project will take advantage of the established infrastruc- Shigella species Fluoroquinolones ture of the GBD, which involves over 3200 collaborators Klebsiella pneumoniae Third-generation cephalosporins, in 140 countries and three non-sovereign locations carbapenems around the world, and will be conducted under a stra- Streptococcus pneumoniae Penicillin tegic partnership with the Big Data Institute and the Staphylococcus aureus Methicillin Centre for Tropical Medicine and Global Health at the Salmonella Typhi and Fluoroquinolones, chloramphenicol University of Oxford, UK. The GBD has the largest Paratyphi known existing repository of epidemiological data, which Non-typhoidal Salmonellae Fluoroquinolones is used to compare the loss of healthy life due to a par- Neisseria gonorrhoeae Third-generation cephalosporins ticular health disparity, such as AMR, around the world relative to other causes of disability and mortality. As Mycobacterium tuberculosis First-line – isoniazid, rifampicin Second-line – fluoroquinolones, with other research areas in the GBD, this research will amikacin, capreomycin, kanamycin undergo a high level of scientific scrutiny by leveraging Hay et al. BMC Medicine (2018) 16:78 Page 3 of 3 current and past magnitude and geographical dispersion of 2. Shallcross LJ, Howard SJ, Fowler T, Davies SC. Tackling the threat of antimicrobial resistance: from policy to sustainable action. Philos Trans R the hazard, thus providing essential health intelligence to Soc Lond Ser B Biol Sci. 2015;370:20140082. guide interventions and policies, as well as a benchmark 3. World Health Organization. Antimicrobial Resistance: Global Report on for measuring the impact of interventions on future Surveillance 2014. http://www.who.int/drugresistance/documents/ surveillancereport/en/. Accessed 20 Mar 2018. burden. By incorporating this work into the GBD, it will 4. 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This aim will Antimicrobial use in aquaculture re-examined: its relevance to benefit from and be supported by similar streams of work antimicrobial resistance and to animal and human health. Environ within this AMR project that will map the prevalence and Microbiol. 2013;15:1917–42. 7. Sharma C, Rokana N, Chandra M, Singh BP, Gulhane RD, Gill JPS, et al. incidence of resistance of selected bacteria-antibacterial Antimicrobial resistance: its surveillance, impact, and alternative drug combinations at the highest geographic resolution management strategies in dairy animals. Front Vet Sci. 2017;4:237. possible (Table 1). Analyses such as these are urgently re- 8. Woolhouse M, Ward M, van Bunnik B, Farrar J. Antimicrobial resistance in humans, livestock and the wider environment. Philos Trans R Soc B Biol Sci. quired to provide accurate and timely data on the magni- 2015;370(1670):20140083. tude of and trends in AMR burden across the world. 9. Fletcher S. Understanding the contribution of environmental factors in the Accurate assessments of AMR burden can be used to in- spread of antimicrobial resistance. Environ Health Prev Med. 2015;20:243–52. 10. Graetz N, Friedman J, Osgood-Zimmerman A, Burstein R, Biehl MH, Shields form treatment guidelines and agendas for decision- C, et al. Mapping local variation in educational attainment across Africa. making, surveillance and research, to detect emerging Nature. 2018;555:48–53. problems, help guide investments in combatting AMR, 11. Osgood-Zimmerman A, Millear AI, Stubbs RW, Shields C, Pickering BV, Earl L, et al. Mapping child growth failure in Africa between 2000 and 2015. and monitor trends to inform global strategies, as well as Nature. 2018;555:41–7. to facilitate the assessment of interventions over time. 12. World Health Organization. Global Antimicrobial Resistance Surveillance System: Manual for Early Implementation. Geneva: WHO; 2015. 13. van der Meer JWM, Fears R, Davies SC, ter Meulen V. Antimicrobial Funding innovation: combining commitment, creativity and coherence. Nature Rev This work is being funded by the United Kingdom’s Department of Health Drug Discov. 2014;13:709–10. and Social Care, Fleming Fund (SH), the Wellcome Trust (209142/Z/17/Z: SH), 14. Naghavi M, Abajobir AA, Abbafati C, Abbas KM, Abd-Allah F, Abera SF, et al. and the Bill and Melinda Gates Foundation (OPP1176062: CM). Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Author’s contributions Study 2016. Lancet. 2017;390:1151–210. SIH, ADL, CJLM, PCR, CD, NPJD, and AS all contributed to the conception, writing, 15. Gakidou E, Afshin A, Abajobir AA, Abate KH, Abbafati C, Abbas KM, et al. and editing of this Commentary. All authors have approved the final version. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Competing interests Disease Study 2016. Lancet. 2017;390:1345–422. The authors declare that they have no competing interest. 16. Hay SI, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, et al. Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries Publisher’sNote and territories, 1990–2016: a systematic analysis for the Global Burden of Springer Nature remains neutral with regard to jurisdictional claims in Disease Study 2016. Lancet. 2017;390:1260–344. published maps and institutional affiliations. 17. Vos T, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, et al. Global, regional, and national incidence, prevalence, and years lived with Author details disability for 328 diseases and injuries for 195 countries, 1990–2016: a Institute for Health Metrics and Evaluation, University of Washington, 2301 systematic analysis for the Global Burden of Disease Study 2016. Lancet. 5th Ave, Seattle, WA 98121, USA. Big Data Institute, University of Oxford, Li 2017;390:1211–59. Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford OX3 7LF, UK. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford OX3 7FZ, UK. Mahidol–Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, 420/6 Rajvithi Road, Bangkok 10400, Thailand. School of Pharmacy, University of Washington, H-362B Box 357631, Seattle, WA 98195, USA. Melbourne School of Population and Global Health, The University of Melbourne, Level 5, 207 Bouverie St, Carlton, VIC 3053, Australia. Received: 23 April 2018 Accepted: 11 May 2018 References 1. Chief Medical Officer Annual Report 2011. Antimicrobial Resistance - GOV. UK. https://www.gov.uk/government/publications/chief-medical-officer- annual-report-volume-2. Accessed 19 Mar 2018. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Medicine Springer Journals

Measuring and mapping the global burden of antimicrobial resistance

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Kadel, Amaha Kahsay, R. Kamal, A. Karch, Seyed Karimi, C. Karimkhani, A. Kasaeian, N. Kassaw, N. Kassebaum, S. Katikireddi, N. Kawakami, P. Keiyoro, L. Kemmer, C. Kesavachandran, Y. Khader, E. Khan, Y. Khang, Abdullah Khoja, Mohammad Khosravi, A. Khosravi, J. Khubchandani, A. Kiadaliri, C. Kieling, Daniel Kievlan, Y. Kim, Daniel Kim, R. Kimokoti, Y. Kinfu, N. Kissoon, M. Kivimaki, A. Knudsen, J. Kopec, S. Kosen, P. Koul, A. Koyanagi, X. Kulikoff, G. Kumar, Pushpendra Kumar, Michael Kutz, H. Kyu, D. Lal, R. Lalloo, Tea Lambert, Q. Lan, V. Lansingh, A. Larsson, P. Lee, J. Leigh, J. Leung, M. Levi, Yongmei Li, Darya Kappe, Xiaofeng Liang, Misgan Liben, Stephen Lim, Patrick Liu, Angela Liu, Yang Liu, R. Lodha, G. Logroscino, Alan Lopez, S. Lorkowski, P. Lotufo, R. Lozano, T. Lucas, Stefan Ma, Erlyn Macarayan, Emilie Maddison, M. Razek, M. Majdan, R. Majdzadeh, A. Majeed, R. Malekzadeh, R. Malhotra, D. Malta, Helena Manguerra, T. Manyazewal, C. Mapoma, L. Marczak, D. Markos, J. 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Schwendicke, S. Sepanlou, E. Serván-Mori, K. Shackelford, S. Shahraz, M. Shaikh, M. Shamsipour, M. Shamsizadeh, Jayendra Sharma, Rajesh Sharma, Jun She, S. Sheikhbahaei, M. Shey, Chloe Shields, M. Shigematsu, R. Shiri, S. Shirude, I. Shiue, H. Shoman, M. Shrime, I. Sigfusdottir, Naris Silpakit, J. Silva, J. Singh, Abhishek Singh, Eirini Skiadaresi, Amber Sligar, David Smith, Alison Smith, Mari Smith, B. Sobaih, S. Soneji, Reed Sorensen, J. Soriano (2017)

    Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016

    Lancet (London, England), 390

  • L. Shallcross, S. Howard, Tom Fowler, S. Davies (2015)

    Tackling the threat of antimicrobial resistance: from policy to sustainable action

    Philosophical Transactions of the Royal Society B: Biological Sciences, 370

  • Mark Woolhouse, Melissa Ward, Bram Bunnik, Jeremy Farrar (2015)

    Antimicrobial resistance in humans, livestock and the wider environment

    Philosophical Transactions of the Royal Society B: Biological Sciences, 370

Publisher
Springer Journals
Copyright
Copyright © 2018 by The Author(s).
Subject
Medicine & Public Health; Medicine/Public Health, general; Biomedicine, general
eISSN
1741-7015
DOI
10.1186/s12916-018-1073-z
pmid
29860943
Publisher site
See Article on Publisher Site

Abstract

Hay et al. BMC Medicine (2018) 16:78 https://doi.org/10.1186/s12916-018-1073-z COMMENTARY Open Access Measuring and mapping the global burden of antimicrobial resistance 1,2 1 3,4 3,4 5 2,6* Simon I. Hay , Puja C. Rao , Christiane Dolecek , Nicholas P. J. Day , Andy Stergachis , Alan D. Lopez and Christopher J. L. Murray Abstract: 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. Keywords: Antimicrobial resistance, Drug-resistant infections, Microbial, Anti-infective agents, Antimicrobial drugs, Global health, Global burden of disease, Public health Background infection control, inadequate sanitary conditions, and Antimicrobial resistance (AMR) occurs when bacteria, inappropriate food handling may facilitate the spread of viruses, fungi, and parasites adapt to antimicrobial drugs, AMR within populations [9]. resulting in drug inefficiency and persistent infections, There are many challenges to estimating the burden of with a subsequent increase in the risks of severe disease AMR. Primarily, there is limited and unreliable current and transmission. AMR is a major global threat to the and historical information on the geographical distribu- health of populations, endangering the ability to prevent tion, prevalence, and incidence of AMR and its health and cure a wide range of infectious diseases [1–3]. While burden, making the burden of AMR difficult to measure AMR occurs naturally, the emergence and spread of new and limiting our ability to devise geographically explicit resistance mechanisms may have been greatly accelerated strategies for its control [10, 11]. Disparate data sources by the overuse and misuse of antimicrobials [4]. In many from public and private sectors are often not collated at countries, antibiotics are given without professional over- the national and international levels and contain little sight and are inappropriately used in both people and information on individual patients and their outcomes. animals; important examples of such misuse include the Furthermore, there are fundamental issues of selection consumption of antibiotics by people with common viral bias in terms of who is tested for AMR and whether or infections or when given to farm-raised fish or livestock as not that information is entered into facility-based labora- growth promoters [4–7]. Microbes that are resistant to tory data systems. Additionally, systematic efforts are yet antimicrobials are found in people, animals, food, and the to be made to quantify antimicrobial drug utilization environment, and can spread between humans and patterns, which would yield important data to address animals, and from person to person [8]. Further, poor AMR. Protocols for diagnostic methods and data collec- tion need to be standardized to allow an accurate depic- tion of the true health burden of AMR to be constructed. * Correspondence: alan.lopez@unimelb.edu.au These problems are exacerbated in low- and middle- Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford OX3 7LF, UK income countries, where there is often inadequate surveil- Melbourne School of Population and Global Health, The University of lance, minimal laboratory capacity, and limited access to Melbourne, Level 5, 207 Bouverie St, Carlton, VIC 3053, Australia essential antimicrobials. Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Hay et al. BMC Medicine (2018) 16:78 Page 2 of 3 As the threat of AMR continues to grow, more work is feedback on data, modelling, and results from existing needed to supplement current surveillance and methodo- partnerships and collaborations. Perhaps more import- logically inconsistent research regarding the global epidemi- antly, including AMR in the GBD will ensure that the ology and impact of AMR. Some studies have addressed resulting estimates comply with the rigorous, evidence- the challenges to measuring the burden of AMR and also based framework that characterizes the GBD effort. provide estimates of prevalence of resistance for particular Annual updates to data and results enable ongoing, pathogen-antimicrobial drug combinations in various loca- improved annual assessment of the AMR burden. tions [1, 3, 12]. However, major gaps in data on prevalence The strategy we will pursue in estimating the burden and incidence as well as on types of resistance, treatment of AMR has several dimensions. First, because of the failures, and studies on the attributable mortality and important role of sepsis involving a drug-resistant organ- morbidity of AMR, particularly in low- and middle-income ism as an intermediate pathway to death from AMR, we countries, have made it nearly impossible to reliably esti- will analyze the burden of all forms of sepsis in the mate the global impact of AMR. To combat AMR, policy- GBD. Second, we will collate and analyze the data makers and other stakeholders have issued calls to action, gathered by the public and private sectors on resistant including a focus on broad improvements to surveillance of bacteria present in various human samples (blood, urine, the current global resistance situation, support for and stool, wounds, etc.). Third, we will systematically review prioritization of new diagnostics, antimicrobials and vac- published and unpublished sources on the relative cines, and improved stewardship of existing antimicrobials case-fatality rate for drug-resistant versus drug-sensitive to avoid further selection and emergence of resistant infections for different clinical syndromes. These compo- bacteria [1, 2, 12, 13]. As a critical input to these actions, a nents will allow estimation of the burden of resistance for high-quality evidence base is needed to support surveillance different drug-organism combinations. Over time, we will and data collection efforts, as well as to inform global systematically expand the number of combinations policy priorities, set clear international standards and included in the GBD assessment. The initial objective of guidelines, establish intervention priorities, and support the burden of disease assessment for AMR will include a investment decisions. comprehensive synthesis of existing global AMR data on selected bacterial pathogens (listed in Table 1), developing Quantifying the global burden of AMR analytical methods to estimate the fraction of burden from Here, we present a new project (“AMR project”)to causes is attributable to AMR, and producing disease provide rigorous quantitative evidence of the burden of burden estimates and incorporating them into interactive AMR, to increase awareness of AMR, to support better visualizations and maps for public access. surveillance of AMR, and to foster the rational use of antimicrobials around the world. An important aspect of Conclusions this AMR project is the integration of AMR burden with Results from this effort will contribute to the assessment of the larger Global Burden of Diseases, Injuries, and Risk theburdenof AMR over time,allowinganevaluationof Factors (GBD) Study at the Institute for Health Metrics and Evaluation. Table 1 Geospatial maps of the prevalence and incidence of The GBD is an ongoing comprehensive global research resistance of selected bacteria-antibacterial drug combinations program that provides comparable estimates of mortality will be created and disability resulting from 328 disease and injury Bacteria Antibacterial drug(s) causes, as well as from 84 risk factors, across age and Escherichia coli Third-generation cephalosporins, sex groups, over time and space [14–17]. This AMR fluoroquinolones project will take advantage of the established infrastruc- Shigella species Fluoroquinolones ture of the GBD, which involves over 3200 collaborators Klebsiella pneumoniae Third-generation cephalosporins, in 140 countries and three non-sovereign locations carbapenems around the world, and will be conducted under a stra- Streptococcus pneumoniae Penicillin tegic partnership with the Big Data Institute and the Staphylococcus aureus Methicillin Centre for Tropical Medicine and Global Health at the Salmonella Typhi and Fluoroquinolones, chloramphenicol University of Oxford, UK. The GBD has the largest Paratyphi known existing repository of epidemiological data, which Non-typhoidal Salmonellae Fluoroquinolones is used to compare the loss of healthy life due to a par- Neisseria gonorrhoeae Third-generation cephalosporins ticular health disparity, such as AMR, around the world relative to other causes of disability and mortality. As Mycobacterium tuberculosis First-line – isoniazid, rifampicin Second-line – fluoroquinolones, with other research areas in the GBD, this research will amikacin, capreomycin, kanamycin undergo a high level of scientific scrutiny by leveraging Hay et al. BMC Medicine (2018) 16:78 Page 3 of 3 current and past magnitude and geographical dispersion of 2. Shallcross LJ, Howard SJ, Fowler T, Davies SC. Tackling the threat of antimicrobial resistance: from policy to sustainable action. Philos Trans R the hazard, thus providing essential health intelligence to Soc Lond Ser B Biol Sci. 2015;370:20140082. guide interventions and policies, as well as a benchmark 3. World Health Organization. Antimicrobial Resistance: Global Report on for measuring the impact of interventions on future Surveillance 2014. http://www.who.int/drugresistance/documents/ surveillancereport/en/. Accessed 20 Mar 2018. burden. By incorporating this work into the GBD, it will 4. 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This aim will Antimicrobial use in aquaculture re-examined: its relevance to benefit from and be supported by similar streams of work antimicrobial resistance and to animal and human health. Environ within this AMR project that will map the prevalence and Microbiol. 2013;15:1917–42. 7. Sharma C, Rokana N, Chandra M, Singh BP, Gulhane RD, Gill JPS, et al. incidence of resistance of selected bacteria-antibacterial Antimicrobial resistance: its surveillance, impact, and alternative drug combinations at the highest geographic resolution management strategies in dairy animals. Front Vet Sci. 2017;4:237. possible (Table 1). Analyses such as these are urgently re- 8. Woolhouse M, Ward M, van Bunnik B, Farrar J. Antimicrobial resistance in humans, livestock and the wider environment. Philos Trans R Soc B Biol Sci. quired to provide accurate and timely data on the magni- 2015;370(1670):20140083. tude of and trends in AMR burden across the world. 9. Fletcher S. Understanding the contribution of environmental factors in the Accurate assessments of AMR burden can be used to in- spread of antimicrobial resistance. Environ Health Prev Med. 2015;20:243–52. 10. Graetz N, Friedman J, Osgood-Zimmerman A, Burstein R, Biehl MH, Shields form treatment guidelines and agendas for decision- C, et al. Mapping local variation in educational attainment across Africa. making, surveillance and research, to detect emerging Nature. 2018;555:48–53. problems, help guide investments in combatting AMR, 11. Osgood-Zimmerman A, Millear AI, Stubbs RW, Shields C, Pickering BV, Earl L, et al. Mapping child growth failure in Africa between 2000 and 2015. and monitor trends to inform global strategies, as well as Nature. 2018;555:41–7. to facilitate the assessment of interventions over time. 12. World Health Organization. Global Antimicrobial Resistance Surveillance System: Manual for Early Implementation. Geneva: WHO; 2015. 13. van der Meer JWM, Fears R, Davies SC, ter Meulen V. Antimicrobial Funding innovation: combining commitment, creativity and coherence. Nature Rev This work is being funded by the United Kingdom’s Department of Health Drug Discov. 2014;13:709–10. and Social Care, Fleming Fund (SH), the Wellcome Trust (209142/Z/17/Z: SH), 14. Naghavi M, Abajobir AA, Abbafati C, Abbas KM, Abd-Allah F, Abera SF, et al. and the Bill and Melinda Gates Foundation (OPP1176062: CM). Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Author’s contributions Study 2016. Lancet. 2017;390:1151–210. SIH, ADL, CJLM, PCR, CD, NPJD, and AS all contributed to the conception, writing, 15. Gakidou E, Afshin A, Abajobir AA, Abate KH, Abbafati C, Abbas KM, et al. and editing of this Commentary. All authors have approved the final version. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Competing interests Disease Study 2016. Lancet. 2017;390:1345–422. The authors declare that they have no competing interest. 16. Hay SI, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, et al. Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries Publisher’sNote and territories, 1990–2016: a systematic analysis for the Global Burden of Springer Nature remains neutral with regard to jurisdictional claims in Disease Study 2016. Lancet. 2017;390:1260–344. published maps and institutional affiliations. 17. Vos T, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, et al. Global, regional, and national incidence, prevalence, and years lived with Author details disability for 328 diseases and injuries for 195 countries, 1990–2016: a Institute for Health Metrics and Evaluation, University of Washington, 2301 systematic analysis for the Global Burden of Disease Study 2016. Lancet. 5th Ave, Seattle, WA 98121, USA. Big Data Institute, University of Oxford, Li 2017;390:1211–59. Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford OX3 7LF, UK. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford OX3 7FZ, UK. Mahidol–Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, 420/6 Rajvithi Road, Bangkok 10400, Thailand. School of Pharmacy, University of Washington, H-362B Box 357631, Seattle, WA 98195, USA. Melbourne School of Population and Global Health, The University of Melbourne, Level 5, 207 Bouverie St, Carlton, VIC 3053, Australia. Received: 23 April 2018 Accepted: 11 May 2018 References 1. Chief Medical Officer Annual Report 2011. Antimicrobial Resistance - GOV. UK. https://www.gov.uk/government/publications/chief-medical-officer- annual-report-volume-2. Accessed 19 Mar 2018.

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BMC Medicine – Springer Journals

Published: Jun 4, 2018

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