CoChat
Sign Up
Cited by 384Antibiotic Use and ResistanceAntibiotic Resistance in BacteriaAntimicrobial Resistance in Staphylococcus

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

The burden of bacterial antimicrobial resistance in the WHO European region in 2019: a cross-country systematic analysis

Open access
Mestrovic, Tomislav, Robles Aguilar, Gisela, Swetschinski, Lucien R, Ikuta, Kevin S, Gray, Authia P, Davis Weaver, Nicole, Han, Chieh, Wool, Eve E, Gershberg Hayoon, Anna, Hay, Simon I, Dolecek, Christiane, Sartorius, Benn, Murray, Christopher J L, Addo, Isaac Yeboah, Ahinkorah, Bright Opoku, Ahmed, Ayman, Aldeyab, Mamoon A, Allel, Kasim, Ancuceanu, Robert, Anyasodor, Anayochukwu Edward, Ausloos, Marcel, Barra, Fabio, Bhagavathula, Akshaya Srikanth, Bhandari, Dinesh, Bhaskar, Sonu, Cruz-Martins, Natália, Dastiridou, Anna, Dokova, Klara, Dubljanin, Eleonora, Durojaiye, Oyewole Christopher, Fagbamigbe, Adeniyi Francis, Ferrero, Simone, Gaal, Peter Andras, Gupta, Veer Bala, Gupta, Vijai Kumar, Gupta, Vivek Kumar, Herteliu, Claudiu, Hussain, Salman, Ilic, Irena M, Ilic, Milena D, Jamshidi, Elham, Joo, Tamas, Karch, André, Kisa, Adnan, Kisa, Sezer, Kostyanev, Tomislav, Kyu, Hmwe Hmwe, Lám, Judit, Lopes, Graciliana, Mathioudakis, Alexander G, Mentis, Alexios-Fotios A, Michalek, Irmina Maria, Moni, Mohammad Ali, Moore, Catrin E, Mulita, Francesk, Negoi, Ionut, Negoi, Ruxandra Irina, Palicz, Tamás, Pana, Adrian, Perdigão, João, Petcu, Ionela-Roxana, Rabiee, Navid, Rawaf, David Laith, Rawaf, Salman, Shakhmardanov, Murad Ziyaudinovich, Sheikh, Aziz, Silva, Luís Manuel Lopes Rodrigues, Skryabin, Valentin Yurievich, Skryabina, Anna Aleksandrovna, Socea, Bogdan, Stergachis, Andy, Stoeva, Temenuga Zhekova, Sumi, Chandra Datta, Thiyagarajan, Arulmani, Tovani-Palone, Marcos Roberto, Yesiltepe, Metin, Zaman, Sojib Bin, Naghavi, Mohsen·2022·The Lancet Public Health
DOI 10.1016/s2468-2667(22)00225-0PMC PMC9630253
Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: Antimicrobial resistance (AMR) represents one of the most crucial threats to public health and modern health care. Previous studies have identified challenges with estimating the magnitude of the problem and its downstream effect on human health and mortality. To our knowledge, this study presents the most comprehensive set of regional and country-level estimates of AMR burden in the WHO European region to date. METHODS: We estimated deaths and disability-adjusted life-years attributable to and associated with AMR for 23 bacterial pathogens and 88 pathogen-drug combinations for the WHO European region and its countries in 2019. Our methodological approach consisted of five broad components: the number of deaths in which infection had a role, the proportion of infectious deaths attributable to a given infectious syndrome, the proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antimicrobial drug of interest, and the excess risk of mortality (or duration of an infection) associated with this resistance. These components were then used to estimate the disease burden by using two counterfactual scenarios: deaths attributable to AMR (considering an alternative scenario where infections with resistant pathogens are replaced with susceptible ones) and deaths associated with AMR (considering an alternative scenario where drug-resistant infections would not occur at all). Data were solicited from a wide array of international stakeholders; these included research hospitals, surveillance networks, and infection databases maintained by private laboratories and medical technology companies. 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. FINDINGS: We estimated 541 000 deaths (95% UI 370 000-763 000) associated with bacterial AMR and 133 000 deaths (90 100-188 000) attributable to bacterial AMR in the whole WHO European region in 2019. The largest fatal burden of AMR in the region came from bloodstream infections, with 195 000 deaths (104 000-333 000) associated with resistance, followed by intra-abdominal infections (127 000 deaths [81 900-185 000]) and respiratory infections (120 000 deaths [94 500-154 000]). Seven leading pathogens were responsible for about 457 000 deaths associated with resistance in 53 countries of this region; these pathogens were, in descending order of mortality, Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterococcus faecium, Streptococcus pneumoniae, and Acinetobacter baumannii. Methicillin-resistant S aureus was shown to be the leading pathogen-drug combination in 27 countries for deaths attributable to AMR, while aminopenicillin-resistant E coli predominated in 47 countries for deaths associated with AMR. INTERPRETATION: The high levels of resistance for several important bacterial pathogens and pathogen-drug combinations, together with the high mortality rates associated with these pathogens, show that AMR is a serious threat to public health in the WHO European region. Our regional and cross-country analyses open the door for strategies that can be tailored to leading pathogen-drug combinations and the available resources in a specific location. These results underscore that the most effective way to tackle AMR in this region will require targeted efforts and investments in conjunction with continuous outcome-based research endeavours. FUNDING: Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/s2468-2667(22)00225-0

Cites

24 of 24 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Heatmap representing death counts associated with antimicrobial resistance by pathogen–drug combination in the WHO European region in 2019 Group A Streptococcus pertains to Streptococcus pyogenes, and Group B Streptococcus pertains to Streptococcus agalactiae. Some counts are rounded to the nearest hundred. 3GC=third-generation cephalosporins. 4GC=fourth-generation cephalosporins. Anti-pseudomonal=anti-pseudomonal penicillin or β-lactamase inhibitors. BL-BLI=β-lactam or β-lactamase inhibitors. MDR=multidrug resistance. Mono INH=isoniazid mono-resistance. Mono RIF=rifampicin mono-resistance. NA=not applicable. Resistance to 1+=resistance to one or more drugs. S Paratyphi=Salmonella enterica serotype Paratyphi. S Typhi=S enterica serotype Typhi. TMP-SMX=trimethoprim-sulfamethoxazole. XDR=extensive drug resistance.
Figure 1 Heatmap representing death counts associated with antimicrobial resistance by pathogen–drug combination in the WHO European region in 2019 Group A Streptococcus pertains to Streptococcus pyogenes, and Group B Streptococcus pertains to Streptococcus agalactiae. Some counts are rounded to the nearest hundred. 3GC=third-generation cephalosporins. 4GC=fourth-generation cephalosporins. Anti-pseudomonal=anti-pseudomonal penicillin or β-lactamase inhibitors. BL-BLI=β-lactam or β-lactamase inhibitors. MDR=multidrug resistance. Mono INH=isoniazid mono-resistance. Mono RIF=rifampicin mono-resistance. NA=not applicable. Resistance to 1+=resistance to one or more drugs. S Paratyphi=Salmonella enterica serotype Paratyphi. S Typhi=S enterica serotype Typhi. TMP-SMX=trimethoprim-sulfamethoxazole. XDR=extensive drug resistance.CC BY · PubMed Central
Figure 2 Heatmap representing death counts attributable to antimicrobial resistance by pathogen–drug combination in the WHO European region in 2019 Group A Streptococcus pertains to Streptococcus pyogenes, and Group B Streptococcus pertains to Streptococcus agalactiae. Some counts are rounded to the nearest hundred. 3GC=third-generation cephalosporins. 4GC=fourth-generation cephalosporins. Anti-pseudomonal=anti-pseudomonal penicillin or β-lactamase inhibitors. BL-BLI=β-lactam or β-lactamase inhibitors. MDR=multidrug resistance. Mono INH=isoniazid mono-resistance. Mono RIF=rifampicin mono-resistance. NA=not applicable. Resistance to 1+=resistance to one or more drugs. S Paratyphi=Salmonella enterica serotype Paratyphi. S Typhi=S enterica serotype Typhi. TMP-SMX=trimethoprim-sulfamethoxazole. XDR=extensive drug resistance.
Figure 2 Heatmap representing death counts attributable to antimicrobial resistance by pathogen–drug combination in the WHO European region in 2019 Group A Streptococcus pertains to Streptococcus pyogenes, and Group B Streptococcus pertains to Streptococcus agalactiae. Some counts are rounded to the nearest hundred. 3GC=third-generation cephalosporins. 4GC=fourth-generation cephalosporins. Anti-pseudomonal=anti-pseudomonal penicillin or β-lactamase inhibitors. BL-BLI=β-lactam or β-lactamase inhibitors. MDR=multidrug resistance. Mono INH=isoniazid mono-resistance. Mono RIF=rifampicin mono-resistance. NA=not applicable. Resistance to 1+=resistance to one or more drugs. S Paratyphi=Salmonella enterica serotype Paratyphi. S Typhi=S enterica serotype Typhi. TMP-SMX=trimethoprim-sulfamethoxazole. XDR=extensive drug resistance.CC BY · PubMed Central
Figure 3 Cross-country comparison of age-standardised mortality rates per 100 000 person-years for deaths attributable to (A) and associated with (B) antimicrobial resistance in the WHO European region in 2019
Figure 3 Cross-country comparison of age-standardised mortality rates per 100 000 person-years for deaths attributable to (A) and associated with (B) antimicrobial resistance in the WHO European region in 2019CC BY · PubMed Central
Figure 4 Age-specific mortality rates for deaths attributable to and deaths associated with AMR per 100 000 person-years by age group and country in 2019 AMR=antimicrobial resistance.
Figure 4 Age-specific mortality rates for deaths attributable to and deaths associated with AMR per 100 000 person-years by age group and country in 2019 AMR=antimicrobial resistance.CC BY · PubMed Central
Figure 5 Age-standardised mortality rate associated with and attributable to AMR in relation to the status of NAPs for the countries in the WHO European region Rates per 100 000 person-years associated with AMR are coloured according to NAP status, while rates attributable to AMR are grey. The category “no NAP” also includes countries that did not provide data about its status. NAP data was acquired from the 2020–21 Country Self-assessment Survey responses.21 Estimates were aggregated across drugs, accounting for the co-occurrence of resistance to multiple drugs. AMR=antimicrobial resistance. NAP=national AMR action plan.
Figure 5 Age-standardised mortality rate associated with and attributable to AMR in relation to the status of NAPs for the countries in the WHO European region Rates per 100 000 person-years associated with AMR are coloured according to NAP status, while rates attributable to AMR are grey. The category “no NAP” also includes countries that did not provide data about its status. NAP data was acquired from the 2020–21 Country Self-assessment Survey responses.21 Estimates were aggregated across drugs, accounting for the co-occurrence of resistance to multiple drugs. AMR=antimicrobial resistance. NAP=national AMR action plan.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 24 references

Cited by

Sorted by citations

Items 101–200 of 383

Related

See all

Metadata

Authors
Mestrovic, T., Robles Aguilar, G., Swetschinski, L. R., Ikuta, K. S., Gray, A. P., Davis Weaver, N., Han, C., Wool, E. E., Gershberg Hayoon, A., Hay, S. I., Dolecek, C., Sartorius, B., Murray, C. J. L., Addo, I. Y., Ahinkorah, B. O., Ahmed, A., Aldeyab, M. A., Allel, K., Ancuceanu, R., Anyasodor, A. E., Ausloos, M., Barra, F., Bhagavathula, A. S., Bhandari, D., Bhaskar, S., Cruz-Martins, N., Dastiridou, A., Dokova, K., Dubljanin, E., Durojaiye, O. C., Fagbamigbe, A. F., Ferrero, S., Gaal, P. A., Gupta, V. B., Gupta, V. K., Gupta, V. K., Herteliu, C., Hussain, S., Ilic, I. M., Ilic, M. D., Jamshidi, E., Joo, T., Karch, A., Kisa, A., Kisa, S., Kostyanev, T., Kyu, H. H., Lám, J., Lopes, G., Mathioudakis, A. G., Mentis, A.-F. A., Michalek, I. M., Moni, M. A., Moore, C. E., Mulita, F., Negoi, I., Negoi, R. I., Palicz, T., Pana, A., Perdigão, J., Petcu, I.-R., Rabiee, N., Rawaf, D. L., Rawaf, S., Shakhmardanov, M. Z., Sheikh, A., Silva, L. M. L. R., Skryabin, V. Y., Skryabina, A. A., Socea, B., Stergachis, A., Stoeva, T. Z., Sumi, C. D., Thiyagarajan, A., Tovani-Palone, M. R., Yesiltepe, M., Zaman, S. B., & Naghavi, M.
Affiliations
University of Washington (US)
Corresponding author
Naghavi, Mohsen
ORCID
Venue
The Lancet Public Health
Publisher
Elsevier BV
Published
2022-11
Volume
7
Issue
11
Pages
e897-e913
ISSN
2468-2667 (ISSN-L)
DOI
10.1016/s2468-2667(22)00225-0
PMC
PMC9630253
OpenAlex
W4306175007
Cited by
384
References
24
Citations by year
2026: 87 · 2025: 91 · 2024: 112 · 2023: 86 · 2022: 8
FWCI
48.05
Type
journal article
Language
en
Open access
Licence
Locations
  • The Lancet Public Health (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Huddersfield Research Portal (University of Huddersfield) (publishedVersion, cc-by)
  • edoc (University of Basel) (acceptedVersion)
  • St George's Online Research Archive (St George's University of London) (acceptedVersion)
  • Charles Sturt University Research Output (CRO) (submittedVersion, cc-by)
  • Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by)
  • Figshare (submittedVersion, cc-by)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
  • Research Explorer (The University of Manchester) (submittedVersion, other-oa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
  • St Andrews Research Repository (St Andrews Research Repository) (submittedVersion, cc-by)
  • edoc (University of Basel)
Funders
  • Bill and Melinda Gates Foundation (OPP1176062)
  • Wellcome Trust (A126042)
  • Manchester Biomedical Research Centre
  • National Authority for Scientific Research and Innovation
  • Autoritatea Natională pentru Cercetare Stiintifică (CEECIND/00394/2017, UID/DTP/04138/2019)
  • Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii (PN-III-P4-ID-PCCF-2016-0084)
  • National Health and Medical Research Council
  • Fundação para a Ciência e a Tecnologia
  • European Social Fund
  • Ministerul Cercetării, Inovării şi Digitalizării (CZ.02.2.69/0.0/0.0/18_053/0016952, ID-585-CTR-42-PFE-2021)
  • National Institute for Health and Care Research
Topics
  • Health Sciences › Medicine › Infectious Diseases › Antibiotic Use and Resistance
  • Health Sciences › Medicine › Microbiology (medical) › Antibiotic Resistance in Bacteria
  • Health Sciences › Medicine › Infectious Diseases › Antimicrobial Resistance in Staphylococcus
Keywords
antimicrobial resistance, bacterial infection, disease burden, mortality, disability-adjusted life years, bloodstream infection, intra-abdominal infection, respiratory infections, drug-resistant pathogens, counterfactual scenarios, WHO European Region, uncertainty intervals, infection duration, surveillance data, public health policy, health care costs, antimicrobial stewardship, infection control
MeSH terms
Anti-Bacterial Agents, Escherichia coli, Humans, World Health Organization, Drug Resistance, Bacterial, Methicillin-Resistant Staphylococcus aureus

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review