Elicit: Burden of AMR by Region (public)
What is the burden of disease for AMR by geographic region?
AMR caused 4.71M associated deaths globally in 2021, with regional distribution showing approximately 541,000 deaths in Europe, 569,000 in the Americas, and varying country-specific impacts.
Abstract
Antimicrobial resistance (AMR) exacts a heavy toll that varies by region. Global cross‐country studies report that in 2021 AMR was linked with 4.71 million deaths (range: 4.23–5.19 million) and 1.14 million deaths were directly attributable to resistance (range: 1.00–1.28 million); projections for 2050 reach 8.22 million associated and 1.91 million attributable deaths, with an estimated 46.5 million disability‐adjusted life years lost. In the WHO European region, estimates include 541,000 associated and 133,000 attributable deaths, while in the Americas figures of 569,000 associated and 141,000 attributable deaths have been documented. Country-specific data further detail the burden; for example, one study from Japan notes 14,300 deaths linked to MRSA and a study from China reports 711,852 associated deaths.
Key pathogens driving these outcomes include Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Acinetobacter baumannii. Findings further indicate that gram-negative resistance is often shaped by carbapenem-resistant pathogens, whereas MRSA predominates the gram-positive burden. Economic and healthcare impacts have been quantified in several settings—for instance, incremental costs of US$2 billion for MRSA in Japan, increases in hospital stays ranging from 1.6 to over 8 additional days, and societal economic burdens reaching billions in local currencies. These studies collectively underscore a substantial and regionally variable disease burden due to AMR.
Methods
We analyzed 25 sources from an initial pool of 496, using 7 screening criteria. Each paper was reviewed for 5 key aspects that mattered most to the research question. More on methods
Papers identified with Elicit search
- n = 496
- Papers screened using: Burden Metrics, Study Population, Geographic Context, Study Design, Pathogen Focus, Outcome Specificity, Sample Size
- n = 496
- Papers screened out
- n = 471
- Papers included for extraction
- n = 25
Paper search
Using your research question “What is the burden of disease for AMR by geographic region?”, we searched across over 126 million academic papers from the Semantic Scholar corpus. We retrieved the 496 papers most relevant to the query.
Screening
We screened in sources based on their abstracts that met these criteria:
- Burden Metrics: Does the study report at least one AMR burden metric (mortality, morbidity, healthcare costs, length of hospital stay, or disability-adjusted life years)?
- Study Population: Does the study examine human populations in any healthcare setting (community, hospital, or long-term care)?
- Geographic Context: Does the study specify a clear geographic region or country where the research was conducted?
- Study Design: Is the study a primary research study, systematic review, or meta-analysis containing empirical data?
- Pathogen Focus: Does the study report on bacterial pathogen(s) with antimicrobial resistance?
- Outcome Specificity: Does the study report specific burden outcomes beyond just prevalence or resistance mechanisms?
- Sample Size: Does the study include 10 or more cases/participants?
We considered all screening questions together and made a holistic judgement about whether to screen in each paper.
Data extraction
We asked a large language model to extract each data column below from each paper:
- Study Design:
Identify the specific type of study design used:
- Systematic analysis
- Cross-country analysis
- Epidemiological study
- Burden of disease study
Look in the methods section for explicit description of the study design. If multiple design elements are present, list all that apply. If the design is not clearly stated, write “Not clearly specified” and note the closest matching description from the text.
- Geographic Scope:
Record the specific geographic regions or countries included in the analysis:
- Total number of countries/territories studied
- Specific regions or countries named
- Any stratification by region (e.g., WHO regions)
Extract this information from the methods or background sections. If multiple geographic scopes are mentioned, list all. Ensure to capture the full geographic coverage of the study.
- Antimicrobial Resistance (AMR) Burden Metrics:
Extract the specific AMR burden metrics used in the study:
- Deaths associated with AMR
- Deaths attributable to AMR
- Disability-adjusted life years (DALYs)
- Years of life lost (YLLs)
- Years lived with disability (YLDs)
Record the numerical values with their 95% uncertainty intervals. Look in the results section for precise figures. If multiple metrics are reported, list all with their corresponding values.
- Pathogens and Drug Resistance:
List the key pathogens and drug resistance combinations studied:
- Number of bacterial pathogens examined
- Number of pathogen-drug combinations
- Top pathogens by mortality
- Most significant drug resistance types
Extract this information from the findings or results sections. Prioritize listing pathogens in order of their mortality impact. If a ranking is provided, use that order.
- Time Period of Analysis:
Record the specific time periods covered in the study:
- Historical data collection period
- Year of primary analysis
- Future projection period (if applicable)
Look in the methods and background sections for explicit time frames. If multiple time periods are mentioned, list all. Pay special attention to any historical trend analysis or future forecasting components.
Results
Characteristics of Included Studies
| Study | Study Design | Geographic Coverage | Burden Metrics | Key Pathogens Studied | Full text retrieved |
|---|---|---|---|---|---|
| Naghavi et al., 2024 | Burden of disease, systematic, cross-country | 204 countries, global, Global Burden of Disease (GBD) superregions | Deaths associated/attributable, Disability-Adjusted Life Years (DALYs) | 22 pathogens, 84 combinations; Staphylococcus aureus, Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa | Yes |
| Uematsu et al., 2017 | Epidemiological, burden of disease | Japan (nationwide) | In-hospital mortality, costs, length of stay | Methicillin-resistant Staphylococcus aureus (MRSA) | Yes |
| Otieku et al., 2023 | Epidemiological, prospective cohort | Ghana (2 hospitals) | Mortality, length of stay, patient costs | Escherichia coli, Klebsiella species, MRSA | Yes |
| Li et al., 2022 | Burden of disease, cross-country, systematic | Global, 204 countries, 21 GBD regions | Deaths associated/attributable, DALYs, Years of Life Lost (YLLs), Years Lived with Disability (YLDs) | 14 pathogens, 66 combinations; Escherichia coli, Klebsiella pneumoniae | Yes |
| Meštrović et al., 2022 | Systematic, cross-country, burden of disease | World Health Organization (WHO) European region (53 countries) | Deaths associated/attributable | 23 pathogens, 88 combinations; Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterococcus faecium, Streptococcus pneumoniae, Acinetobacter baumannii | No |
| Aguilar et al., 2023 | Cross-country, systematic, burden of disease, epidemiological | Americas (35 countries) | Deaths associated/attributable | 23 pathogens, 88 combinations; Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii | No |
| Murray et al., 2022 | Systematic, burden of disease, cross-country | Global, 204 countries | Deaths associated/attributable | 23 pathogens, 88 combinations; Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa | No |
| Lewandrowski et al., 2024 | Burden of disease, cross-country | Global, 195 countries | DALYs, YLLs, YLDs | Staphylococcus aureus, Group A/B Streptococcus, Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterobacter | No |
| Tsuzuki et al., 2021 | Burden of disease, epidemiological, cross-country | Japan | Deaths attributable, DALYs, YLLs | MRSA, fluoroquinolone-resistant Escherichia coli (FQREC), third-generation cephalosporin-resistant Escherichia coli (3GREC), third-generation cephalosporin-resistant Klebsiella pneumoniae (3GRKP), carbapenem-resistant Pseudomonas aeruginosa (CRPA), penicillin-resistant Streptococcus pneumoniae (PRSP) | Yes |
| Waterlow et al., 2025 | Burden of disease, cross-country, systematic, epidemiological | Europe | No mention found | 8 bacteria, 38 combinations; aminoglycoside-resistant Acinetobacter species (example) | No |
Study Design
- Systematic, cross-country, or meta-analytic designs: 16 studies.
- Epidemiological designs (including prospective cohort and case-control): 15 studies.
Geographic Coverage
- Global coverage: 7 studies.
- Europe or European countries: 7 studies.
- Asia: 8 studies (Japan: 3, China: 2, Thailand: 2, 1 with Asia focus).
- Africa: 2 studies (Ghana and Uganda).
- Americas: 3 studies (Americas region, Canada, United States).
Burden Metrics
- Deaths associated or attributable to antimicrobial resistance: 14 studies.
- Disability-Adjusted Life Years (DALYs): 6 studies.
- Years of Life Lost (YLLs): 5 studies.
- Years Lived with Disability (YLDs): 2 studies.
- Mortality (in-hospital or general): 2 studies.
- Costs and length of stay: Each reported in 2 studies.
- No mention found for burden metrics: 7 studies.
- Multiple metrics: Some studies reported more than one metric.
Key Pathogens Studied
- More than 10 pathogens or combinations: 9 studies.
- Escherichia coli: 12 studies.
- Staphylococcus aureus: 9 studies.
- Klebsiella pneumoniae: 9 studies.
- MRSA: 8 studies.
- Acinetobacter baumannii: 7 studies.
- Streptococcus pneumoniae: 6 studies.
- Pseudomonas aeruginosa: 8 studies.
Global and Regional Disease Burden
Mortality Burden
| Study | Geographic Region | Annual Deaths (Associated/Attributable) | DALYs | Leading Resistant Pathogens |
|---|---|---|---|---|
| Naghavi et al., 2024 | Global, 204 countries | 2021: 4.71 million (associated, 4.23–5.19 million); 1.14 million (attributable, 1.00–1.28 million); 2050: 8.22 million (associated), 1.91 million (attributable) | 2050: 46.5 million (37.7–57.3 million) | Staphylococcus aureus, Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa |
| Uematsu et al., 2017 | Japan | 14,300 deaths (associated) | No mention found | MRSA |
| Otieku et al., 2023 | Ghana | 15.4% mortality (antimicrobial resistance cohort) | No mention found | Escherichia coli, Klebsiella species, MRSA |
| Li et al., 2022 | Global/regions | 2019: 0.26 million (associated, 0.18–0.36 million); 64,890 (attributable, 45,860–93,350) | No mention found | Escherichia coli, Klebsiella pneumoniae |
| Meštrović et al., 2022 | WHO Europe | 541,000 (associated, 370,000–763,000); 133,000 (attributable, 90,000–188,000) | No mention found | Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterococcus faecium, Streptococcus pneumoniae, Acinetobacter baumannii |
| Aguilar et al., 2023 | Americas | 569,000 (associated, 406,000–771,000); 141,000 (attributable, 99,900–196,000) | No mention found | Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii |
| Murray et al., 2022 | Global | 4.95 million (associated, 3.62–6.57 million); 1.27 million (attributable, 0.91–1.71 million) | No mention found | Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa |
| Lewandrowski et al., 2024 | Global | No mention found | DALYs, YLLs, YLDs (no values) | Staphylococcus aureus, Group A/B Streptococcus, Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterobacter |
| Tsuzuki et al., 2021 | Japan | 9,447 (attributable, 2018) | 135.8 per 100,000 (128.6–142.9) | MRSA, fluoroquinolone-resistant Escherichia coli (FQREC), third-generation cephalosporin-resistant Escherichia coli (3GREC), third-generation cephalosporin-resistant Klebsiella pneumoniae (3GRKP), carbapenem-resistant Pseudomonas aeruginosa (CRPA), penicillin-resistant Streptococcus pneumoniae (PRSP) |
| Waterlow et al., 2025 | Europe | No mention found | No mention found | No mention found |
Geographic Region
- Global scope: 7 studies.
- Regional: 3 studies (Europe, Americas, WHO Europe).
- Country-specific: 15 studies (Japan: 3, China: 2, Thailand: 2, Spain: 2, Ghana, Uganda, France, United Kingdom/Norway, Canada, United States: 1 each).
Annual Deaths (Associated/Attributable)
- Both associated and attributable death estimates: 7 studies.
- Only associated death estimates: 2 studies.
- Only attributable death estimates: 2 studies.
- Only mortality rates or percentages: 2 studies.
- Death counts without associated/attributable distinction: 4 studies.
- No mention found for death data: 8 studies.
Leading Resistant Pathogens
- Escherichia coli: 11 studies.
- Staphylococcus aureus: 9 studies.
- Klebsiella pneumoniae: 9 studies.
- Acinetobacter baumannii: 7 studies.
- Pseudomonas aeruginosa: 7 studies.
- Streptococcus pneumoniae: 5 studies.
- MRSA: 8 studies.
Disability-Adjusted Life Years (DALYs)
- DALY values found: 2 studies.
- Mention of DALYs without values: 1 study.
- No mention found for DALY data: Remaining studies.