This table provides metadata for the actual indicator available from United States statistics closest to the corresponding global SDG indicator. Please note that even when the global SDG indicator is fully available from American statistics, this table should be consulted for information on national methodology and other American-specific metadata information.
This table provides information on metadata for SDG indicators as defined by the UN Statistical Commission. Complete global metadata is provided by the UN Statistics Division.
Indicator |
Indicator 3.d.2: Percentage of bloodstream infections due to selected antimicrobial-resistant organisms |
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Target |
Target 3.d: Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risks |
Organisation |
World Health Organization (WHO) |
Definition and concepts |
Percentage of bloodstream infection due to methicillin-resistant Staphylococcus aureus (MRSA) and Escherichia coli resistant to 3rd-generation cephalosporin (e.g., ESBL- E. coli) among patients seeking care and whose blood sample is taken and tested.
1 EUCAST guidelines for detection of resistance mechanisms and specific resistances of clinical and/or epidemiological importance. Version 2.0. 2017. Both for species identification and antimicrobial susceptibility testing (AST) CLSI. M100 Performance Standards for Antimicrobial Susceptibility Testing. 29th ed2018 https://clsi.org/standards/products/microbiology/documents/m100/ ↑ |
Data sources |
Preferred sources: National AMR data collected through the national AMR surveillance system and reported to GLASS.
GLASS provides a standardised approach to the collection, analysis, and sharing of AMR data by countries, and seeks to document the status of existing or newly developed national AMR surveillance systems. Furthermore, GLASS promotes a shift from surveillance approaches based solely on laboratory data to a system that includes epidemiological, clinical, and population-level data. GLASS also collaborates with regional and national AMR surveillance networks to produce timely and comprehensive data. Collaboration with the UN Food and Agriculture Organization (FAO) and the World Organisation for Animal Health (OIE) – which together with WHO form the Tripartite Collaboration – is ongoing to improve a comprehensive understanding of AMR across sectors and to promote the One Health Approach to AMR control.
GLASS also collects information on the status of national AMR surveillance systems through a short questionnaire completed by AMR national focal points (NFPs) in each country. The questionnaire covers three main areas: 1) overall coordination; 2) surveillance system; and 3) quality control. Each area consists of a set of indicators developed to measure development and strengthening of national AMR surveillance.
Other possible data sources: Published and non-published data from national centres and research/academic institutions and from others regional surveillance networks. |
Data providers |
Ministries of Health
|
Comment and limitations |
AMR is an emerging global threat and risk to public health worldwide. In its early implementation phase of the global antimicrobial resistance surveillance system (GLASS), WHO recognizes various constraints in obtaining unbiased, representative AMR data: number and distribution of surveillance sites and representativeness of surveillance data, sampling bias, poor diagnostic capacity, measurements errors, issues with data management. It is imperative that countries should have a functioning national system to support AMR surveillance and report to GLASS. More detailed GLASS methodology and limitations of data currently submitted by countries can be found in the GLASS report[6]. AMR surveillance, country preparedness and response are now high priority for WHO and its Member States. In the next five years, WHO aims to provide intensified technical assistance. Experience gained and lessons learnt from the further implementation of the national AMR surveillance systems will increase effectiveness, address limitations, and the make the data more robust. 6 Global antimicrobial resistance surveillance system (GLASS) report: Early implementation 2017-2018 (2019). https://apps.who.int/iris/bitstream/handle/10665/279656/9789241515061-eng.pdf ↑ |
Method of computation |
The WHO Global AMR Surveillance System (GLASS) supports countries to implement an AMR standardized surveillance system. Cases of AMR infection are found among patients from whom routine clinical samples have been collected for blood culture at surveillance sites (health care facility) according to local clinical practices, and antimicrobial susceptibility tests (AST) are performed for the isolated blood pathogens as per international standards[7]. The microbiological results (bacteria identification and AST) are de-duplicated and combined with the patient data and related to population data from the surveillance sites. GLASS does collect information on the origin of the infection, either community origin (less than 2 calendar days in hospital) or hospital origin (patients hospitalized for more than 2 calendar days). Data are collated and validated at national level and reported to GLASS where epidemiological statistics and metrics are generated. GLASS has published guidelines on the set up of national AMR surveillance systems[8] and the GLASS methodology implementation manual[9] is available to countries. Although national representativeness of generated AMR rates is not a strict requirement, GLASS encourages countries to derive representative national data. Formulation of the proposed new indicator: Proportion of patients with Percentage of bloodstream infections due to selected antimicrobial resistant organisms. This is derived from the following and multiplied by 100[10]: Numerator: Number of patients with growth of methicillin-resistant S. aureus or E. coli resistant to third generation cephalosporins in tested blood samples Denominator: Total number of patients with growth of S. aureus or E. coli in tested blood samples
Stratification: The data are stratified by gender, and age group. Data are aggregated at the country level. Data are analysed and reported according to whether specimen is within 2 calendar days of admission (community origin) or after 2 calendar days of admission (hospital origin).
7 EUCAST, ≪EUCAST guidelines for detection of resistance mechanisms and specific resistances of clinical and/or epidemiological importance,≫ 2013, Available: http://www.amcli.it/wp-content/uploads/2015/10/ EUCAST_detection_resistance_mechanisms_V1.pdf . CLSI, ≪M100 Performance Standards for Antimicrobial Susceptibility Testing,≫ 27th ed, 2017. ↑ 8 National antimicrobial resistance surveillance systems and participation in the Global Antimicrobial Resistance Surveillance System (GLASS): A guide to planning, implementation, and monitoring and evaluation (2016). https://www.who.int/glass/resources/publications/national-surveillance-guide/en/ ↑ 9 Global Antimicrobial Resistance Surveillance System: Manual for Early Implementation (2015). https://www.who.int/antimicrobial-resistance/publications/surveillance-system-manual/en/ ↑ 10 Both for species identification and antimicrobial susceptibility testing (AST) ↑ |
Metadata update |
2021-04-01 |
International organisations(s) responsible for global monitoring |
World Health Organization (WHO) |