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Interactive app allows users to explore data underlying estimates of global antimicrobial resistance burden

World map showing country-level AMR and related metrics

Providing a closer snapshot of health loss linked to antimicrobial resistance (AMR), the Global Research on Antimicrobial Resistance (GRAM) Project has released a visualization tool that measures worldwide AMR burden and related metrics—including pathogen and infectious syndrome deaths—by country, age, bacteria and antibiotic.

The tool, released by the GRAM partnership between the Institute for Health Metrics and Evaluation (IHME) and the University of Oxford, follows the team’s January report which estimated that bacterial AMR caused more than 1.2 million deaths in 2019. Read the study, ‘Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis’, in the Lancet.

Supported by the UK Fleming Fund, the Wellcome Trust, and the Bill and Melinda Gates Foundation, the GRAM findings described AMR as a leading cause of death, and an urgent problem in both low- and high-resource settings. Data collected by GRAM, and analyzed using methodologies from IHME’s ongoing Global Burden of Disease study, represent one of the most comprehensive AMR datasets available, with 471 million separate records.

The tool allows users to generate maps, graphs and other data collected by GRAM, including those showing AMR prevalence and mortality in 204 countries, and for 88 pathogen-and-antibiotic combinations.

In addition to resistance, the tool also allows viewers to explore estimates that researchers used to calculate the burden of AMR, including data on infectious syndromes and bacterial infections.

Users may review deaths and disability adjusted life years (DALYs) for seven infectious syndromes—including bloodstream and lower respiratory infections—by age and sex. The tool also lists deaths and DALYs by pathogen, including 33 bacteria, and several viruses and fungi.

GRAM researchers have cited lack of available data as a key limitation of their research. Indeed, limited data is available for many parts of the world, particularly low- and middle-income settings, where the estimated burden of AMR is greatest.