Global Burden: Morbidity, Mortality, and Economic Impact

Quantifying the burden of antimicrobial resistance translates resistance frequencies into measures of human and economic harm: how many illnesses and deaths are associated with or attributable to resistant infections, how many years of healthy life are lost, and what the costs are to health systems and economies. This topic examines how that burden is estimated and what current estimates show.

Definition

The global burden of antimicrobial resistance is the population-level estimate of the morbidity, mortality, and economic cost associated with or attributable to infections caused by antimicrobial-resistant organisms, expressed in deaths, disability-adjusted life-years, and financial impact.

Scope

The topic covers the concepts and methods of burden estimation — attributable versus associated mortality, disability-adjusted life-years, and economic costing — together with the principal global and regional estimates and their uncertainties. It is a methodological and descriptive overview of burden, not a forecast or a basis for clinical decisions.

Core questions

• How is the burden of resistance defined and measured?
• What is the difference between deaths associated with and deaths attributable to resistance?
• What do current global and regional estimates show?
• What are the main sources of uncertainty in these estimates?

Key concepts

• Attributable versus associated mortality
• Disability-adjusted life-years (DALYs)
• Counterfactual scenarios in burden modelling
• Direct and indirect economic costs
• Data gaps and surveillance coverage
• Pathogen- and region-specific burden
• Burden as a driver of policy

Mechanisms

Burden estimation combines surveillance data on the frequency of resistance with data on infection incidence and outcomes, then applies a counterfactual: comparing the observed harm with what would be expected if the infecting organisms were susceptible. This distinguishes deaths and illness attributable to resistance (the excess relative to a susceptible counterfactual) from those merely associated with resistant infection. Outcomes are summarized as deaths and as disability-adjusted life-years, which combine years of life lost with years lived with disability. Economic costing adds direct healthcare costs and broader productivity losses. Because the underlying surveillance and outcome data are incomplete, especially in low-resource settings, estimates carry substantial uncertainty.

Clinical relevance

Burden estimates explain why antimicrobial resistance is treated as a major public-health priority and motivate investment in stewardship, infection prevention, surveillance, and new antimicrobials. This topic describes population-level harm and its measurement; it does not provide guidance for treating individual patients.

Epidemiology

Modelling work attributes a large number of deaths to bacterial antimicrobial resistance globally, with the heaviest relative burden in regions with weaker health and surveillance infrastructure and with most deaths concentrated among a limited set of pathogens. Regional analyses, such as those for the European Union and European Economic Area, provide more granular attributable estimates, and influential reports have projected substantial future health and economic costs if resistance is left unchecked.

History

Early concern about the consequences of resistance was largely qualitative; rigorous global burden estimation is more recent, emerging as surveillance data and modelling methods matured. A widely cited 2016 review framed resistance as a major future threat to health and economies, and subsequent population-level modelling produced systematic global and regional estimates of attributable deaths and disability-adjusted life-years.

Debates

How should attributable burden be estimated, and how certain are the figures?

Estimates depend on the counterfactual chosen and on incomplete underlying data, so widely cited numbers carry wide uncertainty intervals; distinguishing burden attributable to resistance from burden associated with resistant infection remains methodologically demanding.

Seminal works

• murray-2022
• cassini-2019
• oneill-2016

Frequently asked questions

What is the difference between deaths 'attributable to' and deaths 'associated with' resistance?

Deaths attributable to resistance are the excess deaths estimated to occur because the organism was resistant rather than susceptible, whereas deaths associated with resistance include all deaths in people who had a resistant infection regardless of whether resistance itself caused the death; the attributable figure is smaller and harder to estimate.

Why do burden estimates carry large uncertainty?

They depend on incomplete surveillance and outcome data, especially in low-resource settings, and on modelling assumptions such as the susceptible counterfactual, all of which widen the uncertainty around the resulting figures.