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Global Economic Impacts of Antimicrobial Resistance

Author

Listed:
  • Roshen Fernando
  • Warwick McKibbin

Abstract

Antimicrobial resistance (AMR) is a growing global health threat that led to 1.27 million deaths in 2019. Given the widespread use of antimicrobials in healthcare, agriculture, and industrial applications and a range of factors affecting AMR, including demographic trends and physical climate risks, an economy-wide approach is essential to understand and assess the economic consequences of AMR. We model the global economic impacts of AMR under six alternative scenarios. These scenarios are designed to incorporate assumptions about changes in AMR-related disease incidence, the impact of a central scenario about future demographic change on AMR over time, and explore the sensitivity of assumptions about the effects of AMR on agriculture productivity. We also examine the additional impacts of changing climate risks on the evolution of AMR (focusing on one climate scenario), the consequences of changes in country risk premia due to the differential im-pacts of the evolution of AMR on countries, and the global economic impacts of changes in government expenditure in response to AMR. Our results find a significant global economic burden of worsening AMR due to demographic change and climate change risks, as well as significant eco-nomic benefits of taking action to address AMR. We emphasize that a “one-health†approach to managing AMR will have substantial economic benefits over the coming decades.

Suggested Citation

  • Roshen Fernando & Warwick McKibbin, 2024. "Global Economic Impacts of Antimicrobial Resistance," CAMA Working Papers 2024-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2024-41
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    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2024-06/41_2024_fernando_mckibbin.pdf
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    More about this item

    Keywords

    antimicrobial resistance; antibiotic resistance; infectious diseases; macroeconomic modelling;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F01 - International Economics - - General - - - Global Outlook
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • I10 - Health, Education, and Welfare - - Health - - - General

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