Global policy responses to antimicrobial resistance, 2021–22: a systematic governance analysis of 161 countries and territories

Background

Most countries have endorsed a national action plan (NAP) on antimicrobial resistance. We previously used a governance framework to assess NAPs on antimicrobial resistance available for the period of 2020–21 from 114 countries, finding substantial variation worldwide in the commitment of resources to address an escalating global health challenge. We sought to expand and advance this analysis to include the NAPs of more low-income and middle-income countries, to cover the period of 2021–22, and to examine the strength of NAPs to address antimicrobial resistance.

Methods

In this systematic governance analysis, we searched ten repositories from their inception to April 1, 2023, to identify all publicly retrievable NAPs on antimicrobial resistance, with no language restrictions. Machine learning tools and artificial intelligence were used to translate all native-language NAPs into English. Three researchers independently conducted a detailed content analysis of new and updated NAPs on antimicrobial resistance. 22 057 datapoints were mapped against a governance framework and a numerical system was developed to quantify country scores for 54 indicators, 18 domains, and three governance areas. We applied principal component analysis to construct country scores between 0 and 100. Through Pearson's correlation coefficient, we evaluated the correlation between the country scores and various metrics pertaining to the burden of antibiotic-resistant infections from the IHME GRAM project.

Findings

161 countries and territories were included in this analysis, 47 more than the previous report. Governance scores varied across countries, with Norway achieving the highest score (score of 100) and Djibouti the lowest (score of 0). Generally, higher scores were seen in high-income countries (eg, France, USA, UK, Sweden, and Denmark), whereas lower scores were more common in low-income countries. High-income regions performed well across governance domains, whereas lower scores were seen in other regions (eg, Libya, Central African Republic, South Sudan, and Seychelles). Higher governance scores were significantly associated with a lower burden of antimicrobial resistance-associated disability-adjusted life-years (r=–0·469, p<0·001) and death (r=–0·477, p<0·001). Infection prevention and control (r=–0·532, Bonferroni-adjusted p<0·001), surveillance (r=–0·482, Bonferroni-adjusted p<0·001), and stewardship (r=–0·459, Bonferroni-adjusted p<0·001) were the domains most strongly correlated with a lower burden of drug-resistant infections.

Interpretation

The global response to antimicrobial resistance was greatly affected by the income level of the nation, highlighting global disparities in antimicrobial resistance governance capacity. Lower scores in lower-income regions likely reflect systemic challenges, such as less public health spending and less access clean water and santiation. Implementation tools should be prioritised in the design and execution of NAPs, especially measures that improve infection prevention and control, surveillance systems for antimicrobial use, and stewardship programmes.