Review 1: "How Demographic Factors Matter for Antimicrobial Resistance – Quantification of the Patterns and Impact of Variation in Prevalence of Resistance by Age and Sex"

Andrew Shoubridge; Sophie Miller

doi:doi:10.1162/2e3983f5.4988e6d4

How demographic factors matter for antimicrobial resistance – quantification of the patterns and impact of variation in prevalence of resistance by age and sex

by Naomi R Waterlow, Ben S Cooper, Julie V Robotham, and Gwenan M Knight

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Published on Sep 26, 2023
www.medrxiv.org

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Abstract Background Antibiotic usage, contact with high transmission healthcare settings as well as changes in immune system function all vary by a patient’s age and sex. Yet, most analyses of antimicrobial resistance (AMR) ignore demographic indicators and provide only country level resistance prevalence values.In this work we use routine surveillance data on serious infections in Europe to characterise the importance of age and sex on incidence and resistance prevalence patterns for 33 different bacteria and antibiotic combinations. We fit Bayesian multilevel regression models to quantify these effects and provide estimates of country-, bacteria- and drug-family effect variation.Results At the European level, we find distinct patterns in resistance prevalence by age that have previously not been explored in detail. Trends often vary more within an antibiotic family than within a bacterium: clear resistance increases by age for methicillin resistant S. aureus (MRSA) contrast with a peak in resistance to several antibiotics at ∼30 years of age for P. aeruginosa. This diverges from the known, clear exponential increase in infection incidence rates by age, which are higher for males except for E. coli at ages 15-40.At the country-level, the patterns are highly context specific with national and subnational differences accounting for a large amount of resistance variation (∼38%) and a range of associations between age and resistance prevalence. We explore our results in greater depths for two of the most clinically important bacteria–antibiotic combinations. For MRSA, age trends were mostly positive, with 72% of countries seeing an increased resistance between males aged 1 and 100 and more resistance in males. This compares to age trends for aminopenicillin resistance in E. coli which were mostly negative (males: 93% of countries see decreased resistance between ages 1 and 100) with more resistance in females. A change in resistance prevalence between ages 1 and 100 ranged up to ∼0.46 (95% CI 0.37 – 0.51, males) for MRSA but varied between 0.16 (95% CI 0.23-0.3, females) to -0.27 (95%CI -0.4 - - 0.15, males) across individual countries for aminopenicillin resistance in E. coli.Conclusion Prevalence of resistance in infection varies substantially by the age and sex of the individual revealing gaps in our understanding of AMR epidemiology. These context-specific patterns should now be exploited to improve intervention targeting as well as our understanding of AMR dynamics.

RR:C19 Evidence Scale rating by reviewer:

Reliable. The main study claims are generally justified by its methods and data. The results and conclusions are likely to be similar to the hypothetical ideal study. There are some minor caveats or limitations, but they would/do not change the major claims of the study. The study provides sufficient strength of evidence on its own that its main claims should be considered actionable, with some room for future revision.

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Review: The importance to address the rising prevalence of antimicrobial resistance worldwide has been expanded upon by Waterlow et al. in this manuscript that describes a large population-level investigation. It is a well written manuscript that is transparent and clear in its aims, methodology and outcomes. Using data from 30 different countries across Europe, the authors have effectively demonstrated that the prevalence of antimicrobial resistance varies for specific bacteria-antibiotic combinations, namely methicillin resistant S. aureus and aminopenicillin resistant E. coli, depending on the age and sex of the individual. Variations were also observed between and within countries, highlighting the importance to consider individual-level characteristics when developing interventions that address the global health threat of antimicrobial resistance.

Decision-makers should consider the claims in this study reliable, based on the methods and data. Age and sex are clearly demonstrated to contribute to patterns of variance for resistance in bacteria-antibiotic combinations across Europe. Interestingly, the authors also demonstrate a large variation between countries across Europe for multiple bacteria-antibiotic combinations. Considering the authors conclude cultural factors may be more important to consider than biological ones, the differences between countries, for example socioeconomic status or healthcare systems (quality and access), could be investigated further or featured more prominently to strengthen the claims made by the authors.

The study would also benefit from further commentary around the justification of choice from a clinical perspective for the two featured bacteria-antibiotic combinations. In particular, aminopenicillin resistant E. coli and the source of infections and methods of transmission compared with the highly clinically-prevalent and -relevant carbapenem-resistant Acinetobacter or vancomycin-resistant Enterococci species.

Recognised as a limitation of the study by the authors and an area of importance for future work, individual-level patient data will be crucial to understand the mechanisms underlying variance in antimicrobial resistance, such as a person’s comorbidities and healthcare service usage.

Overall, the authors have provided valuable evidence that supports the need for future reporting, research and policy designers to consider individual characteristics in order to develop effective interventions for antimicrobial resistance.