Contribution of socio-economic factors in the spread of antimicrobial resistant infections in Australian primary healthcare clinics. (September 2022)

• Record Type: Journal Article
• Authors: Wozniak, Teresa M.; Cuningham, Will; Ledingham, Katie; McCulloch, Karen
• Is Part Of: Journal of global antimicrobial resistance. Volume 30(2022)
• Page Start: 294
• Page End: 301
• Publication Date: 2022-09
• Subjects: Antibiotic resistance -- Social determinants of health -- Australia -- Remoteness -- Disease surveillance; Drug resistance -- Periodicals; Drug resistance -- Periodicals; Drug resistance; Periodicals; 616.9041
• DOI: 10.1016/j.jgar.2022.06.005
• Languages: English
• ISSNs: 2213-7165

Abstract

Highlights: Exploration of AMR and social drivers from a high-burden, low-resource setting. Identifies AMR geographical variation across northern (tropical) Australia. Establishes correlation between AMR prevalence and access to health services. Explores repurposing disease surveillance to identify broader AMR containment solutions. Abstract: Objectives: To effectively contain antimicrobial-resistant (AMR) infections, we must better understand the social determinates of health that contribute to transmission and spread of infections. Methods: We used clinical data from patients attending primary healthcare clinics across three jurisdictions of Australia (2007–2019). Escherichia coli (E. coli ), Klebsiella pneumoniae (K. pneumoniae ), Pseudomonas aeruginosa ( P. aeruginosa ) and Staphylococcus aureus (S. aureus ) isolates and their corresponding antibiotic susceptibilities were included. Using multivariable logistic regression analysis, we assessed associations between AMR prevalence and indices of social disadvantage as reported by the Australian Bureau of Statistics (i.e., remoteness, socio-economic disadvantage and average person per household). Results: This study reports 12 years of longitudinal data from 43 448 isolates from a high-burden low-resource setting in Australia. Access to health and social services (as measured by remoteness index) was a risk factor for increased prevalence of third-generation cephalosporin-resistant (3GC) E. coli (odds ratio 5.05; 95% confidence interval 3.19, 8.04) and methicillin-resistant S. aureus (MRSA) (odds ratio 5.72; 95% confidence interval 5.02, 6.54). We did not find a positive correlation of AMR and socio-economic disadvantage or average person per household indices. Conclusion: Remoteness is a risk factor for increased prevalence of 3GC-resistant E. coli and MRSA. We demonstrate that traditional disease surveillance systems can be repurposed to capture the broader social drivers of AMR. Access to pathogen-specific and social data early and within the local regional context will fill a significant gap in disease prevention and the global spread of AMR.