Transmission routes of antibiotic resistant bacteria: a systematic review

Abstract

Background Quantification of acquisition routes of antibiotic resistant bacteria (ARB) is pivotal for understanding transmission dynamics and designing cost-effective interventions. Different methods have been used to quantify the importance of transmission routes, such as relative risks, odds ratios (OR), genomic comparisons and basic reproduction numbers. We systematically reviewed reported estimates on acquisition routes’ contributions of ARB in humans, animals, water and the environment and assessed the methods used to quantify the importance of transmission routes. Methods PubMed and EMBASE were searched, resulting in 6054 articles published up until January 1st, 2019. Full text screening was performed on 525 articles and 277 are included. Results We extracted 718 estimates with S. aureus (n = 273), E. coli (n = 157) and Enterobacteriaceae (n = 99) being studied most frequently. Most estimates were derived from statistical methods (n = 560), mainly expressed as risks (n = 246) and ORs (n = 239), followed by genetic comparisons (n = 85), modelling (n = 62) and dosage of ARB ingested (n = 17). Transmission routes analysed most frequently were occupational exposure (n = 157), travelling (n = 110) and contacts with carriers (n = 83). Studies were mostly performed in the United States (n = 142), the Netherlands (n = 87) and Germany (n = 60). Comparison of methods was not possible as studies using different methods to estimate the same route were lacking. Due to study heterogeneity not all estimates by the same method could be pooled. Conclusion Despite an abundance of published data the relative importance of transmission routes of ARB has not been accurately quantified. Links between exposure and acquisition are often present, but the frequency of exposure is missing, which disables estimation of transmission routes’ importance. To create effective policies reducing ARB, estimates of transmission should be weighed by the frequency of exposure occurrence.

Using intersectionality to study gender and antimicrobial resistance in low- and middle-income countries

“…One of the most common transmission routes for DROs is human contact with contaminated food ( Godijk et al. , 2022 ).…”

“…In low- and middle-income countries (LMICs), evidence suggests that the main drivers of AMR include the misuse and overuse of antimicrobials; lack of access to clean water, sanitation and hygiene (WASH); limited resources for infection prevention and control (IPC) in healthcare facilities and farms; limited access to quality, affordable medicines, vaccines and diagnostics; lack of awareness and knowledge and lack of enforcement of legislation ( WHO, 2021a ). The most common transmission routes for drug-resistant organisms (DROs) include human-to-human transmission, contact with contaminated medical equipment, medical waste, human–animal interaction, environmental exposure and contaminated food ( Godijk et al. , 2022 ).…”

Limited evidence of spill over of antimicrobial resistantKlebsiella pneumoniaefrom animal/environmental reservoirs to humans in India

“…13,14 An integrated approach of whole genome sequencing (WGS) and phylogenetic analysis has proven to be an effective tool in determining AMR transmission pathways. 15,16,17,18 One-Health genomic surveillance studies have previously been used to gain a better understanding of AMR transmission at the human-animal-environment interface. 10,19 Here, we used comparative genome analysis of clinical isolates of K. pneumoniae from a tertiary-care teaching hospital with non-clinical isolates collected from livestock and wastewater samples from Vellore in Southern India.…”

Modeling the transmission of antibiotic-resistant Enterobacterales in the community: a systematic review

“…It is also unclear how bacterial persistence in the environment contributes to maintain community transmission. 15,21 Mathematical modeling can help make sense of the scarce data available and disentangle the various mechanisms potentially contributing to observed dynamics.…”