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

Abstract

Background. Infections by antibiotic-resistant Enterobacterales are a public health threat worldwide. While dissemination of these opportunistic pathogens has been largely studied in hospitals, less is known about their acquisition and spread in the community. Here, we aim to characterize mechanistic hypotheses and scientific contributions of mathematical modeling studies focusing on antibiotic-resistant Enterobacterales in the community. Methods. We conducted a systematic review of mathematical modeling studies indexed in PubMed and focusing on the transmission of antibiotic-resistant Enterobacterales in the community (i.e., excluding models only specific to hospitals). For each study, we extracted model features (host population, setting), formalism (compartmental, individual-based), biological hypotheses (transmission, infection, antibiotic use impact, resistant strain specificities) and main findings. We discussed additional mechanisms to be considered, open scientific questions, and most pressing data needs to further improve upon existing epidemiological modeling. Results. We identified 18 modeling studies focusing on the human transmission of antibiotic-resistant Enterobacterales in the community (n=11) or in both community and hospital (n=7). Models aimed at: (i) understanding mechanisms driving resistance dynamics; (ii) identifying and quantifying transmission routes; or (iii) evaluating public health interventions to reduce resistance. Studies highlighted that community transmission, compared to hospital transmission, play a significant role in the overall acquisition of antibiotic-resistant Escherichia coli. Predictions across models regarding the success of public health interventions to reduce resistance rates depended on pathogens, settings, and antibiotic resistance mechanisms. For E. coli, lowered person-to-person transmission led to greater reduction in antibiotic resistance rates compared to lowered antibiotic use in the community (n=2). For Klebsiella pneumoniae lowered antibiotic use in the hospital led to greater reduction compared to lowered use in the community (n=2). Finally, we reported a moderate number of modeling studies inferring parameters from empirical data (n=9), probably due to a critical lack of available data for antibiotic resistance rates in the community. Conclusions. We found a limited number of modeling studies addressing the transmission of antibiotic-resistant Enterobacterales in the community, highlighting a need for model development and extensive community-based data collection. Such modeling will be critical to better understand the spread of antibiotic-resistant Enterobacterales in the community and design public health interventions specific to this setting.