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Quantifying where human acquisition of antibiotic resistance occurs: a mathematical modelling study.
- Gwenan M Knight, Céire Costelloe, Sarah R Deeny, MooreLuke S PLSPNational Institute of Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Diseases, Imperial College London, London, W12 0NN, UK.Imperial College Health, Susan Hopkins, Alan P Johnson, Julie V Robotham, and Alison H Holmes.
- National Institute of Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Diseases, Imperial College London, London, W12 0NN, UK. gwen.knight@lshtm.ac.uk.
- Bmc Med. 2018 Aug 23; 16 (1): 137.
BackgroundAntibiotic-resistant bacteria (ARB) are selected by the use of antibiotics. The rational design of interventions to reduce levels of antibiotic resistance requires a greater understanding of how and where ARB are acquired. Our aim was to determine whether acquisition of ARB occurs more often in the community or hospital setting.MethodsWe used a mathematical model of the natural history of ARB to estimate how many ARB were acquired in each of these two environments, as well as to determine key parameters for further investigation. To do this, we explored a range of realistic parameter combinations and considered a case study of parameters for an important subset of resistant strains in England.ResultsIf we consider all people with ARB in the total population (community and hospital), the majority, under most clinically derived parameter combinations, acquired their resistance in the community, despite higher levels of antibiotic use and transmission of ARB in the hospital. However, if we focus on just the hospital population, under most parameter combinations a greater proportion of this population acquired ARB in the hospital.ConclusionsIt is likely that the majority of ARB are being acquired in the community, suggesting that efforts to reduce overall ARB carriage should focus on reducing antibiotic usage and transmission in the community setting. However, our framework highlights the need for better pathogen-specific data on antibiotic exposure, ARB clearance and transmission parameters, as well as the link between carriage of ARB and health impact. This is important to determine whether interventions should target total ARB carriage or hospital-acquired ARB carriage, as the latter often dominated in hospital populations.
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