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salmonella antibiotic resistance
Salmonella is a common, widely distributed bacterium that causes food-borne disease which has a major impact on both human and animal health. The development of antimicrobial resistance in Salmonella is an increasing problem, and resistant strains are widespread.
Understanding of the epidemiology of Salmonella antimicrobial resistance is limited. Knowledge of the burden of resistant and multi-resistant strains of Salmonella in livestock populations and an understanding of risk factors for infection are necessary for the management and control of resistance in both human and animal populations. Critical to this is an understanding of the role played by temporal and spatial factors in the epidemiology of epidemic strains.
Similar antimicrobial resistance patterns occurring at similar periods in time (‘temporal components’) or locations (‘spatial components’) may reflect the effect of unmeasured explanatory variables or might provide evidence of a contagious mechanism. In either case, they have a potentially important role to play in veterinary surveillance and hence in the design and implementation of effective control strategies.
Our research focuses on understanding temporal and spatial patterns of antimicrobial resistance in Salmonella outbreaks in farm animal species.
Recently we have conducted a detailed evaluation of the VLA Farmfile database which documents antimicrobial resistance in all incidents of Salmonella in the UK. We have identified that antimicrobial resistance, including multiresistance, was common in the UK, particularly in cattle and pigs between 2003 and 2006.
We have also demonstrated temporal patterns in antimicrobial resistance, including evidence of trend and seasonal variation in both cattle and pigs for a number of antimicrobials. Finally we have found some evidence of spatial structure in the occurrence of resistance.
Having identified that species and time are both risk factors for antimicrobial resistance, we are now investigating other potential risk factors such as age group, type of herd, breed or previous infection.
Future research focuses on multiresistance. We have used techniques such as cluster analysis to assess the relationship between different resistance patterns and we are developing more sophisticated modelling that will investigate resistance to a combination of antimicrobials as a function of geographical distance, while taking into account other risk factors.
Funding was provided by Defra
