Picture of virus under microscope

Research under the microscope...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

Explore SIPBS research

Antimicrobial resistance: a microbial risk assessment perspective

Snary, E.L. and Kelly, L.A. and Davison, H. and Teale, C.J. and Wooldridge, M. (2004) Antimicrobial resistance: a microbial risk assessment perspective. Journal of Antimicrobial Chemotherapy, 53 (6). pp. 906-917. ISSN 0305-7453

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

The emergence of antimicrobial-resistant microorganisms in both humans and food animals is a growing concern. Debate has centred on links between antimicrobial use in the production of food animals and the emergence of resistant organisms in the human population. Consequently, microbial risk assessment (MRA) is being used to facilitate scientific investigations of the risks related to the food chain, including quantification of uncertainty and prioritization of control strategies. MRA is a scientific tool that can be used to evaluate the level of exposure and the subsequent risk to human health relating to a specific organism or particular type of resistance. This paper reviews the recent applications of MRA in the area of antimicrobial resistance, and in particular, it focuses on the methods, assumptions and data limitations. Since MRA outputs are dependent on the quality of data inputs used in their development, we aim to promote the generation of good quality data by describing the properties that data should ideally possess for MRA and by highlighting the benefit of data generation specifically for inclusion in MRAs.