Salmonella Typhimurium definitive type 104 (ST DT104) isolates resistant to antibiotics have been an issue since the multi-resistant clone was identified in 1985. In order to advance understanding of ST DT104 infections in Scotland, 2,796 human and 2,439 animal isolates with their corresponding antibiotic resistance patterns submitted from 1988 to 2004 were used to conduct descriptive, hierarchical, and geographical cluster studies and to construct a time series model. The analyses showed that using the 13 antibiotics used by the Scottish Salmonella Reference Laboratory, isolates could be allocated into two distinct groups. The first group containing the ApC1SpStSuTe R-type with its associated resistance patterns, mainly the ApCISpStSuTeTm and the ApCISpStSuTeNa R-types, dominated the trend throughout the study period. The second group, mainly composed of fully sensitive isolates, formed a low proportion except during the period from 1988 to 1990. Temporal analyses showed that there was an epidemic from 1993 to 1998 in human ST DT104 and from 1992 to 1999 in animals. Spatial analysis identified the southern part of Scotland as the higher relative risk area for both human and animal infections caused by multi-resistant ST DT104 strains In contrast, the central belt of Scotland was mainly the relative risk lower spatial cluster for the multi-resistant ST DT104 R-types. Of note in the spatio-temporal analysis was the stability and persistence of the chromosomally mediated multiple resistance compared to the more sporadic plasmid mediated resistance types of the second group. Although there were many similarities between the infections in humans and animals, there was no consistent temporal association between the emergence of clones in humans compared with animals suggesting that the ecological and epidemiological direction of the relationships is complex.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:444381 |
| Date | January 2007 |
| Creators | Lai, Jyhmirn |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/5439/ |
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