Objective: To find out the spatial autocorrelation of antibiotic resistance of S. pneumonia and test the significance of distance as a risk factor.
Methods: Descriptions of penicillin and macrolide resistance in EARS-Net countries from 2006 to 2010 were given. Global moran’s I and Anselin moran’s I were used to assess the spatial autocorrelation and gravity model was used to test the significance of distance and other socio – economic factors.
Results: The trend of resistance in Europe was stable. Positive spatial autocorrelation existed from 2006 to 2010 for penicillin (Z(I): 0.16-0.2) and 2009 to 2010 for macrolide (Z(I): 0.11 -0.13). Some clusters (hotspots) were identified; they were Cyprus (2006-2010 for penicillin and 2009 to 2010 for macrolide), Spain (2006 for penicillin), France (2006 for penicillin), Romania (2009 for penicillin and macrolide) and Bulgaria (2009 for penicillin and macrolide). The result of gravity model showed that only parameters of population in 2007 for penicillin (p<0.05) and parameter of distance in 2009 for penicillin (p<0.05) in Cyprus were statistically significant.
Conclusion: Distance was not a risk factor of high prevalence of antibiotic resistance of S. pneumoniae although there was a positive spatial autocorrelation. Improvement in surveillance system and appropriate public action were recommended for controlling the spread of resistant strain of S. pneumoniae. / published_or_final_version / Public Health / Master / Master of Public Health
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/183652 |
| Date | January 2012 |
| Creators | Wan, Hok-him., 尹學謙. |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Source | http://hub.hku.hk/bib/B50223112 |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
Page generated in 0.0026 seconds