Int J Health Geogr - A spatial approach for the epidemiology of antibiotic use and resistance in community-based studies: the emergence of urban clusters of Escherichia coli quinolone resistance in Sao Paulo, Brasil.

Tópicos

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Resumo

CKGROUND: Population antimicrobial use may influence resistance emergence. Resistance is an ecological phenomenon due to potential transmissibility. We investigated spatial and temporal patterns of ciprofloxacin (CIP) population consumption related to E. coli resistance emergence and dissemination in a major Brazilian city. A total of 4,372 urinary tract infection E. coli cases, with 723 CIP resistant, were identified in 2002 from two outpatient centres. Cases were address geocoded in a digital map. Raw CIP consumption data was transformed into usage density in DDDs by CIP selling points influence zones determination. A stochastic model coupled with a Geographical Information System was applied for relating resistance and usage density and for detecting city areas of high/low resistance risk.RESULTS: E. coli CIP resistant cluster emergence was detected and significantly related to usage density at a level of 5 to 9 CIP DDDs. There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density.CONCLUSIONS: There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. The usage density of 5-9 CIP DDDs per 1,000 inhabitants within the same influence zone was the resistance triggering level. This level led to E. coli resistance clustering, proving that individual resistance emergence and dissemination was affected by antimicrobial population consumption.

Resumo Limpo

ckground popul antimicrobi use may influenc resist emerg resist ecolog phenomenon due potenti transmiss investig spatial tempor pattern ciprofloxacin cip popul consumpt relat e coli resist emerg dissemin major brazilian citi total urinari tract infect e coli case cip resist identifi two outpati centr case address geocod digit map raw cip consumpt data transform usag densiti ddds cip sell point influenc zone determin stochast model coupl geograph inform system appli relat resist usag densiti detect citi area highlow resist riskresult e coli cip resist cluster emerg detect signific relat usag densiti level cip ddds cluster hotspot signific global spatial variat residu resist risk allow usag densityconclus cluster hotspot signific global spatial variat residu resist risk allow usag densiti usag densiti cip ddds per inhabit within influenc zone resist trigger level level led e coli resist cluster prove individu resist emerg dissemin affect antimicrobi popul consumpt

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