期刊
JOURNAL OF THE ROYAL SOCIETY INTERFACE
卷 9, 期 70, 页码 1029-1039出版社
ROYAL SOC
DOI: 10.1098/rsif.2011.0499
关键词
antibiotic resistance; Escherichia coli; transmission models; Ecuador; community
资金
- National Institute of Allergy and Infectious Diseases (NIAID) [RO1-AI050038]
- Fogarty International Centre (FIC) of the National Institutes of Health (NIH) [0811934]
- National Science Foundation (NSF)
- Direct For Biological Sciences
- Division Of Environmental Biology [811934, 0811901] Funding Source: National Science Foundation
The evolution of antibiotic resistance (AR) increases treatment cost and probability of failure, threatening human health worldwide. The relative importance of individual antibiotic use, environmental transmission and rates of introduction of resistant bacteria in explaining community AR patterns is poorly understood. Evaluating their relative importance requires studying a region where they vary. The construction of a new road in a previously roadless area of northern coastal Ecuador provides a valuable natural experiment to study how changes in the social and natural environment affect the epidemiology of resistant Escherichia coli. We conducted seven bi-annual 15 day surveys of AR between 2003 and 2008 in 21 villages. Resistance to both ampicillin and sulphamethoxazole was the most frequently observed profile, based on antibiogram tests of seven antibiotics from 2210 samples. The prevalence of enteric bacteria with this resistance pair in the less remote communities was 80 per cent higher than in more remote communities (OR = 1.8 [1.3, 2.3]). This pattern could not be explained with data on individual antibiotic use. We used a transmission model to help explain this observed discrepancy. The model analysis suggests that both transmission and the rate of introduction of resistant bacteria into communities may contribute to the observed regional scale AR patterns, and that village-level antibiotic use rate determines which of these two factors predominate. While usually conceived as a main effect on individual risk, antibiotic use rate is revealed in this analysis as an effect modifier with regard to community-level risk of resistance.
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