Local changes in rates of group A Streptococcus disease and antibiotic resistance are associated with geographically widespread strain turnover events
Local changes in rates of group A Streptococcus disease and antibiotic resistance are associated with geographically widespread strain turnover events
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DOI：
10.4161/viru.1.4.11979
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发表时间：
2010-07-01
期刊：
影响因子：
5.2
通讯作者：
Russell, Kevin L.
中科院分区：
文献类型：
--
作者：
Metzgar, David;McDonough, Erin A.;Russell, Kevin L.
本研究探讨了菌株动态转换和抗生素预防对A组链球菌(GAS)耐药性和发病率的影响。作者分析了2002-2007年间收集的802株气体分离株的菌株分布、发病率和耐药模式。这些样本是从10个军事设施中有气体感染症状的患者身上采集的。由于单一耐药株(M75)在地理上的广泛优势，大环内酯类抗生素的耐药性在2004年达到了25%的峰值。无论大环内酯类抗生素的局部使用模式如何，耐药菌株都不会被保留，当M75被大环内酯类敏感菌株取代后，耐药率会降低。发病率与特定M型的显性相似。统计分析揭示了多个位置的应变分布之间的时间相关性。只有最常见的菌株才能在多个地点产生足够的数据，以便对优势地位的时间波动进行统计上的显著比较，但这些菌株(包括M44、M3、M18、M118和M6)在年度尺度上都产生了90%或更高的高度显著的时间相关性。正如预期的那样，考虑到应变分布在较短时间尺度上的复杂性和变异性，对月度尺度的分析得出的正相关程度较低(31-62%)，但在这种情况下，所有显著的相关仍然是正的。抗生素耐药性图谱和特定部位发病率的变化似乎与更大规模的菌株更换有关，与个别部位的抗生素使用无关。
This study addresses the effects of dynamic strain turnover and antibiotic prophylaxis on rates of group A Streptococcus (GAS) antibiotic resistance and disease. The authors analyzed the strain distributions, disease rates and patterns of antibiotic resistance of 802 GAS isolates collected from 2002 through 2007. These samples were collected from patients with GAS infection symptoms at ten military facilities. Macrolide resistance peaked at 25% during 2004, due to the geographically widespread dominance of a single resistant strain (M75). The resistant strain was not retained regardless of local patterns of macrolide use, and resistance rates decreased upon replacement of M75 with macrolide-susceptible strains. Disease rates were similarly correlated with dominance of specific M types. Statistical analysis revealed temporal correlations between strain distributions at multiple locations. Only the most common strains yielded enough data at multiple sites for statistically significant comparison of temporal fluctuations in dominance, but these (including M44, M3, M18, M118 and M6) all yielded highly significant temporal correlations of 90% or greater on yearly scales. As expected given the complexity and variability of strain distributions on shorter time scales, analysis on a monthly scale yielded lower degrees of positive correlation (31-62%), but in this case all significant correlations were still positive. Shifts in antibiotic resistance profiles and disease rates at specific sites appear to be associated with strain replacements happening on larger scales, independent of antibiotic use at individual sites.