期刊
JOURNAL OF INFECTIOUS DISEASES
卷 226, 期 3, 页码 546-553出版社
OXFORD UNIV PRESS INC
DOI: 10.1093/infdis/jiac162
关键词
invasive disease; outbreaks; Streptococcus pyogenes
资金
- Centers for Disease Control and Prevention
Using a cluster detection tool, we identified genetically related clusters representing previously unidentified iGAS outbreaks. Our findings showed that 65% of invasive isolates were associated with clusters, and emm types with a higher tendency to cluster had a higher proportion of cases from disadvantaged populations.
Background Group A streptococci (GAS), although usually responsible for mild infections, can sometimes spread into normally sterile sites and cause invasive GAS disease (iGAS). Because both the risk of iGAS disease and occurrence of outbreaks are elevated within certain communities, such as those comprising people who inject drugs (PWID) and people experiencing homelessness (PEH), understanding the transmission dynamics of GAS is of major relevance to public health. Methods We used a cluster detection tool to scan genomes of 7552 Streptococcus pyogenes isolates acquired through the population-based Active Bacterial Core surveillance (ABCs) during 2015-2018 to identify genomically related clusters representing previously unidentified iGAS outbreaks. Results We found that 64.6% of invasive isolates were included within clusters of at least 4 temporally related isolates. Calculating a cluster odds ratio (COR) for each emm type revealed that types vary widely in their propensity to form transmission clusters. By incorporating additional epidemiological metadata for each isolate, we found that emm types with a higher proportion of cases occurring among PEH and PWID were associated with higher CORs. Higher CORs were also correlated with emm types that are less geographically dispersed. Conclusions Early identification of clusters with implementation of outbreak control measures could result in significant reduction of iGAS. We used a cluster detection tool to scan 7552 Streptococcus pyogenes genomes. We found that 65% of invasive isolates were clusters-associated and that emm types with higher propensity to cluster had a higher proportion of cases from people experiencing disadvantage.
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