Cluster Transmission Drives Invasive Group A Streptococcus Disease Within the United States and Is Focused on Communities Experiencing Disadvantage.

Autor:	Metcalf B; Respiratory Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Nanduri S; Respiratory Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Chochua S; Respiratory Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Li Y; Respiratory Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Fleming-Dutra K; Respiratory Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., McGee L; Respiratory Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Beall B; Respiratory Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Jazyk:	angličtina
Zdroj:	The Journal of infectious diseases [J Infect Dis] 2022 Aug 26; Vol. 226 (3), pp. 546-553.
DOI:	10.1093/infdis/jiac162
Abstrakt:	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. (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
Databáze:	MEDLINE
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