A growing global network's role in outbreak response: AFHSC-GEIS 2008-2009.

A cornerstone of effective disease surveillance programs comprises the early identification of infectious threats and the subsequent rapid response to prevent further spread. Effectively identifying, tracking and responding to these threats is often difficult and requires international cooperation due to the rapidity with which diseases cross national borders and spread throughout the global community as a result of travel and migration by humans and animals. From Oct.1, 2008 to Sept. 30, 2009, the United States Department of Defense's (DoD) Armed Forces Health Surveillance Center Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) identified 76 outbreaks in 53 countries. Emerging infectious disease outbreaks were identified by the global network and included a wide spectrum of support activities in collaboration with host country partners, several of which were in direct support of the World Health Organization's (WHO) International Health Regulations (IHR) (2005). The network also supported military forces around the world affected by the novel influenza A/H1N1 pandemic of 2009. With IHR (2005) as the guiding framework for action, the AFHSC-GEIS network of international partners and overseas research laboratories continues to develop into a far-reaching system for identifying, analyzing and responding to emerging disease threats.

Inference of antibiotic resistance and virulence among diverse group A Streptococcus strains using emm sequencing and multilocus genotyping methods.

BACKGROUND: Group A Streptococcus pyogenes (GAS) exhibits a high degree of clinically relevant phenotypic diversity. Strains vary widely in terms of antibiotic resistance (AbR), clinical severity, and transmission rate. Currently, strain identification is achieved by emm typing (direct sequencing of the genomic segment coding for the antigenic portion of the M protein) or by multilocus genotyping methods. Phenotype analysis, including critical AbR typing, is generally achieved by much slower and more laborious direct culture-based methods. METHODOLOGY/PRINCIPAL FINDINGS: We compare genotype identification (by emm typing and PCR/ESI-MS) with directly measured phenotypes (AbR and outbreak associations) for 802 clinical isolates of GAS collected from symptomatic patients over a period of 6 years at 10 military facilities in the United States. All independent strain characterization methods are highly correlated. This shows that recombination, horizontal transfer, and other forms of reassortment are rare in GAS insofar as housekeeping genes, primary virulence and antibiotic resistance determinants, and the emm gene are concerned. Therefore, genotyping methods offer an efficient way to predict emm type and the associated AbR and virulence phenotypes. CONCLUSIONS/SIGNIFICANCE: The data presented here, combined with much historical data, suggest that emm typing assays and faster molecular methods that infer emm type from genomic signatures could be used to efficiently infer critical phenotypic characteristics based on robust genotype: phenotype correlations. This, in turn, would enable faster and better-targeted responses during identified outbreaks of constitutively resistant or particularly virulent emm types.