Using an Established Outbreak Response Plan and Molecular Epidemiology Methods in an HIV Transmission Cluster Investigation, Tennessee, January-June 2017

在田纳西州2017年1月至6月发生的艾滋病毒传播聚集性疫情调查中,运用既定的疫情应对计划和分子流行病学方法

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Abstract

INTRODUCTION: In April 2017, the Tennessee Department of Health (TDH) was notified of an increase in the number of persons newly diagnosed with HIV in eastern Tennessee in the same month. Two were identified as persons with a history of injection drug use (IDU) and named each other as syringe-sharing partners, prompting an investigation into a possible HIV cluster among persons with a history of IDU. MATERIALS AND METHODS: TDH and public health staff members in eastern Tennessee collaborated to implement procedures outlined in TDH's HIV/hepatitis C virus (HCV) Outbreak Response Plan, including conducting enhanced interviewing and using a preestablished database for data collection and management. To complement contact tracing and enhanced interviewing, TDH partnered with the Centers for Disease Control and Prevention to conduct molecular HIV analyses. RESULTS: By June 27, 2017, the investigation had identified 31 persons newly diagnosed with HIV infection; 8 (26%) self-reported IDU, 4 of whom were also men who have sex with men (MSM). Of the remaining 23 persons newly diagnosed with HIV infection, 10 were MSM who did not report IDU, 9 reported high-risk heterosexual contact, and 4 had other or unknown risk factors. Molecular analysis of the 14 HIV-1 polymerase genes (including 7 of the 8 persons self-reporting IDU) revealed 3 distinct molecular clusters, one of which included 3 persons self-reporting IDU. PRACTICE IMPLICATIONS: This investigation highlights the importance of implementing an established Outbreak Response Plan and using HIV molecular analyses in the event of a transmission cluster or outbreak investigations. Future HIV outbreak surveillance will include using Global Hepatitis Outbreak Surveillance Technology to identify HCV gene sequences as a potential harbinger for HIV transmission networks.

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