# Novel threat detection methodology to detect HIV outbreaks in Washington

> **NIH NIH R21** · UNIVERSITY OF WASHINGTON · 2022 · $252,281

## Abstract

Abstract/summary
Despite recent significant advances in biomedical HIV prevention, HIV diagnosis rates in Washington State
have been stable over the past several years, with a rate of 5.3 per 100,000 in 2014 and 5.4 per 100,000 in
2018. Identifying and responding to outbreaks is a cornerstone of public health practice; rapid public health
action in such cases may decrease the transmission of HIV and other infectious diseases. While the Centers
for Disease Control and Prevention (CDC) require that local health departments conduct analyses to identify
HIV molecular clusters and/or time-space clusters of new HIV diagnoses, no recent HIV outbreaks have been
identified by methods other than local health department staff or providers noticing increases in cases in
specific areas or populations.
Working in collaboration with the Washington State Department of Health (DOH), we propose the following
aims to evaluate a new methodology to identify HIV outbreaks: (1) To adapt rapid threat detection
methodology that was developed by our team to identify outbreaks in gonorrhea to instead identify spatial-
temporal clusters of HIV cases, or changes in previously identified clusters in Washington State, based on
retrospective data from multiple counties, and (2) To compare the performance of this methodology to the
performance of current cluster identification methods being used by the Washington DOH, including CDC
recommended strategies for molecular and time-space cluster identification. We will determine whether this
method could have identified outbreaks sooner than the routine, CDC-recommended approaches, including an
HIV outbreak that occurred among injection drug users in King County, WA in 2018.
We propose an innovative approach; the methods are adapted and expanded from statistical change detection
and spatiotemporal approaches to identify the time and location of the clusters rapidly. If our approach is
found to provide added value to ongoing work at Washington DOH, we will help implement the approach so
that it can be used in conjunction with HIV surveillance in Washington State. While our approach does not rely
on HIV genetic sequence information, if successful, it can also be used to assist in identifying more appropriate
local criteria to identify HIV molecular clusters. This approach is flexible and can be applied in numerous
scenarios, including for other infections such as syphilis or SARS-CoV-2.

## Key facts

- **NIH application ID:** 10547381
- **Project number:** 1R21AI157618-01A1
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** SARAH E HOLTE
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $252,281
- **Award type:** 1
- **Project period:** 2022-08-12 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10547381

## Citation

> US National Institutes of Health, RePORTER application 10547381, Novel threat detection methodology to detect HIV outbreaks in Washington (1R21AI157618-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10547381. Licensed CC0.

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