Using a molecular sequencing method to gage HIV surveillance trends in the United States, researchers identified 60 transmission clusters
in which the transmission rate was 11-fold higher than the national rate.
Anne Marie France, PhD, MPH, Centers for Disease Control and Prevention (CDC) epidemiologist, said in a press conference at the 25th Conference on Retroviruses and Opportunistic Infections (CROI)
that traditional HIV surveillance data have limitations and are unable to pinpoint the leading edge of HIV transmission.
“Molecular surveillance is an advanced public health technology that we believe will enable state and local health departments to more quickly and efficiently identify where HIV transmission may be occurring and how to efficiently intervene to stop it,” Dr. France explained. The findings emphasize how valuable molecular sequence data is at guiding prevention intervention at a local level.
For the study, Dr. France and colleagues analyzed partial HIV-1 pol sequences reported to the National HIV Surveillance System (NHSS) at quarterly intervals ranging from December 31, 2015 to December 31, 2016. The data examined pertained to diagnosed HIV infections within the previous 3 years.
Using the NHSS data, researchers were able to detect transmission clusters, which were defined as groups of patients whose viruses had no more than 0.5% variation, or genetic distance, between them. Furthermore, rapidly growing clusters were defined as those with ≥ 5 diagnoses during the most recent 12-month period.
Among the 51,750 sequences analyzed, 60 rapidly growing transmission clusters were detected in all regions of the country involving 20 states.
Clusters ranged in size from 5 to 42 individuals, with transmission rates ranging from 21 to 132 transmission events per 100 person-years Additionally, the median rate of 44 infections per 100 person-years was 11 times greater than the national rate of 4 infections per 100 person-years.
In rapidly growing clusters (n=903), researchers concluded that there was a disproportionate number of patients who were young men who have sex with men (MSM) (61% vs 32%), particularly young Hispanic/Latino MSM (26% vs 10%), compared with the non-rapidly growing clusters (n=50,847).
“Routine surveillance for rapidly growing clusters consistently identifies clusters across the US with transmission rates far exceeding the estimated national rate,” Dr. France said at the CROI press conference.
Study findings suggest that rapid transmission occurs in networks involving young MSM, especially young Hispanic MSM, and that prioritizing these clusters for public health intervention may reduce future infections.
The utilization of molecular surveillance allows researchers to identify networks particularly in high-burden areas, which will, in turn, help public health experts to determine additional HIV preventative measures.
In recent years, the CDC has been working with jurisdictions to evaluate the most effective ways to analyze and use data to effectively slow transmission rates.
While the CDC had not previously developed a systematic method using HIV diagnosis data in real-time to detect HIV outbreaks, Dr. France and colleagues sought to determine whether they could apply methods of time-space cluster detection to surveillance data; this would help them potentially identify clusters of increased diagnoses in order to focus on high-impact prevention efforts.
Dr. France and colleagues developed a systematic method for determining increased numbers of HIV diagnoses above expected baselines, or alerts, in a specific geographic area — which could represent potential transmission clusters or outbreaks.
Using NHSS data collected from 51 jurisdictions that were reported through December 31, 2016, researchers compared the number of cases reported in 2016 to the previous 3-year baseline period by jurisdiction and county for all diagnoses, and for those with a transmission risk category of injection drug use.
An alert for the given area was generated when the 2 criteria were met: a statistically greater number of cases for the most recent year (by 2 standard deviations) than the 3-year mean of the baseline period; and an increase of more than 2 diagnoses over the baseline mean.
To avoid possible reporting delays, the analyses were performed with and without lags of up to 3 months.
In the analyses of all diagnoses by jurisdiction, alerts occurred for 12 (24%) of the 51 jurisdictions, of which 4 alerted without lags. Alerts that occurred at the county level occurred for 265/3, 142 (8%) counties (143 without lags); the median and mean were 4 and 6 county alerts per jurisdiction, respectively.
Notably, a higher percentage of counties with alerts than counties without alerts were located in the South. For cases with a risk of injection drug use, alerts occurred for 7/51 (14%) jurisdictions and 39/3, 142 (1%) counties. Compared with counties without injection drug use alerts, a higher percentage of counties with injection drug use alerts were located in the Northeast.
Alerts were found in counties with low (<3) medium (3–9) and high (10+) baseline burden of HIV diagnoses.
The researchers concluded that the method of time-space cluster detection identifies significant increases in annual HIV cases across all regions and for countries with varying levels of disease burden.
Utilizing the tool in near real-time to provide systematic automated detection of possible increases in diagnoses, requires further investigation in order to determine whether the tool can serve to prioritize and focus prevention efforts in local areas for maximal public health impact.
“While we are early in the implementation process, we believe that this technology holds tremendous promise in helping identify transmission networks of potential concerns, and we’ll be continuing to work with state and local communities to further assess and intensify interventions, as needed to slow the HIV epidemic in the US,” Dr. France concluded.
A previous version of this article has been posted on MDMagazine.com.
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