In the Journals

Molecular data helps identify HIV networks

Using molecular data to supplement information gained through public health interviews — chiefly, the names of sexual or needle-sharing partners — can help identify HIV transmission networks and prevent new infections in states with low HIV morbidity, researchers reported in a recent MMWR.

“Public health interviews (ie, partner services), during which persons with diagnosed HIV infection name their sexual or needle-sharing partners (named partners) are used to identify HIV transmission networks to guide and prioritize HIV prevention activities,” Katarina M. Grande, MPH, from the Wisconsin Department of Health Services, and colleagues wrote. “HIV sequence data, generated from provider-ordered drug resistance testing, can be used to understand characteristics of molecular clusters, a group of sequences for which each sequence is highly similar (linked) to all other sequences, and assess whether named partners are plausible HIV transmission partners.”

Grande and colleagues noted that although molecular data have been analyzed in states with higher HIV morbidity, few states with lower morbidity — such as Wisconsin — have conducted such analyses. According to their report, in 2016, Wisconsin reported 4.6 HIV diagnoses per 100,000 people aged at least 13 years.

For their study, Grande and colleagues used HIV sequence data from provider-ordered tests to identify molecular clusters and describe demographic and transmission risk characteristics of pairs of people whose sequences were highly genetically similar, they explained. They assessed the overlap between molecular linkages and partner data reported during public health interviews.

According to their findings, “characteristics of molecular clusters in Wisconsin mirrored those from states with more HIV diagnoses, particularly in that most molecular linkages were observed among persons of the same race ... the same transmission risk ... and the same age group,” the researchers wrote.

There was a moderate overlap of named partner and molecular linkages, with 33.8% of named partners as plausible transmission partners, according to the report.

“Analysis of HIV sequence data is a useful tool for characterizing transmission patterns not immediately apparent using traditional public health interview data, even in a state with lower HIV morbidity,” the researchers wrote.

“Despite relatively low overlap between molecular data and named partner data, the results of public health interviews are still important for identifying persons at high risk for acquiring HIV infections, identifying undiagnosed HIV infection and ensuring that persons with diagnosed HIV infection are engaged in HIV medical care,” they wrote. “The combination of public health interview and molecular sequence data is a powerful new tool for understanding HIV transmission networks and identifying population- or individual-level interventions to reduce HIV transmission and improve health outcomes.” – by Bruce Thiel

Disclosures: The researchers report no relevant financial disclosures.

Using molecular data to supplement information gained through public health interviews — chiefly, the names of sexual or needle-sharing partners — can help identify HIV transmission networks and prevent new infections in states with low HIV morbidity, researchers reported in a recent MMWR.

“Public health interviews (ie, partner services), during which persons with diagnosed HIV infection name their sexual or needle-sharing partners (named partners) are used to identify HIV transmission networks to guide and prioritize HIV prevention activities,” Katarina M. Grande, MPH, from the Wisconsin Department of Health Services, and colleagues wrote. “HIV sequence data, generated from provider-ordered drug resistance testing, can be used to understand characteristics of molecular clusters, a group of sequences for which each sequence is highly similar (linked) to all other sequences, and assess whether named partners are plausible HIV transmission partners.”

Grande and colleagues noted that although molecular data have been analyzed in states with higher HIV morbidity, few states with lower morbidity — such as Wisconsin — have conducted such analyses. According to their report, in 2016, Wisconsin reported 4.6 HIV diagnoses per 100,000 people aged at least 13 years.

For their study, Grande and colleagues used HIV sequence data from provider-ordered tests to identify molecular clusters and describe demographic and transmission risk characteristics of pairs of people whose sequences were highly genetically similar, they explained. They assessed the overlap between molecular linkages and partner data reported during public health interviews.

According to their findings, “characteristics of molecular clusters in Wisconsin mirrored those from states with more HIV diagnoses, particularly in that most molecular linkages were observed among persons of the same race ... the same transmission risk ... and the same age group,” the researchers wrote.

There was a moderate overlap of named partner and molecular linkages, with 33.8% of named partners as plausible transmission partners, according to the report.

“Analysis of HIV sequence data is a useful tool for characterizing transmission patterns not immediately apparent using traditional public health interview data, even in a state with lower HIV morbidity,” the researchers wrote.

“Despite relatively low overlap between molecular data and named partner data, the results of public health interviews are still important for identifying persons at high risk for acquiring HIV infections, identifying undiagnosed HIV infection and ensuring that persons with diagnosed HIV infection are engaged in HIV medical care,” they wrote. “The combination of public health interview and molecular sequence data is a powerful new tool for understanding HIV transmission networks and identifying population- or individual-level interventions to reduce HIV transmission and improve health outcomes.” – by Bruce Thiel

Disclosures: The researchers report no relevant financial disclosures.