Passive testing venues have been largely successful in screening for HIV in San Diego County, California, a new study suggests. Still, high-prevalence areas may benefit from targeted testing efforts.
The study, published in Open Forum Infectious Diseases
, analyzed 379,074 HIV tests performed in community-based HIV screening programs between 1998 and 2016 with the aim of understanding the relationship between screen efforts, HIV prevalence, HIV incidence and rates of sexually transmitted infections (STIs).
“We wanted to see if where the people were coming from to get tested correlated with the number of known cases in those zip codes to see if a venue can actually reach out and sample the appropriate population in a reasonable manner,” Sanjay Mehta, associate professor of medicine and pathology at University of California San Diego, told Contagion®
. “We found that was actually pretty good for HIV. It matched up pretty good. But there were a few outlying zip codes.”
The study determined that standalone testing centers dispersed throughout the county were effective at reaching people at high risk of infection. It also could be used to identify areas where targeted testing through mobile HIV resources might be useful.
“What was interesting is that the outliers, where there were more cases than we would expect per the number of tests being performed, were in the highest prevalence zip codes, where these testing centers were located. Some of them at least,” Mehta told Contagion®
. “What it really highlighted to us is that these high-prevalence zip codes are still probably undertested, which is kind of interesting.”
With about 11,252 residents living with HIV in San Diego County in 2010, the county has an overall HIV prevalence of 0.36%, and 2 zip codes with prevalence rates over 4%. Overall, the number of tests performed strongly correlated with HIV prevalence (R2
=0.714), new HIV diagnoses (R2
=0.798), and STI diagnoses (R2
=0.768 [chlamydia],0.836 [gonorrhea], 0.655 [syphilis]).
“The overall conclusion really was that a passive venue-based testing program was actually pretty decent at sampling the people around the county that were at risk for infection,” Mehta told Contagion®
The central part of the county consistently showed the highest prevalence of HIV, with more than 50% of newly diagnosed cases from 2007 to 2012 and 2 zip codes accounting for 22.7% of the county’s prevalent HIV cases in 2016. The central area’s portion of newly diagnosed HIV cases dropped to 42.9% in 2016, while other areas increased—18.2% to 20.4% in the south and 4.0% to 7.2% in the north inland region.
Mehta said his team will reach out to programs working to end HIV in San Diego County and talk to them about targeting their mobile testing resources to areas identified by the study.
“Even though there are clearly HIV infections across the county, it is really highly concentrated in a handful of zip codes,” Mehta told Contagion®
. “It does make sense to really pour your efforts into those areas.”
Similar studies could be repeated frequently to adjust for changing demographics and shifts in disease patterns.
“It is something that would be easy enough for a public health jurisdiction to do on an annual basis,” Mehta told Contagion®
The research team also will reach out to other jurisdictions in areas with high prevalence of HIV infection about doing similar research there.
About 10% of people living with HIV in San Diego County are unaware of their diagnosis, making increasing testing and diagnosis a priority for health officials. A recent study
explored universal screening for HIV and hepatitis C at 2 emergency department in San Diego. From July 2017 to September 2018, 12,575 individuals were tested, and 81 had a positive result, including 10 false positives, 38 who had previously tested positive and 33 new diagnoses.
In November, the World Health Organization released new testing guidelines
encouraging all countries to adopt a standard HIV testing strategy using 3 consecutive reactive tests to confirm a diagnosis, recommending use of self-tests, and emphasizing the importance of using social network-based HIV testing to reach at-risk individuals.
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