Understanding the dynamics of recent infection among people newly diagnosed with HIV may help in identifying geographic areas and subpopulation with high HIV transmission rates for super targeted testing. Recency testing helps to detect people who were recently infected with HIV so that prevention programs can focus on preventing incident infections to reduce new infection rate and ultimately interrupt further transmission to achieve epidemic control. The PEPFAR team in Nigeria introduced recency testing in 2020. We analyzed recent infection among newly diagnosed PLHIV in 10 states.
Testing for recent infection using pre-approved recency test kit was conducted for newly diagnosed HIV positive clients in 10 states over an 18-month period. Using One way Welch ANOVA we determined if there was any difference in the recent infection yields of different age groups. Welch T- test was done to determine if any significant difference exist in the recency testing yield between male and female. We carried out a Multinomial regression to determine how well gender and age range can predict recency yield in the states
A total of 10,070 PLHIV (male=40%; female=60%) where tested for recent infection with 10% (n=1010; (male=39%; female=61%) identified as having recent HIV infection. One-way Welch ANOVA shows statistically significant difference in recency testing yield for the 8 different age groups, Welch’s F (7, 304.463) = 183.574, p<0.0005., the highest yield for recent infection was seen in the age group 20-24 years (16%) while the lowest in the age group 50+ (4%). Females generally had higher recent infection rates (11%) than men (9%). Games-Howell post hoc analysis revealed that the difference in the mean for the age groups with the highest (25-29 years) and lowest (15-19 years) number of recent infections was significant. Welch T test shows that the difference in the mean yield between male and female was statistically significant with a mean difference of 131. 624 (95%CI = -144.635 to -118.613); t (873.43) = 19.855; p < 0005. Multinomial regression shows a statistically significant likelihood ratio test for both gender and age range. This means that gender and age significantly improve yield prediction in the sates.
Recent infection is higher among certain age group and varies across states. Recent infection rate is higher among females. HIV intervention should be prioritized to focus on the age range and sex with the highest new infection rates by geography.