Validation of HIV risk screening tool to identify infected adults and adolescents greater than 14 years at community level in Tanzania and Zambia

Introduction: There are several risk factors being used to identify undiagnosed HIV-infected adults. As the number of undiagnosed people gets less and less, it is important to know if existing risk factors and risk assessment tools are valid for use. Methods: Data from the Tanzania and Zambia Population-Based HIV Impact Assessment (PHIA) household surveys which were conducted during 2016 was used. We first included 12 risk factors (being divorced, separated or widowed; having an HIV+ spouse; having one of the following within 12-months of the survey: paid work, slept away from home for ≥1-month, having multiple sexual partners, clients of sex workers, sexually transmitted infection, being tuberculosis suspect, being very sick for ≥3-months; ever sold sex; diagnosed with cervical cancer; and had TB disease into a risk assessment tool and assessed its validity by comparing it against HIV test result. Sensitivity, specificity and predictive value of the tool were assessed. Receiver Operating Characteristic (ROC) curve comparison statistics was also used to determine which risk assessment tool was better. Results: HIV prevalence was 2.3% (2.0%-2.6%) (n=14,820). For the tool containing all risk factors, HIV prevalence was 1.0% when none of the risk factors were present (Score 0) compared to 3.2% when at least one factor (Score ≥1) was present and 8.0% when ≥4 risk factors were present. Sensitivity, specificity, PPV, and NPV were 82.3% (78.6%-85.9%), 41.9%(41.1%-42.7%), 3.2%(2.8%-3.6%), and 99.0%(98.8%-99.3%), respectively. The use of a tool containing conventional risk factors (all except those related with working and sleeping away) was found to have higher AUC (0.65 vs 0.61) compared to the use of all risk factors (p value <0.001). Conclusions: The use of a screening tool containing conventional risk factors improved HIV testing yield compared to doing universal testing. Prioritizing people who fulfill multiple risk factors should be explored further to improve HIV testing yield.

ART experienced patients for tackling attrition from HIV care: a multi-site cohort study

Introduction: Retention of patients on anti-retroviral treatment in Ethiopia is a challenge. Use of anti-retroviral treatment experienced patients to prepare and re-engage them when they miss follow-ups is recommended, but evidence on its effectiveness is limited. This study evaluated its effectiveness.Methods: A retrospective cohort study in 10 randomly selected health facilities was conducted to compare outcomes before and after initiation of the adherence supporters program in HIV care and treatment from September 2001 to August 2013. Data analysis involved Kaplan-Meier survival and Log-rank test analysis on STATA statistical software Version 12 to compare survival experiences.Results: Of 18,835 records that were available, 938 (4.36%) records with missing values were excluded and data from the remaining 17,897 was analyzed. The incidence of first instance lost to follow-up was 22.2 per 100 person-years (95% confidence interval 21.7-22.7). The risk of missing follow-ups after initiation of the program was high (Hazard Ratio ­1.22, P < 0.001). The incidence of restarting after missed follow-ups was 23 per 100 PY (95% CI 22.2-24.0). The likelihood of restarting after missed follow-ups was four times higher during the period adherence supporters were present (P<0.001). Patients who stayed longer in care before missing follow ups were more likely to restart (5.7 times the chance of restarting treatment for those whose first lost to follow-up occurred at≥12 months compared to <3 months, P< 0.001).Time to restarting treatment was shorter after the initiation of the adherence supporters program (median 37 vs. 115 days). The risk of recurrence of being lost to follow-up in the presence of adherence supporters was significantly higher than when there were no adherence supporters; 38.8 (95% CI 36.3-41.6) per 100 PY vs. 26.1 (95% CI 19.8-34.4) per 100 PY, respectively. Conclusion: Adherence supporters were effective in improving re-engagement of patients in treatment and care after they were lost to follow-up. Yet, prevention of lost to follow-up cases has remained a challenge to the program