Validation of HIV Risk Screening Tool To Identify Infected Adults And Adolescents >14 Years At Community Level

Abstract

BackgroundThere are a number of risk factors being used to identify undiagnosed HIV infected adults. As the number of undiagnosed people gets lesser and lesser, it is important to know if existing risk factors and risk assessment tools are valid for use. In this study, we validate existing HIV risk assessment tools and see if they are worth using for HIV case finding among adults who remain undiagnosed. Methods The Tanzania and Zambia Population-Based HIV Impact Assessment (PHIA) household surveys were conducted during 2016. We used adult interview and HIV datasets to assess validity of different HIV risk assessment tools. We first included 12 risk factors (being divorced, separated or widowed (DSW); having an HIV+ spouse; having one of the following within 12 months of the survey: paid work, slept away from home for at least a month, had multiple sexual partners, paid for sex, had sexually transmitted infection (STI), being a tuberculosis (TB) suspect, being very sick for at least 3 months; had 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 against the HIV test result. A receiver operator characteristic (ROC) analysis was conducted to determine a suitable cut-off score in order to have a tool with better sensitivity, specificity, and PPV. ROC comparison statistics was used to statistically test equality between AUC (area under the curve) of the different scores. ROC comparison statistics was also used to determine which risk assessment tool was better compared to the tool that contained all risk factors. Results Of 14,820 study participants, 57.8% were men, and had a median age of 30 (IQR: 21-24). HIV prevalence was 2.3% (95% confidence interval (CI): 2.0-2.6). For the tool containing all risk factors, HIV prevalence was 1.0% when none of the risk factors were positive (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 compared to the use of all risk factors (p value <0.001), with corresponding sensitivity, specificity, PPV, and NPV of 63.5% (58.9%-68.1%), 66.2% (65.5%-67.0%), 4.2% (3.6%-4.8%), and 98.7% (98.5%-98.9%), respectively. Conclusion Use of a screening tool containing conventional risk factors improved HIV testing yield compared to doing universal testing. Prioritizing people who fulfil multiple risk factors should be explored further to improve HIV testing yield.