Forecasting HIV positivity through identification of predictors amongst high-risk women: A cohort study

Introduction: High-risk women are the major drivers of India's HIV epidemic. The targeted intervention (TI) project is working for the prevention and control of sexually transmitted infections (STIs) including HIV/AIDS among them. The current study was carried out among high-risk women to identify the predictors for HIV positivity through a model generation and assess the impact of targeted interventions in averting new HIV infections. Aims and Objectives: To generate the model for HIV positivity among high-risk women based on various independent variables using logistic regression analysis. Each year, how many HIV infections have been averted among them based on probability calculations of HIV positivity with positive and negative predictors? Methodology: Study Design: Prospective cohort with retrospective comparison. Study Setting: It was done at two different drop-in center clinics (DICs) and project field areas of the city. Sample Size: In total, 2,193 registered women availing services through NGOs/DIC clinics were enrolled. Data Entry and Analysis: Done using Excel and SPSS software. Association between the dichotomous dependent variables and continuous or categorical variables was assessed using the binary logistic regression model. Each year, how many HIV infections have been averted among them was calculated. Results: Statistically significant predictors of HIV positivity were alcohol consumption, category “A” and “C” women, partner status, regular medical check-ups, and attendance at counseling sessions. The number of HIV infections averted from 2009–10 to 2013–14 came out to be 52. Conclusion: Category C of high-risk women, alcohol consumption, and regular medical check-ups as (negative predictors) came out to be statistically significant predictors for HIV positivity.