HIV TESTING AMONG ADOLESCENTS (15 TO 24 YEARS).pptx

HIV TESTING AMONG YOUNG ADULTS

1. PREVALENCE AND DETERMINANTS OF HIV TESTING AMONG ADOLESCENTS (15 TO 24 YEARS)

2. OUTLINE Background Problem Statement Objectives Methods

3. BACKGROUND Over 39 million people globally were living with HIV in 2022 and 1.3 million new infections were recorded same year (UNAIDS, 2023). Recent studies have shown that the HIV prevalence rate among the general population in Ghana is 1.7%, affecting 334,713 people and accounting for over a thousand annual deaths N ew HIV infections among 15-24 years in Ghana was 28.0 % in 2020 According to the United Nation by 2025, 95% of individuals living with HIV should be aware of their status, 95% of those diagnosed with the virus should be getting continuous antiretroviral therapy (ART), and 95% of those on such treatment should have viral suppression

4. PROBLEM STATEMENT Adolescents are most at risk due to extreme peer pressure and the emergence of their sexual and social identities Despite the high prevalence of HIV infection among adolescents, policymakers give less attention to HIV testing and counseling services particularly in developing countries. Most previous studies in different regions of Africa on the prevalence of HIV testing have been focused on samples of adults and pregnant women. Also, HIV counseling and testing is very important for all strategies related to care, prevention, and treatment of HIV

5. OBJECTIVES General Objective To determine the prevalence and determinants of HIV testing among adolescents (15 to 24 years) in Ghana Specific Objectives Prevalence of HIV testing in Ghana Knowledge of adolescents on HIV prevention in Ghana Risky sexual behaviors among adolescents in Ghana Factors associated with HIV testing in Ghana

6. METHODS Data Source G DHS 2022 Data Analysis Methods Descriptive statistics will be presented for all variables (frequency, percentage, mean (standard deviation), median (interquartile range) Chi-square test of association between HIV testing and possible determinants Logistic regression model for strength of association

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