Determinants of High HIV Infection Prevalence in Vijayapura, Bagalkot, and Belagavi Districts in Karnataka, India

印度卡纳塔克邦维杰亚普拉、巴加尔科特和贝拉加维地区艾滋病毒感染率高的决定因素

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Abstract

Introduction India has the second-highest number of people living with human immunodeficiency virus (PLHIV). Despite the national decline in the prevalence of the human immunodeficiency virus (HIV) from 2000 to 2021, regional variations persist, particularly in the northeastern and southern states. High-risk populations, including female sex workers (FSW), men who have sex with men (MSM), and injecting drug users (IDU), significantly contribute to these dynamics. This study focuses on high-prevalence districts in Karnataka. Objectives This study aims to identify socioeconomic and behavioral factors associated with high HIV prevalence in high-burden districts of South Indian states. Methodology A cross-sectional study was conducted using data from Integrated Counseling and Testing Centers (ICTCs) and Designated STI/RTI (sexually transmitted infections/reproductive tract infections) Clinics (DSRCs) across 24 centers in the three districts. The centers were determined using a simple random sampling method. Data from 2501 HIV-positive individuals were analyzed, focusing on demographics, risk behaviors, and treatment history. Results Males constituted the majority of HIV cases, accounting for 448 (56.0%) in Vijayapura, 334 (51.4%) in Bagalkot, and 644 (61.1%) in Belagavi districts, with a significant portion referred by government hospitals. High HIV prevalence was linked to adults aged 25-49 years of age; the number of people with HIV was high among daily wage workers and individuals with multiple sexual partners compared to married and educated people. Newly diagnosed discordant couples ranged from 129 (12.2%) in Belagavi to 133 (18.4%) in Vijayapura districts. Most patients were on first-line antiretroviral therapy (ART), with loss to follow-up attributed to system negligence and poor compliance. Conclusion Key determinants of high HIV prevalence include gender, age, marital status, socioeconomic status, and sexual behavior. Effective interventions require targeted education, improved healthcare services, robust surveillance, and strengthened collaboration among stakeholders.

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