Immunological Markers for Identifying Recent HIV Infection in North-West India

Overview

Journal Indian J Med Res

Specialty General Medicine

Date 2020 Oct 27

PMID 33107482

Citations 7

Authors

Chandar Kanta Chauhan

P V M Lakshmi

Vivek Sagar

Aman Sharma

Sunil K Arora

Rajesh Kumar

Affiliations

Soon will be listed here.

Abstract

Background & Objectives: Being more efficient and widely used, limiting antigen (LAg)-avidity enzyme immunoassay (EIA) based on the recent infection testing algorithm (RITA) has been developed for differentiating recent and established HIV-1 infection. So far, LAg-avidity EIA has not been validated among the Indian population. Hence, the present study was planned to identify recent HIV infections in high risk patients in the North-West region of India using modified LAg-avidity RITA.

Methods: Four hundred HIV-positive high risk patients registered on pre-antiretroviral therapy (ART) programme in the last one year, from five ART centres in North-Western States of India, were included for identifying the recent HIV infections. One hundred HIV-positive cases registered for pre-ART for greater than two years in ART centres were included for estimating false recent rate (FRR). Single-well LAg-avidity EIA-based modified RITA was used to identify recent HIV infection cases.

Results: Of the 400 HIV-1-positive samples, 64 (16%) were found to have been infected within the past 130 days. The proportion of recent HIV infections was 16.8 per cent (18/107) among female sex workers, 10.7 per cent (9/84) among men who have sex with men and 17.7 per cent (37/209) among injecting drug users. The FRR was one per cent (1/100).

Interpretation & Conclusions: LAg-avidity EIA-based modified RITA provided good discrimination between recent and non-recent HIV infection, hence, it could be considered suitable for estimating HIV incidence in sentinel surveillance system in India.

Citing Articles

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Evaluation of antiretroviral therapy effect and prognosis between HIV-1 recent and long-term infection based on a rapid recent infection testing algorithm.

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