Application of limiting antigen avidity enzyme immunoassay for estimating HIV-1 incidence in men who have sex with men

Abstract

Objective: To estimate the incidence of HIV-1 infection in men who have sex with men (MSM) in key areas of China through HIV-1 limiting antigen avidity enzyme immunoassay (LAg-Avidity EIA), analyze the deviation from the actual results and identify influencing factors, and provided reference for improving the accuracy of estimation results. Methods: Based on the principle of the cohort randomized study design, 20 cities were selected in China based on population size and the number of HIV-positive MSM. The sample size was estimated to be 700 according to the HIV-1 infection rate in MSM. MSM mobile phone app. was used to establish a detection appointment and questionnaire system, and the baseline cross-sectional survey was conducted from April to November 2019. LAg-Avidity EIA was used to identify the recent infected samples. The incidence of HIV-1 infection was calculated and then adjusted based on the estimation formula designed by WHO. The influencing factors were identified by analyzing the sample collection and detection processes. Results: Among the 10 650 blood samples from the participants, 799 were HIV-positive in initial screening, in which 198 samples (24.78%) missed during confirmation test. Only 621 samples were received by the laboratory. After excluding misreported samples, 520 samples were qualified for testing. A total of 155 samples were eventually determined as recent infection through LAg-Avidity EIA; Based on the estimation formula , the incidence of HIV-1 infection in MSM in 20 cities was 4.06% (95%CI:3.27%-4.85%), it increased to 5.53% (95%CI: 4.45%-6.60%)after the adjusting for sample missing rate. When the sample missing rate and misreporting rate were both adjusted, the incidence of HIV-1 infection in the MSM increased to 5.66% (95%CI:4.67%-6.65%). The actual incidence of HIV-1 infection in MSM in the 20 cities might be between 4.06% and 5.66%. Conclusions: Sample missing and misreporting might cause the deviation of the estimation of HIV-1 infection incidence. It is important to ensure the sample source and the quality of sample collection and detection to reduce the deviation in the estimation of HIV-1 infection incidence.