Objective: To describe the characteristics of molecular transmission network of newly diagnosed HIV-1 infected patients, analyze their risk factors related to network access and provide a scientific basis for precise prevention of HIV infection. Methods: For 340 blood samples collected from confirmed HIV-1 infection cases aged ≥50 years in Pengzhou city of Sichuan province from April 2019 to August 2021, nested PCR amplification was used to amplify, clean up and splice clips the pol gene region. The phylogenetic tree was constructed by multi-sequence comparison to distinguish subtypes, and the pairwise genetic distance was calculated. When the genetic distance threshold was 0.90%, the number of clusters was the largest (41), and the molecular transmission network was constructed.The χ2 test and logistic regression analysis were performed.The software SPSS 19.0 was used for statistical analysis. Results: A total of 340 samples were successfully amplified (97.06%, 330/340) in 330 samples. 6 HIV-1 subtypes identified, including:CRF01_AE(56.67%,187/330), CRF07_BC(27.88%,92/330), B(11.21%,37/330), CRF08_BC(3.33%,11/330), CRF55_01B(0.61%,2/330) and C(0.30%,1/330).The network entry rate was 58.79% (194/330).The results of logistic regression analysis of the risk factors of HIV-1 molecular transmission network in the research subjects showed that compared with illiteracy, junior high school (OR=0.35, 95%CI:0.13-0.97) and high school/technical secondary school (OR=0.14, 95%CI: 0.02-0.97) had lower possibility of network entry. Compared with farmers, unknown occupations (OR=0.40,95%CI: 0.17-0.95) are less likely to enter the network .Compared with CRF01_AE, CRF07_BC (OR=0.20, 95%CI: 0.11-0.35) and CRF08_BC subtype (OR=0.09, 95%CI: 0.02-0.45) were less likely to enter the network. Conclusions: The sources of AIDS transmission among middle-aged and elderly people of rural areas are diversified in Pengzhou city of Sichuan province. AIDS intervention should focus on middle-aged and elderly farmers with low educational level, and strengthen detection and traceability investigation.
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