Development of a Subsequence Correlation Coefficient Feature Vector Method for High-Resolution HIV-1 Subtype Classification — China, 2004–2022

What is already known about this topic? Current HIV-1 subtype classification tools often rely on time-consuming alignment, whereas new non-alignment methods typically target single genes. China lacks a model for specifically predicting the non-B subtype strains prevalent domestically. What is added by this report? We developed a fast alignment-free method (SCCFV-RDA) for building multigene models. It achieved over 99.85% accuracy in classifying an international dataset and 99.7% accuracy in classifying Chinese pol gene data and showed superior recall for key circulating recombinant form subtypes. What are the implications for public health practice? This tool provides accurate and efficient computational support for the precise molecular surveillance of HIV-1 in China, thereby facilitating the formulation of targeted prevention and control strategies.