Abstract
INTRODUCTION: We established a reliable and cost-effective method for identifying severe acute respiratory syndrome coronavirus 2 variants circulating in central China and analysed the clinical characteristics of patients with acute coronavirus disease 2019 who were infected with these variants. METHODS: The RNA of centrifuged and enriched samples was extracted and reverse transcribed into cDNA. cDNA was then analysed using a nested polymerase chain reaction amplification and Sanger sequencing method targeting specific mutations in the spike, ORF1a, and N genes. This was validated against next-generation sequencing, achieving 100% concordance. RESULTS: Among 172 isolates, JN.1.18.2 was the most prevalent (52.9%, 91/172), followed by XDV.1 (25.0%, 43/172), JN.1.16 (20.9%, 36/172), and KP.2 (1.2%, 2/172), which was found in central China for the first time. Fever with cough (52.6%, 80/152) was the most common symptom and 59.9% (91/152) of patients had underlying conditions. JN.1.18.2-infected patients more frequently presented with double-lung computed tomography changes. A strong positive correlation was observed between the duration from hospital admission to the detection of SARS-CoV-2 variants and total hospitalisation duration. DISCUSSION: The new method provides a reliable tool for variant detection, highlighting milder clinical presentations in patients with active infections. Long-term monitoring of variants and patient characteristics is essential for effective prevention and treatment strategies.