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Background: Human papillomavirus (HPV) infection may lead to a series of lesions in the cervix. Distributions of HPV genotypes reveal that an increased prevalence of high-risk HPV (HR-HPV) is positively correlated with the severity of cervical lesions. Furthermore, persistent infection of HR-HPV is associated with a risk of cervical cancer. Considering the newly approval of the HPV vaccine in China and the prevalence of HPV distribution, which is meaningful for directing efforts for HPV vaccination, a more detailed understanding of HPV distribution is critical. This study aimed to investigate the overall prevalence of HPV and the age-specific features related to HPV distribution in the Jiangsu population. Methods: We collected a total of 62,317 cervical cytological specimens from Xuzhou, Nanjing and Suzhou, which represent the northern, middle and southern regions of Jiangsu Province, respectively. All these samples were assigned to 6 groups based on participant age. HPV genotypes tests were performed by using a commercial kit which is designed for the detection of 17 high-risk HPV genotypes and 6 low-risk HPV genotypes. Results: The overall prevalence of HPV was up to 26.92% in Jiangsu Province. The most common high-risk genotype was HPV52 (5.09%), followed by HPV16, HPV58, HPV53, HPV51 and HPV68. The most prevalent low-risk genotype was HPV81 (2.70%), followed by HPV43, HPV42, HPV6, HPV11 and HPV83. Most infections were caused by HR-HPV, while single-genotype infection occurred more frequently than multiple-genotype infection. Regarding participant age, the overall infection rate of HPV was distributed in a U-shaped manner, with the highest peak in the younger than 20-year-old cohort. Additionally, significant variations were found between different cities, representing different regions of Jiangsu. Conclusions: HPV prevalence is high in Jiangsu Province. The prevention of HPV-related diseases is challenging. Given the variation in HPV prevalence between ages groups and regions, a flexible HPV vaccination program, adjusted base on regional infection features, could have a beneficial effect in Jiangsu Province. [ABSTRACT FROM AUTHOR]