Prevalence of cervicovaginal human papillomavirus infection and genotype distribution in Shanghai, China

Abstract

Background: The evaluation of human papillomavirus (HPV) prevalence rate dynamics and genotype distribution could support the adoption of more targeted prevention and treatment of cervical cancer. We aimed to assess the infection status and genotype characteristics of HPV among gynecological outpatients in Shanghai, China.

Methods: Clinical specimens were collected from patients attending gynaecological department of the Putuo Hospital, Shanghai University of Traditional Chinese Medicine, between January 2015 and December 2019. The cervicovaginal infection of 17 high-risk genotypes and 10 low-risk genotypes were analyzed by Luminex-based multiple assays.

Results: The overall HPV infection rate was 18.81% (95% CI 18.31-19.30%) in Shanghai city, with high-risk, low-risk and mixed high- and low-risk HPV prevalence being 11.65% (95% CI 11.24-12.06%), 4.19% (95% CI 3.94-4.44%) and 2.96% (95% CI 2.74-3.17%), respectively. The five most prevalent high-risk genotypes were HPV-52 (2.95%), HPV-16 (2.34%), HPV-58 (2.07%), HPV-53 (1.67%) and HPV-39 (1.36%). The most common low-risk genotype was HPV-61 (1.52%), followed by HPV-6 (1.29%) and HPV-81 (1.19%). Moreover, the coverage of HPV genotype by nonavalent vaccine was 10.42%, and non-vaccine-covered high-risk genotype was 7.70%. The 15-24 years age group demonstrated the highest HPV prevalence (43.14%), and significant differences were observed among different age groups (P < 0.001).

Conclusions: This study revealed the HPV prevalence and genotype distribution among women in Shanghai city, which could serve as guidance for HPV vaccination and preventative strategies against cervical cancer in this area.

Keywords: Cervical cancer; Genotype; Human papillomavirus; Prevalence; Vaccine.

Fig. 1

The prevalence of HPV infection by age groups. A any, high-risk, low-risk and low and high-risk HPV infection. B single, dual and multiple infection. C bivalent, quadrivalent, nonavalent vaccine targeting genotypes and non-vaccine high-risk genotypes. Error bars represent 95% confidence intervals

Fig. 2

Bubble plots showing the relative prevalence of detected A 17 high-risk HPV genotypes and B 10 low-risk HPV genotypes across age groups

Fig. 3

Heatmap of distribution of HPV genotypes in age groups. The prevalence was log-transformed to reduce the skewness of data

Fig. 4

Prevalence and distribution of HPV by using both this study and collected data. A Prevalence of HPV stratified by geographical areas. Solid black lines represent the median value for each geographical group. B Non-metric Multi-Dimensional Scaling (NMDS) of HR-HPV genotypes using the Euclidean similarity index