Abstract
Objective
Human papillomavirus (HPV) infection is closely associated with the occurrence and development of cervical cancer. This study comprehensively investigates HPV infection and subtype distribution among women in Chengdu from 2019 to 2024, aiming to provide scientific evidence for screening, prevention, and optimization of HPV vaccination strategies against cervical cancer and related diseases.
Methods
Cervical exfoliated cell specimens from 65,130 female patients attended Sichuan Jinxin Xinan Women & Children Hospital from 2019 to 2024 were collected and detected 26 HPV gene subtypes using gene chip technology.
Results
Among the 65,130 women included in the study, 13,463 were HPV positive, with an overall detection rate of 20.67%. The single infection rate was 14.80%, and the multiple infection rate was 5.88%; the infection rates for pure HR-HPV, pure LR-HPV, and mixed infections were 13.86%, 3.90%, and 2.92%, respectively. The HPV detection rate was highest in those aged ≤ 20 years (46.01%) and among those aged > 60 years (35.37%), showing a bimodal distribution across ages. The top five HR-HPV subtypes detected were HPV52, 58, 16, 51, and 39, with infection rates of 3.71%, 2.81%, 2.56%, 1.83%, and 1.64%, respectively. The top three LR-HPV subtypes were HPV54, 42, and 40, with detection rates of 1.85%, 0.99%, and 0.93%, respectively. From 2019 to 2024, HPV detection showed a U-shaped trend, with a significant decrease in HPV16 detection rate and an increase in HPV42. Among other subtypes co-infected with the top five HR-HPV subtypes, HPV52 and HPV58 accounted for the highest proportion. After 2023, co-infections with LR-HPV increased.
Conclusion
During 2019–2024, the HPV infection rate among women in Chengdu was high with an increase in detection rates after 2023. The co-infection patterns of HR-HPV are complex. Infection rates are highest among women aged ≤ 20 years and > 60 years. Priority should be given to young women for vaccination. HPV screening should be strengthened for women across different age groups. Developing vaccines targeting locally prevalent HPV subtypes is crucial for reducing infection rates and preventing cervical cancer and other HPV-related diseases.
Keywords: Human papillomavirus, Prevalence, Genotype, Cervical cancer, Women
Introduction
Human papillomavirus (HPV) is a type of small non-enveloped, double-stranded DNA viruses that tend to infect epithelial cells. Currently, over 200 types of HPV have been identified [1]. HPV infection is closely linked to various cancers, including cervical cancer, vaginal cancer, anal cancer, and oropharyngeal cancer [2]. Different subtypes possess varied pathogenic capabilities. Based on their carcinogenic risk, they are classified into high-risk HPV (HR-HPV) and low-risk HPV (LR-HPV) [3]. Virtually all cervical cancers are related to HPV infection, with 14 HR-HPV subtypes (HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 68, 66) being related to cervical cancer. Persistent infection can lead to precancerous cervical lesions and invasive cervical cancer. LR-HPV types such as HPV6, 11, 42, 43, 44 are mainly associated with benign genital warts [4–6]. Based on the estimations from GLOBOCAN, cervical cancer is the fourth most common malignant tumor among women globally, in 2020, Asia accounted for 58% of new cervical cancer cases worldwide, approximately 352,000 cases. In the same year, Asian women comprised 59% of global cervical cancer deaths, numbering around 200,000 [7]. In 2020, China had 109,700 new cervical cancer cases and 59,100 deaths, making up 18.16% and 17.28% of global cases respectively [8]. On November 17, 2020, the WHO launched the Global Strategy to Accelerate the Elimination of Cervical Cancer as a Public Health Problem, aiming to eliminate cervical cancer globally by 2030 [9]. Various reports show that HPV infection rates and genotype distribution vary due to differences in time, countries, regions, populations, ages, diseases, and so on [10–13]. Due to China’s vast territory and large population, HPV genotype distribution varies across regions. The COVID-19 pandemic has influenced HPV infection rates and subtype prevalence [14–16]. Understanding local HPV infection and subtype distribution is crucial not only for preventing HPV infection and early diagnosis of cervical and other HPV-related diseases but also for the development of vaccines preventing infections from different HPV subtypes. This study analyzes the detection results of 26 HPV subtypes among 65,130 women in Chengdu from 2019 to 2024, providing scientific basis for preventing HPV infection and early diagnosis of cervical-related diseases in this region.
Materials and methods
Subjects
We conduct a retrospective cross-sectional study at Sichuan Jinxin Xinan Women & Children Hospital from 2019 to 2024, a total of 65,130 women who underwent HPV testing at our hospital were enrolled in this study, including both gynecological outpatients (65.86%, 42894/65130) and women undergoing routine health examinations (34.14%, 22236/65130). The subjects ranged in age from 15 to 89 years, with a mean age of 33.74 ± 8.79 years. Participants were classified into six age groups: 476 women were aged ≤ 20 years old, 27,008 women were between 21 and 30 years old, 25,887 women were aged 31–40 years old, 7,298 women were aged 41–50 years old, 3,805 women were aged 51–60 years old, and 656 women were over 60 years old. This study constituted a retrospective and anonymized analysis of patient data, which was approved by the Medical Ethics Committee of Sichuan Jinxin Xinan Women & Children Hospital.
Specimen collection and processing
Cervical exfoliated cell specimens were collected by clinical gynecologists. Before sampling, excess secretions at the cervical or urethral opening were wiped off. A cervical brush was inserted at the cervical opening, gently pressed against the cervix, and rotated 3 to 5 times to collect an adequate sample of cervical epithelial cells. Samples were placed into a dedicated cell preservation tube (provided by Shenzhen Yaneng Bio-Tech Co., Ltd.) and sent for testing promptly. Samples were stored at room temperature and tested within 7 days.
DNA extraction, PCR amplification, and HPV genotyping
The HPV genotyping test kit and nucleic acid extraction kit (Shenzhen Ganglong Bio-Tech Co., Ltd.) were used to detect 26 HPV types, including 17 high-risk types: HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 67, 68, 73, and 9 low-risk types: HPV6, 11, 40, 42, 43, 44, 54, 55, 57. The procedure followed the kit instructions strictly. DNA extraction, PCR amplification, DNA hybridization, and color development steps were performed on cervical exfoliated cell specimens. PCR amplification used the SLAN-96 Automatic Medical PCR Amplifier (Shanghai Hongshi Medical Technology Co., Ltd.) with parameters: (1) 2 min at 50 °C; (2) 10 min at 95 °C; (3) 40 cycles of 30 s at 95 °C, 45 s at 52 °C, and 30 s at 65 °C; (4) 5 min incubation at 65 °C. The hybridization reaction results were interpreted using the HPV-GenoCam-9600 HPV Genotyping Detection System (Shenzhen Ganglong Bio-Tech Co., Ltd.). A positive HPV genotyping result (INS) is defined as a value of 11.0 or higher, while less than 11.0 is regarded as negative. A single infection is defined as one HPV subtype, while infections of two or more HPV subtypes are defined as multiple infections.
Statistical analysis
Data were organized using Excel software, and statistical analyses were performed using SPSS 27.0 software. Categorical data were statistically described using frequencies and percentages (%). Group comparisons utilized the χ² test or Fisher’s exact test. In cases where the chi-square test was significant, Cochran-Armitage trend testing was further performed. P-value less than 0.05 was considered statistically significant.
Results
Overall prevalence of HPV infection
Among the 65,130 female samples included in the analysis, a total of 13,463 were HPV positive, resulting in a detection rate of 20.67% (13,463/65,130). Among the HPV-positive women, there were 9636 cases of single infection, with a detection rate of 14.80%, accounting for 71.57% (9636/13,463). Multiple infections totaled 3827 cases, with a detection rate of 5.88%, making up 28.43% (3827/13,463). Multiple infections primarily consisted of dual infections, with a detection rate of 4.01% (2613/65,130), accounting for 19.41% of the positive cases (2613/13,463) and 68.28% of the multiple infections (2613/3,827). Two women were found to be infected with up to eight HPV subtypes. Among the 13,463 HPV-positive women, there were 9025 cases of pure HR-HPV infection, 2537 cases of pure LR-HPV infection, and 1,901 cases of mixed HR-HPV and LR-HPV infection, with proportions of 67.04%, 18.84%, and 14.12%, respectively. HPV infections were predominantly single infections, particularly pure HR-HPV infections, as shown in Table 1.
Table 1.
Distribution of HPV infection in 65,130 women
| Infection type | Positive cases | Prevalence (%) | Proportion (%) | |
|---|---|---|---|---|
| Single or lctions | Single | 9636 | 14.80 | 71.57 |
| Double | 2613 | 4.01 | 19.41 | |
| Triple | 832 | 1.28 | 6.18 | |
| Quadruple | 260 | 0.40 | 1.93 | |
| Quintuple | 81 | 0.12 | 0.60 | |
| Sextuple | 29 | 0.04 | 0.22 | |
| Septuple | 10 | 0.02 | 0.07 | |
| Octuple | 2 | 0.00 | 0.01 | |
| Simple or mixed infections | HR-HPV Only | 9025 | 13.86 | 67.04 |
| LR-HPV Only | 2537 | 3.90 | 18.84 | |
| HR-HPV/LR-HPV Mixed | 1901 | 2.92 | 14.12 | |
| Total | 13,463 | 20.67 | 100 | |
Distribution of HR-HPV and LR-HPV in single and multiple infections
In cases of single infection, pure HR-HPV infections predominated, accounting for 75.65% (7290/9636), while pure LR-HPV infections constituted 24.35% (2346/9636). As the number of infection types increased, the proportions of pure HR-HPV and pure LR-HPV infections declined, while mixed infections gradually increased. In dual infections, the rate of pure HR-HPV infections decreased to 52.51%, with mixed infections representing 40.68%. Notably, in infections of three or more types, there were no cases of pure LR-HPV infections. There were only 2 cases of eightfold infections, with one case each of pure HR-HPV and mixed infections, as illustrated in Fig. 1.
Fig. 1.
Distribution of HR-HPV and LR-HPV in different types of HPV infections
Analysis of changes in HPV prevalence from 2019 to 2024
In this study, the detection rates of HPV positivity, single infection rates, dual infection rates, triple infection rates, rates of infections with three or more types, pure LR-HPV infection rates, and mixed infection rates exhibited a U-shaped trend over time. The HPV positivity rates from 2019 to 2024 were 23.41%, 19.32%, 19.27%, 19.92%, 20.14%, and 23.48%, respectively, with the lowest detection rate occurring in 2021 and the highest in 2024. Significant differences were observed in HPV positivity rates across different years (χ²=115.219, P < 0.001). The year with the lowest single infection rate was 2020 (13.90%), while the lowest rates for triple infections (0.97%), pure LR-HPV infections (3.33%), and mixed infections (2.41%) occurred in 2021. The lowest rates for dual infections and infections with three or more types were observed in 2022, at 3.53% and 0.47%, respectively. Additionally, the lowest rate for pure HR-HPV infections was found in 2023 (12.93%), as shown in Table 2.
Table 2.
Overview of human papillomavirus (HPV) infection rates across various Years[n(%)]
| Year | Total cases | Positive cases | Single infection | Double infection | Triple infection | Infection of more than three | HR-HPV only | LR-HPV only | HR-HPV/LR-HPV mixed |
|---|---|---|---|---|---|---|---|---|---|
| 2019 | 8395 | 1965(23.41) | 1349(16.07) | 428(5.10) | 136(1.62) | 52(0.62) | 1325(15.78) | 364(4.34) | 276(3.29) |
| 2020 | 11,403 | 2203(19.32) | 1585(13.90) | 418(3.66) | 132(1.16) | 68(0.58) | 1504(13.19) | 387(3.39) | 312(2.74) |
| 2021 | 12,098 | 2331(19.27) | 1718(14.20) | 431(3.56) | 117(0.97) | 65(0.54) | 1636(13.52) | 403(3.33) | 292(2.41) |
| 2022 | 12,990 | 2587(19.92) | 1920(14.78) | 458(3.53) | 148(1.14) | 61(0.47) | 1774(13.66) | 489(3.76) | 324(2.49) |
| 2023 | 11,280 | 2272(20.14) | 1615(14.32) | 434(3.85) | 157(1.39) | 66(0.59) | 1458(12.93) | 465(4.12) | 349(3.09) |
| 2024 | 8964 | 2105(23.48) | 1449(16.17) | 444(4.95) | 142(1.58) | 70(0.78) | 1328(14.82) | 429(4.79) | 348(3.88) |
| Total | 65,130 | 13,463(20.67) | 9636(14.80) | 2613(4.01) | 832(1.28) | 382(0.59) | 9025(13.86) | 2537(3.90) | 1901(2.92) |
| χ 2 | 115.219 | 36.831 | 65.004 | 28.170 | 9.533 | 47.006 | 43.435 | 55.117 | |
| P | <0.001 | <0.001 | <0.001 | <0.001 | 0.09 | <0.001 | <0.001 | <0.001 |
HPV prevalence by age group
In the age group of ≤ 20 years, there were 476 cases, with an HPV positivity rate soaring to 46.01% (219/476). The rate of mixed infections stood at 14.71% (70/476), accounting for 31.96% of the HPV-positive cases (70/219). Moreover, the proportion of multiple infections was notably high at 53.42% (117/219). The > 60 years age group exhibited the second-highest HPV positivity rate at 35.37%, with multiple infections comprising 39.22% (91/232).
Statistical analyses indicated significant differences in various infection rates: HPV positivity (χ²=406.645, P < 0.001), pure HR-HPV infections (χ²=168.087, P < 0.001), mixed infections (χ²=354.942, P < 0.001), single infections (χ²=67.508, P < 0.001), dual infections (χ²=199.548, P < 0.001), triple infections (χ²= 176.966, P < 0.001), and infections with three or more types (χ²=318.87, P < 0.001). All these rates exhibited a bimodal distribution across age groups, indicating significant variations. Notably, the rate of infections involving three or more types was found to be the lowest in the 31–40 years age group, at 0.29%. In addition, pure LR-HPV infection rates were the lowest in both the 21–30 and 31–40 years groups (3.76%). Conversely, all other types of HPV infection rates were found to be the lowest in the 41–50 years age group. These findings are presented in Table 3; Fig. 2.
Table 3.
Prevalence of human papillomavirus (HPV) infection across different age groups [n (%)]
| Age group (years) | Total cases | Positive cases | HR-HPV only | LR-HPV only | HR-HPV/LR-HPV mixed | Single infection | Dual infection | Triple infection | Infection of more than three |
|---|---|---|---|---|---|---|---|---|---|
| ≤ 20 | 476 | 219(46.01) | 112(23.53) | 37(7.77) | 70(14.71) | 102(21.43) | 62(13.03) | 27(5.67) | 28(5.88) |
| 21–30 | 27,008 | 5822(21.56) | 3926(14.54) | 1015(3.76) | 881(3.26) | 3993(14.78) | 1209(4.48) | 419(1.55) | 201(0.74) |
| 31–40 | 25,887 | 4886(18.87) | 3322(12.83) | 974(3.76) | 590(2.28) | 3701(14.30) | 864(3.34) | 245(0.95) | 76(0.29) |
| 41–50 | 7298 | 1345(18.43) | 884(12.11) | 302(4.14) | 159(2.18) | 1037(14.21) | 231(3.17) | 54(0.74) | 23(0.32) |
| 51–60 | 3805 | 959(25.20) | 622(16.35) | 183(4.81) | 154(4.05) | 662(17.40) | 194(5.10) | 59(1.55) | 44(1.16) |
| >60 | 656 | 232(35.37) | 159(24.24) | 26(3.96) | 47(7.16) | 141(21.49) | 53(8.08) | 28(4.27) | 10(1.52) |
| χ² | 406.645 | 168.087 | 31.349 | 354.942 | 67.508 | 199.548 | 176.966 | 318.87 | |
| P | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
Fig. 2.
Infection patterns of hpv types across different age groups. A Prevalence of isolated HR-HPV, isolated LR-HPV, and mixed infections among various age groups. B Prevalence of single infections versus multiple infections
HPV genotype distribution from 2019 to 2024
Among the high-risk HPV (HR-HPV) genotypes, the top five detected were HPV52 (3.71%), HPV58 (2.81%), HPV16 (2.56%), HPV51 (1.83%), and HPV39 (1.64%). For low-risk HPV (LR-HPV), HPV54 was the most prevalent (1.85%), followed by HPV42 (0.99%) and HPV40 (0.93%). The infection rate of HPV16 showed a significant decline from 3.26% in 2019 to 2.32% in 2024, indicating a notable downward trend, with significant differences in infection rates across years (χ²=25.466, P < 0.001; Z=−2.89, P = 0.0039).
The infection rates of HPV52, HPV51, and HPV33 recorded their lowest levels in 2022, 2021, and 2022, respectively, exhibiting a U-shaped distribution over time. Each of these genotypes displayed significant differences in infection rates across the years (χ²=78.474, P < 0.001; χ²=16.015, P = 0.007; χ²=21.788, P < 0.001).
Within the LR-HPV, the detection rate of HPV42 showed a significant upward trend (χ²=180.953, P < 0.001; Z = 4.02, P < 0.001), indicating statistically significant differences. The infection rates of HPV54 and HPV43 exhibited a U-shaped trend over time (χ²=17.994, P = 0.003; χ² = 33.101, P < 0.001). These findings are summarized in Table 4 and illustrated in Figs. 3 and 4.
Table 4.
Annual distribution of high-risk and low-risk HPV subtypes (2019–2024)
| HPV Subtypes | 2019 n = 8395 |
2020 n = 11,403 |
2021 n = 12,098 |
2022 n = 12,990 |
2023 n = 11,280 |
2024 n = 8964 |
Total n = 65,130 |
χ² | P |
|---|---|---|---|---|---|---|---|---|---|
| HR-HPV subtypes | |||||||||
| 52 | 366 (4.36%) | 382 (3.35%) | 379 (3.13%) | 400 (3.08%) | 446 (3.95%) | 441 (4.92%) | 2414 (3.71%) | 272.62 | < 0.001 |
| 58 | 273 (3.25%) | 290 (2.54%) | 345 (2.85%) | 363 (2.79%) | 301 (2.67%) | 261 (2.91%) | 1833 (2.81%) | 72.34 | < 0.001 |
| 16 | 274 (3.26%) | 299 (2.62%) | 315 (2.60%) | 312 (2.40%) | 257 (2.28%) | 208 (2.32%) | 1665 (2.56%) | 63.21 | < 0.001 |
| 51 | 172 (2.05%) | 200 (1.75%) | 184 (1.52%) | 226 (1.74%) | 216 (1.91%) | 195 (2.18%) | 1193 (1.83%) | 32.45 | < 0.001 |
| 39 | 151 (1.80%) | 194 (1.70%) | 175 (1.45%) | 208 (1.60%) | 169 (1.50%) | 169 (1.89%) | 1066 (1.64%) | 28.76 | < 0.001 |
| 68 | 129 (1.54%) | 140 (1.23%) | 152 (1.26%) | 165 (1.27%) | 147 (1.30%) | 122 (1.36%) | 855 (1.31%) | 18.93 | 0.002 |
| 53 | 109 (1.30%) | 129 (1.13%) | 132 (1.09%) | 175 (1.35%) | 148 (1.31%) | 149 (1.66%) | 842 (1.29%) | 22.11 | < 0.001 |
| 59 | 98 (1.17%) | 112 (0.98%) | 127 (1.05%) | 129 (0.99%) | 121 (1.08%) | 122 (1.36%) | 709 (1.09%) | 12.05 | 0.034 |
| 66 | 86 (1.02%) | 110 (0.96%) | 127 (1.05%) | 126 (0.97%) | 97 (0.86%) | 107 (1.19%) | 653 (1.00%) | 9.87 | 0.079 |
| 56 | 93 (1.11%) | 110 (0.96%) | 113 (0.93%) | 131 (1.01%) | 94 (0.83%) | 110 (1.23%) | 651 (1.00%) | 10.32 | 0.067 |
| 18 | 95 (1.13%) | 107 (0.94%) | 105 (0.87%) | 103 (0.79%) | 99 (0.88%) | 71 (0.79%) | 580 (0.89%) | 7.45 | 0.189 |
| 33 | 87 (1.04%) | 92 (0.81%) | 81 (0.67%) | 84 (0.42%) | 57 (0.51%) | 64 (0.71%) | 465 (0.71%) | 15.21 | 0.009 |
| 67 | 60 (0.71%) | 62 (0.54%) | 72 (0.60%) | 70 (0.54%) | 49 (0.43%) | 48 (0.54%) | 361 (0.55%) | 6.32 | 0.276 |
| 31 | 40 (0.48%) | 60 (0.53%) | 45 (0.37%) | 55 (0.42%) | 52 (0.46%) | 51 (0.57%) | 303 (0.47%) | 4.98 | 0.418 |
| 35 | 38 (0.45%) | 23 (0.20%) | 45 (0.37%) | 47 (0.36%) | 32 (0.28%) | 33 (0.37%) | 218 (0.33%) | 8.76 | 0.119 |
| 45 | 30 (0.36%) | 21 (0.18%) | 21 (0.17%) | 34 (0.26%) | 21 (0.19%) | 17 (0.19%) | 144 (0.22%) | 5.12 | 0.401 |
| 73 | 17 (0.20%) | 9 (0.08%) | 20 (0.17%) | 24 (0.18%) | 15 (0.13%) | 32 (0.36%) | 117 (0.18%) | 13.45 | 0.019 |
| LR-HPV subtypes | |||||||||
| 54 | 183 (2.18%) | 190 (1.67%) | 198 (1.64%) | 221 (1.70%) | 216 (1.91%) | 197 (2.20%) | 1205 (1.85%) | 29.87 | < 0.001 |
| 42 | 55 (0.66%) | 65 (0.57%) | 79 (0.65%) | 92 (0.71%) | 176 (1.56%) | 177 (1.97%) | 644 (0.99%) | 156.32 | < 0.001 |
| 40 | 90 (1.07%) | 102 (0.89%) | 89 (0.74%) | 117 (0.90%) | 105 (0.93%) | 100 (1.12%) | 603 (0.93%) | 11.23 | 0.047 |
| 44 | 75 (0.89%) | 90 (0.79%) | 108 (0.89%) | 117 (0.90%) | 115 (1.02%) | 85 (0.95%) | 590 (0.91%) | 9.56 | 0.089 |
| 55 | 94 (1.12%) | 102 (0.89%) | 91 (0.75%) | 105 (0.81%) | 83 (0.74%) | 110 (1.23%) | 585 (0.90%) | 14.78 | 0.011 |
| 6 | 94 (1.12%) | 83 (0.73%) | 96 (0.79%) | 120 (0.92%) | 96 (0.85%) | 77 (0.86%) | 566 (0.87%) | 8.34 | 0.138 |
| 43 | 91 (1.08%) | 97 (0.85%) | 77 (0.64%) | 86 (0.66%) | 103 (0.91%) | 111 (1.24%) | 565 (0.87%) | 18.95 | 0.002 |
| 11 | 42 (0.50%) | 45 (0.39%) | 38 (0.31%) | 46 (0.35%) | 43 (0.38%) | 19 (0.21%) | 233 (0.36%) | 3.21 | 0.667 |
| 57 | 1 (0.01%) | 0 (0.00%) | 1 (0.01%) | 1 (0.01%) | 0 (0.00%) | 0 (0.00%) | 3 (0.00%) | - | - |
The “-” indicates that there is no value for Fisher’s exact test
Fig. 3.
Prevalence of HR-HPV and LR-HPV Genotypes in HPV Infections of 65,130 Women. A Distribution of HR-HPV Genotypes. B Distribution of LR-HPV Genotypes
Fig. 4.
Changes in the prevalence of the top five HR-HPV genotypes and the top five LR-HPV genotypes from 2019 to 2024. A Changes in the prevalence of the top five HR-HPV genotypes from 2019 to 2024. B Changes in the prevalence of the top five LR-HPV genotypes from 2019 to 2024
HPV subtype infection patterns by age group
Among the high-risk HPV (HR-HPV) genotypes, the following were identified: HPV52, HPV58, HPV16, HPV51, HPV39, HPV68, HPV53, HPV59, HPV56, HPV66, HPV18, HPV33, HPV67, HPV31, and HPV73, for the low-risk HPV (LR-HPV) genotypes, HPV40, HPV44, HPV55, and HPV11 showed a bimodal trend associated with age. In the ≤ 20 years age group, the most frequently detected HR-HPV genotype was HPV16, with an infection rate of 7.98% (38/476), followed by HPV58, HPV52, HPV59, and HPV51. In contrast, the primary HR-HPV subtype in the other age groups was HPV52, with HPV58 and HPV16 following closely. The LR-HPV subtype with the highest detected rate in the ≤ 20 years age group was HPV6, which had a prevalence of 5.46% (26/476), while the > 60 years age group exhibited HPV55 as the most prevalent LR-HPV genotype. Among the remaining age groups, HPV54 was identified as the predominant LR-HPV subtype (Fig. 5).
Fig. 5.
Distribution of HPV subtype infections across different age groups. A Distribution of high-risk HPV subtype infections by age group. B Distribution of low-risk HPV subtype infections by age group
Changes in co-infection combinations with the top 5 h-HPV genotypes from 2019 to 2024
Among the subtypes co-infected with the top five HR-HPV genotypes, HR-HPV represented nearly 70% of the cases. Common co-infections included HPV16, HPV52, HPV58, HPV51, and HPV39, with HPV52 and HPV58 being the most likely to co-infect with other HR-HPV subtypes.
Notably, the prevalence of LR-HPV genotypes significantly increased from 2023 to 2024, primarily involving HPV54 and HPV42. Among the co-infected subtypes with HPV39, HPV51, HPV52, and HPV58, HPV54 entered the top five lists. In 2023, HPV54 became the most prevalent subtype co-infected with HPV51, and the low-risk HPV type HPV42 made its debut in the top five rankings.
In 2019, HPV16 predominantly co-infected with HPV58, HPV52, HPV33, and HPV68. By 2024, there was a marked increase in co-infection cases involving HPV16 with LR-HPV types HPV42 and HPV54. Additionally, in 2024, HPV56 (a high-risk HPV) entered the fifth position among the subtypes co-infected with HPV58 for the first time (Fig. 6).
Fig. 6.
Genotype combinations co-infected with the top 5 HR-HPV genotypes from 2019 to 2024
Discussion
Genital HPV infection is the most common sexually transmitted disease [17, 18]. Assessments show that more than 80% of sexually active individuals are expected to be infected with HPV by age 45 [10, 19]. Most HPV infected individuals do not have symptoms, and the body can clear the virus in 1 to 2 years [20]. However, some people may experience persistent or recurrent infections, and their condition may worsen [19]. About 1–4% of those infected may eventually develop cervical intraepithelial neoplasia (CIN) or cervical cancer [21]. Cervical cancer is the only preventable malignant tumor and may be the first cancer to be eliminated. HPV DNA testing is recommended by WHO as the preferred method for cervical cancer screening [4]. The process of HPV infection leading to cervical cancer takes time. Using prevention strategies, promoting early screening, ensuring timely diagnosis, and providing appropriate treatment can improve healthcare effectively [22]. Early screening is important for stopping precancerous lesions from developing into cervical cancer. By testing specific HPV genotypes, doctors can assess individual risks based on subtypes. This can also improve local epidemiological databases to support vaccine development and public health decisions [17, 23].
In this study, the HPV positivity rate among 65,130 women in Chengdu was 20.67% (13,463/65,130). This rate is higher than in Suzhou (10.2%) [24], Shenzhen (17.83%) [13], Xianning (15.5%) [25], and Guangxi (18.1%) [26]. It is similar to the rates in northern Henan (19.7%) [27] and Zigong (20.11%) [23], but lower than in Guangzhou (21.66%) [28], Zhejiang (22.3%) [29], and Luoyang (22.8%) [30]. Although the positivity rate in Chengdu is lower than in some cities, it is still above the national average rate (19%) [31]. This shows clear regional differences in HPV infection rates across China. Factors such as the age structure of the female population, economic development levels, education levels, efforts by the government to promote cervical cancer prevention and control, and HPV vaccination status may cause these differences.
The HPV infection rate in Chengdu showed significant changes from 2019 to 2024, following a typical U-shaped fluctuation pattern. The baseline infection rate was 23.41% in 2019 and fell to 19.27% by 2021. This trend matches earlier research [14, 16]. From 2022 onward, the rate rebounded, reaching 23.48% by 2024. The COVID-19 outbreak at the end of 2019 changed sexual behavior patterns, and prevention policies led to delays in screening and interruptions in medical services. This likely affected the detection and management of HPV infections and related diseases [14–16]. In the post-pandemic era, changes in women’s overall immunity, increased population mobility, decreases in vaccine antibodies, the rise of non-vaccine HPV types, and the promotion of free cancer screenings have likely led to a rapid increase in HPV positivity rates among women in this region starting in 2023 [23].
In this study, HPV infections were mainly single infections (14.80%, 9636/65,130) and single high-risk (HR) HPV infections (13.86%, 9025/65,130). These accounted for 71.57% and 67.04% of the positive cases, respectively. Multiple infections were mainly double infections, making up 68.28% of multi-type infections. In single infections, HR-HPV infection predominates (accounting for 75.65%). As the number of infection types increases, mixed infections gradually become dominant. In infections involving three or more types, no pure LR-HPV infection is detected, indicating that HR-HPV demonstrates a more significant subtype advantage in infections, and LR-HPV infections are difficult to exist independently in multiple infections. There may be a potential synergistic effect between HR-HPV and LR-HPV [23], which may also be closely related to the body’s immune clearance mechanisms. In octuple infections (n = 2 octuple infections), both pure HR-HPV infections and mixed infections accounted for 50%. Given the uniqueness of this proportion, it is speculated that the core reason lies in the extremely limited sample size: the sample size of only 2 cases of octuple infections is far from meeting the minimum sample size required for statistical analysis, and the proportional distribution may be significantly affected by random errors, making it difficult to reflect the true infection patterns. Although there may be a potential synergistic effect between HR-HPV and LR-HPV, whether this synergistic mechanism changes in the extreme case of octuple infections cannot be verified due to the limitation of sample size. In conclusion, the special proportion of octuple infections in this study may more reflect the limitations caused by the small sample size rather than a definite infection pattern, and its inherent association remains to be revealed by further studies with larger sample sizes. Some studies suggest that multiple HPV infections are associated with persistent infections [32] and may worsen cervical lesions, increasing the risk of cervical cancer [33, 34]. Persistent HR-HPV infections are the primary factor leading to cervical cancer [5, 35]. An analysis of the trends in multiple HPV infection rates in this study showed that, except for the rate of pure HR-HPV infections, the rates of other types of HPV infections from 2019 to 2024 presented a U-shaped trend, first decreasing and then increasing.
The HPV positivity rates and the rates of different types of HPV infections among different age groups showed statistically significant differences. In Chengdu, the HPV positivity rate, single HR-HPV infection rate, mixed infection rate, single infection rate, double infection rate, triple infection rate, and rates of infections with three or more types all follow a bimodal distribution pattern across different age groups. There was a peak positivity in the group aged ≤ 20 years. Notably, among HPV-positive females in this age group, the proportion of mixed and multiple infections was higher than in other age groups. The proportion of multiple infections reached 53.42% (117/219). The HPV positivity rate, single infection rate, double infection rate, triple infection rate, single HR-HPV infection rate, and mixed infection rate were all lowest in the 41 to 50 age group. A second peak in positivity was observed in the > 60 age group, consistent with reports from other regions [25, 26, 28, 29]. High HPV infection rate among females aged ≤ 20 is attributed to insufficient awareness of HPV risks, a lack of sex education, and a lack of self-protection awareness during sexual behavior. Additionally, their immune systems are not fully developed, making it difficult to clear the virus during the first infection, and cervical cell turnover is faster, making it easier to detect the virus [29]. The HPV infection rate remains low among middle-aged individuals (31 to 50 years), likely due to enhanced immune function and stable sexual behavior in this age group [36]. The positivity rate begins to increase in women aged 51 to 60, with another peak in the > 60 age group, primarily due to ovarian function decline and hormonal changes during the perimenopausal and menopausal periods. These changes lead to degenerative changes in the vaginal and cervical mucosa, microecological imbalances, and alterations in cervical epithelial cell structure, which increase susceptibility to HPV and allow for latent virus activation or persistent infections that are not cleared [27, 35, 37]. Optimal time for HPV vaccination is before individuals are exposed to HPV infection. Young women and girls who have not yet had sexual experience are the greatest beneficiaries of the HPV vaccine [38]. It is important to note that, like other studies [23, 29, 36], the number of females aged ≤ 20 and > 60 in this study was much lower than in other age groups. To reduce the HPV infection rate, health education efforts targeting these two age groups should be strengthened. This includes increasing awareness of the dangers of HPV infections, actively promoting vaccination, improving vaccination coverage, and appropriately raising the maximum age for cervical cancer screening to expand screening coverage and increase screening rates. This will provide a more comprehensive prevention and control of HPV infections.
Globally, the most common high-risk (HR) HPV genotypes are HPV 16, 18, 59, 45, 31, 33, 52, 58, 35, 39, 51, 56, and 53, while the most common low-risk (LR) HPV genotypes are HPV 6 and 11 [17]. Approximately 70% of cervical cancers are associated with HPV 16 and 18 infections [32]. Reports indicate that the infection rates of HR-HPV types such as HPV 16, 18, and 52 increase with the severity of cervical lesions [27], and HPV 16, 18, 56, 58, and 66 are independent risk factors for cervical cancer [29]. In East Asian countries, infections with HPV 52 and HPV 58 dominate, leading to a significantly higher number of cervical precancerous lesions and invasive cervical cancer cases compared to other regions [39].
In this study, among the 26 HPV genotypes detected, the top five HR-HPV genotypes in terms of detection rates were HPV 52 (3.71%), HPV 58 (2.81%), HPV 16 (2.56%), HPV 51 (1.83%), and HPV 39 (1.64%). The top three LR-HPV genotypes were HPV 54 (1.85%), HPV 42 (0.99%), and HPV 40 (0.93%). The detection rates of HPV genotypes in this study also differed from reports in various regions of China. HPV 52 had the highest detection rate among HR-HPV in this study, consistent with reports from Suzhou [24], Zhejiang [29], Shenzhen [13], Guangzhou [28], Xianning [25], Guangxi [26], and Zigong [23]. However, HPV 16 was the main type detected in Henan [27, 30] and Xinjiang [40]. It is noteworthy that, similar to previous reports, the infection rates of HPV 52, 58, and 16 ranked among the top three HR-HPV types, although their order varied across studies. Similar to reports from other regions [25, 26, 28], HPV 51 and HPV 39 were not covered by any of the currently available HPV vaccines among the top five HR-HPV types detected in this study.
For females aged ≤ 20, HPV 16 was the highest detected HR-HPV type at 7.98%, while HPV 52 was the predominant type in other age groups. The detection of LR-HPV types also showed variation across age groups; HPV 6 was the most common LR-HPV type among females aged ≤ 20 (5.46%), suggesting a higher prevalence of genital warts in this age group. For females > 60, HPV 55 (2.13%) dominated, while HPV 54 was the main type in other age groups. This indicates variations not only in the predominant HPV subtypes across different regions but also in the major detected subtypes among different age groups.
The infection rates of different HPV subtypes in this research exhibited varying trends. For HR-HPV types, the infection rate of HPV 16 significantly decreased from 2019 to 2024 (χ²=25.466, P < 0.001; Z=−2.89, P = 0.0039). The infection rates of HPV 52, 51, and 33 showed a U-shaped trend over time. For LR-HPV, the infection rate of HPV 42 significantly increased (χ²=180.953, P < 0.001; Z = 4.02, P < 0.001), while the infection rates of HPV 54 and 43 exhibited a U-shaped trend over time.
China’s initiation of HPV vaccination has lagged behind that of developed countries. Since 2016, preventive HPV vaccines have entered the Chinese market, and currently, three bivalent vaccines, one quadrivalent vaccine, and one nonavalent vaccine have been launched [41]. The bivalent vaccine targets HPV 16 and 18, the quadrivalent vaccine includes HPV 6 and 11 in addition to 16 and 18, and the nonavalent vaccine offers the broadest coverage, preventing HPV types 6, 11, 16, 18, 31, 33, 45, 52, and 58 [18]. The immune response induced by these vaccines is not only strong but also efficient; these three types of HPV vaccines can prevent 70%-90% of HPV-related cancers [42], providing extensive cross-protection against non-vaccine-related subtype infections [18], and also reducing the incidence of genital warts [43].With the launch of the second domestic HPV vaccine producer’s bivalent HPV vaccine in 2022 [44], more eligible women have access to this vaccine. However, the HPV vaccine has not yet been included in China’s National Immunization Program, which limits its widespread coverage and ensures that vaccination rates remain low [17]. At present, the coverage rate of the nonavalent vaccine is lower than that of the bivalent vaccine, which may explain the continued decline in HPV 16 infection rates while HPV 52 infection rates remain high in this study. Moreover, the nonavalent HPV vaccine does not cover approximately 10% of the genotypes associated with cervical cancer, and it also fails to include HPV genotypes that are significantly related to other cervical tumor lesions in Chinese women [45].
Increasing the coverage of the nonavalent vaccine and establishing large-scale population screening are essential, while carefully considering age stratification and regional epidemic characteristics, is crucial. It is also essential to focus on the development of preventive HPV vaccines that meet the needs of the local population [18]. Regular HPV screening is necessary to effectively prevent and control HPV infections and related diseases.
In this study, the subtypes co-infected with the top five HR-HPV genotypes were predominantly HR-HPV as well, specifically HPV 52, 58, 16, 51, and 39, which frequently co-occurred. HPV 52 and HPV 58 were identified as the subtypes most commonly co-infected with other HR-HPVs. There were significant changes in the co-infection subtypes from 2019 to 2024. In 2019, HPV 16 was primarily co-infected with HPV 58, 52, 33, and 68. By 2024, the number of co-infections with HPV 16 and LR-HPV(HPV 42 and 54) significantly increased, suggesting an increase in cases of genital warts patients co-infected with HPV 16, which may elevate the risk of precancerous lesions. Additionally, in 2024, among the subtypes co-infected with HPV 58, HPV 56 rose to the fifth position, indicating that the complexity of co-infections has increased, potentially reflecting the risk associated with new high-risk genotype combinations. Overall, the prevalence of low-risk HPV types significantly increased between 2023 and 2024, primarily involving HPV 54 and HPV 42. Notably, in 2023, HPV 54 was ranked first among the subtypes co-infected with HPV 51, and the low-risk HPV type 42 also entered the top five for the first time that year. The differences between infection patterns among various subtypes and the changes in co-infection combinations provide a more comprehensive understanding of local HPV infection characteristics. This highlights the need to consider the specific infection traits of different subtypes in HPV infection prevention and control efforts. Such insights are crucial for developing targeted prevention strategies, including vaccine development and screening program formulation.
This study has certain limitations. First, it is based on a survey conducted among women who visited a single hospital’s gynecology department and those who underwent self-examinations, while our findings provide valuable reference data for HPV prevention and control in Chengdu, caution should be exercised when generalizing these results to the broader population due to the single-center design. This study was unable to further investigate the correlation between HPV genotypes and the severity of cervical lesions due to incomplete collection of cervical cell or pathological test data from HPV-positive women and not be able to perform statistical analysis. Additionally, information regarding vaccination status for all statistical subjects could not be obtained, and assessments of related potential risk factors are lacking. Moreover, due to the retrospective nature of this hospital-based study, we were unable to collect key behavioral and socioeconomic variables known to influence HPV risk, including sexual behavior patterns, socioeconomic status, and HIV co-infection status. This limitation is inherent to the study design and prevents us from examining potential drivers of the observed infection disparities.
However, this study provides a comprehensive analysis of the prevalence of HPV in the region before and after the outbreak of the novel coronavirus over a six-year period. It offers scientific evidence to elucidate the HPV infection spectrum in Chengdu and is expected to play a key role in local HPV vaccination planning, optimizing cervical cancer screening programs, and adjusting public health policies, ultimately enhancing the health security level for women in Chengdu.
Conclusions
In summary, the study found a high HPV detection rate among women in Chengdu, with a U-shaped trend observed in HPV positivity rates and the rates of other HPV infection types (excluding pure HR-HPV infections) from 2019 to 2024, indicating a decline followed by an increase. The main types of infections were single infections and pure HR-HPV infections. The top five HR-HPV genotypes detected were HPV 52, 58, 16, 51, and 39. Aside from the pure LR-HPV infection rate, the infection rates of other HPV types displayed a U-shaped bimodal distribution pattern with age. The infection rate of HPV 16 showed a decreasing trend, while the infection rate of HPV 42 significantly increased, correlating with a marked increase in the number of LR-HPV genotypes co-infected with HR-HPV, leading to diversified co-infection patterns. Enhancing health education efforts, vigorously developing, introducing, promoting, and vaccinating HPV vaccines, as well as raising awareness of HPV screening among women, can effectively reduce HPV infection rates and prevent the occurrence of cervical cancer.
Acknowledgements
None.
Abbreviations
- HPV
Human papillomavirus
- LR-HPV
Low-risk human papillomavirus
- HR-HPV
High-risk human papillomavirus
Author contributions
XL.Z: Conducted study design, data collection, statistical analysis, data analysis, prepared original tables, and drafted/revised the manuscript; HP.L: Performed data analysis, created tables and figures, and edited/reviewed the manuscript for submission; LP.H: Carried out experimental testing and data collection; J.M: Reviewed and supervised the entire manuscript development.
Funding
The authors declare that no funds, grants, or other support were received for the conduct of this study or the preparation of this manuscript.
Data availability
The datasets utilized and/or analyzed in this study can be obtained from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
This study followed the ethical guidelines of the Declaration of Helsinki and was approved by the Medical Ethics Committee of Sichuan Jinxin Xinan Women & Children Hospital (202521).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets utilized and/or analyzed in this study can be obtained from the corresponding author upon reasonable request.