Modelling the epidemic dynamics of HPV among women in China and optimization of ongoing cervical cancer elimination strategies

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However, the benefits of ongoing strategies in China remains unclear. Insufficient vaccine supply and excessive screening workload have hindered the widespread implementation of HPV immunization plans. Methods We constructed stratified mathematical models to simulate the transmission of hr-HPV among women under ongoing strategies, and calculated the incremental cost-utility ratio (ICUR) to compare the health-economics benefits among different intervention pathways, including different vaccine type and dose schedules, commonly recommended screening algorithms as well as AI-assisted TCT method. The model parameters were calibrated according to real-world HPV prevalences, incorporating segmented model assumptions reflecting the levels of COVID-19 lockdown. Results The model shows that ongoing strategies in China are projected to reducing cervical cancer prevalence continuously and demonstrate good cost-utility (ICUR: 22,532.04 USD/QALY, 21,968.74-23,095.34), when increasing the participation rate to achieve the global goal by 2030. HPV vaccination provides substantial health benefits, while cannot improve the cost-utility at current cost. Offering single-dose of 2vHPV vaccine to girls before the age of 14 and reallocating excess doses to women under 25 yields a lower ICUR compared to two- or three-dose scenarios. Cervical screening can significantly reduce the ICUR. Among the screening methods, HPV testing demonstrates higher cost-utility, while AI-TCT outperforms all recommended traditional pathways. Conclusion The ongoing strategies demonstrate substantial health and economic benefits in achieving the 2030 global target; however, neither screening nor vaccination alone can deliver optimal effectiveness. The findings highlight the importance of combining vaccination and screening, and provide evidence for the promotion of single-dose vaccination and AI-TCT projects to alleviate resource burdens. Human papillomavirus (HPV) HPV vaccination Cervical screening Evaluation of preventive interventions Mathematical model of infectious diseases Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Cervical cancer has remained to be a severe threat to women health. As of 2020, approximately 604,000 cumulative cervical cancer cases and 342,000 related deaths were reported worldwide 1 . China bears the second largest burden of cervical cancer 1 . According to statistics, an average of 100,000 new cases and 30,000 deaths are reported in China annually, with the incidence and mortality rates increasing by 8.5% and 5.4% respectively 2 . The persistent infection of high-risk human papillomavirus (hr-HPV) is the primary cause of cervical cancer. Research has indicated that HPV can be detected from over 99% of cervical cancer patients, and the detection rate increases with the severity of cervical lesions 3 . Among more than 100 HPV genotypes, HPV-16 and 18 are responsible for approximately 75% of global cervical cancer cases 4 . In China, HPV-52 and 58 are gradually recognized as the major contributors besides HPV-16 due to their continuously rising infection rates 5 . Fortunately, cervical cancer can be effectively prevented through Grade I-III interventions. HPV vaccination can protect individuals from the most common carcinogenic HPV genotypes, and is considered as the primary preventive measure against cervical cancer. There are three categories of HPV vaccines approved at present, including bivalent (2v), quadrivalent (4v) and nonavalent (9v) vaccines. The 2v and 4v vaccines cover HPV-16 and 18, preventing approximately 70% of cervical cancers; the 9v vaccine additionally covers HPV-31, 33, 45, 52 and 58, providing protection against roughly 90% of cervical cancers 6 . Several randomized controlled trials (RCTs) have demonstrated that full HPV vaccination with multiple doses is safe and elicits strong immunogenic responses 7 . In April 2022, researchers confirmed that single dose of HPV vaccination can provide similar protection with multiple doses in preventing persistent HPV infections 8 , highlighting the importance of vaccination efficiency in situations of limited supply. In China, a clinical trial for single-dose 9vHPV vaccine was launched in March 2024 9 , supporting the potential future expansion of reduced-dose vaccination. The early detection and diagnosis through cervical screening are also crucial. According to a study conducted in Australia, over 70% of cervical cancer occurred in women who were either insufficiently screened or had never participated in screening 10 . The widely used cervical screening methods at current include visual inspection with acetic acid (VIA), HPV nucleic acid (DNA) testing, thin layer liquid-based cytology test (TCT) and colposcopy examination. Among these, HPV DNA testing has garnered particular attention due to its high sensitivity and non-invasive characteristic, and has become the primary screening method recommended by WHO 11 . In addition to manual methods, artificial intelligence (AI)-assisted TCT is emerging as a promising tool. Studies have shown that AI-TCT achieves comparable sensitivity (odds ratio [OR]: 1.01, 95% confidence interval [CI]: 0.97–1.05) and higher specificity (1.26, 1.20–1.32) compared to skilled cytology experts 12 . In China, the national AI cervical screening project has been carried out since 2017, during which 5.86% positive cases out of 10.08 million screenings were detected 13 . In 2020, WHO released the Global Strategy for Accelerating Cervical Cancer Elimination, which set the 2030 targets of vaccinating 90% of girls, screening 70% of women, and providing treatment to 90% of diagnosed patients 14 . In response, China is actively promoting HPV vaccination along with the screening pathway of primary HPV testing followed by cytology triage. However, there is a lack of health economic evidence supporting the scaling-up of interventions to meet the 2030 targets. Moreover, studies have shown that between 2018 and 2020, the full-course HPV vaccination rate among women aged 9–45 in China was only 2.24% 15 . and the cervical screening rate among women aged 35–64 as of 2023 was only 36.8% 16 , falling significantly short of the 2030 goals. The supply restrictions and high costs have continued to hinder the widespread implementation of vaccination. TCT-based screening remains prevalent, despite a growing mismatch between the demand for screening and the availability of trained cytologists. Therefore, this study aims to predict the epidemic trends of hr-HPV under ongoing strategies among women in China, evaluate the health economics effects, and assess the potential benefits of alternative intervention scenarios including dose-reduction regimens and AI-TCT adoption for strategy optimization. 2. Methods 2.1 Study design and data sources In this study, a population-based dynamic model was established to predict HPV epidemics under ongoing cervical cancer elimination strategies among women in China. Sensitivity analyses were conducted based on this model to provide suggestions for strategy optimization. An individual-based stochastic model was thereafter established to observe the long-term effects of alternative intervention scenarios among susceptible young women. The optimal strategy was determined by comparing the health economics benefits between scenarios. The population-based model was simulated among all women at current health state distribution in China. All-cause mortality rates and a background birth rate were considered. Ordinary differential equations (ODEs) were constructed to realize model formulation. The parameters required in the equations were calibrated using real-world epidemiological data. The individual-based model was simulated among a 75-year intervention cohort of 100,000 women, who were assumed to be initially susceptible and follow a uniform distribution within 14 years old. Markov Chain Monte Carlo (MCMC) algorithm was applied to achieve the formulation (Fig. 1 ). All parameters in this study were collected from public database and published literatures (Table 1 ). Details are shown in Supplementary Materials. Table 1 The summary of main parameters used in the model. Symbol Implication Value Range Source Transition parameters α f the rate of waning innate immunity 0.021 0.015–0.027 38 γ cin1 the backward transition rate from CIN1 to I 0.5044 0.4732–0.5561 39 γ cin2 the backward transition rate from CIN2 to CIN1 0.2494 0.1994–0.2992 39 γ cin3 the backward transition rate from CIN3 to CIN2 0.0135 0.0101–0.0169 40,41 β if the forward transition rate from I to CIN1 0.0450 0.0279–0.0661 39 β cin1 the forward transition rate from CIN1 to CIN2 0.2240 0.1608–0.2972 40,41 β cin2 the forward transition rate from CIN2 to CIN3 0.3498 0.2623–0.4372 40,41 β cin3 the forward transition rate from CIN3 to ACC1 0.1019 0.0764–0.1274 40,41 β acc1 the forward transition rate from ACC1 to ACC2 0.4377 0.3283–0.5471 21,42 β acc2 the forward transition rate from ACC2 to ACC3 0.5358 0.4019–0.6698 21,42 β acc3 the forward transition rate from ACC3 to ACC4 0.6838 0.5129–0.8548 21,42 s 1 symptom development rate from ACC1 to CC1 0.15 0.11–0.19 21 s 2 symptom development rate from ACC2 to CC2 0.23 0.17–0.29 21 s 3 symptom development rate from ACC3 to CC3 0.60 0.45–0.75 21 s 4 symptom development rate from ACC4 to CC4 0.90 0.68-1.00 21 ωd acc1 the death rate of ACC1 0.024 0.012–0.036 43 ωd acc2 the death rate of ACC2 0.044 0.024–0.064 43 ωd acc3 the death rate of ACC3 0.127 0.064–0.191 43 ωd acc4 the death rate of ACC4 0.300 0.191–0.450 43 ωs acc1 the 5-year survival rate of ACC1 0.90 0.82–0.94 43,44 ; calculated ωs acc2 the 5-year survival rate of ACC2 0.78 0.68–0.88 43,44 ; calculated ωs acc3 the 5-year survival rate of ACC3 0.37 0.05–0.68 43,44 ; calculated ωs acc4 the 5-year survival rate of ACC4 0.03 0.00-0.05 43,44 ; calculated Intervention parameters VE 1 the efficacy of bivalent vaccine 94.00% 80.00–99.00% 43 VE 2 the efficacy of quadrivalent vaccine 94.50% 65.20–99.90% 45,46 VE 3 the efficacy of ninvalent vaccine 96.70% 80.90–99.80% 47 κ VIA the sensitivity of VIA 0.58 0.45–0.72 21 κ 1hc2 the sensitivity of HPV testing (HC2) 0.91 0.79-1.00 48 κ 1pcr the sensitivity of HPV testing (PCR) 0.96 0.93-1.00 49 κ 2 the sensitivity of LBC to detect LSIL 0.70 0.53–0.88 50 κ 3 the sensitivity of LBC to detect HSIL 0.81 0.78–0.84 50 κ 4 the sensitivity of LBC to detect cell carcinoma 0.94 0.90–0.99 21 Utility parameters (QALYs) q cin1 the life quality of individual in CIN1 0.938 0.730-1.000 51 q cin23 the life quality of individual in CIN2/3 0.900 0.873–0.927 52 q cint the life quality of individual in treated CIN 0.960 0.945–0.976 21 q cc1 the life quality of individual in CC1 0.830 0.788–0.873 52 q cc2 the life quality of individual in CC2 0.780 0.773–0.907 52 q cc3 the life quality of individual in CC3 0.720 0.650–0.780 52 q cc4 the life quality of individual in CC4 0.600 0.430–0.770 52 q cc1t the life quality of individual in treated CC1 0.705 0.490–0.810 53 q cc2t the life quality of individual in treated CC2 0.605 0.420–0.670 53 q cc3t the life quality of individual in treated CC3 0.560 0.420–0.700 53 q cc4t the life quality of individual in treated CC4 0.480 0.360–0.600 53 q ccs the life quality of individual in CCs 0.930 0.700–0.990 41,43 NOTE : I, infectious; CIN, cervical intraepithelial neoplasia; ACC, asymptomatic cervical cancer (undiagnosed); CC, cervical cancer (diagnosed). 2.2 Model overview The model was stratified and compartmental, consisting of a dynamic pattern to simulate hr-HPV transmission, and a natural history pattern to predict cervical carcinogenesis trends. Susceptible-infectious-recovered-susceptible (SIRS) structure was applied to illustrate the HPV transmission pattern. We assumed that susceptible women (S) would be infected with hr-HPV (I) through heterosexual partnership at age- and region-stratified force of infection (FOI). Infected individuals could get rid of HPV infection and remain naturally immune (Im) until antibodies waned. The FOI was determined by HPV prevalence among opposite sex counterpart, sexual mixing matrices and the transmission probability. The natural history pattern was divided into cervical intraepithelial neoplasia (CIN, grade 1–3) and cervical cancer (CC, stage I-IV). The staging of cervical carcinogenesis was according to the International Federation of Gynecology and Obstetrics (FIGO). Patients with cervical cancer were assumed to be initially asymptomatic (ACC, stage I-IV), who would enter the advanced asymptomatic state or display detectable symptoms at independent probabilities. Individuals in precancerous stage could clear their infection, while those progressing to cancer would never naturally recover. Early, advanced and terminal cancer were subjected to different death rates (Rd). Cancer patients who remained alive for no less than 5 years (Rs) were break from subsequent simulation (Figure S1 ). A total of 18 hr-HPV genotypes were considered. The natural history among men and the sexual mixing pattern are shown in Figure S2-S3. 2.3 Interventions The primary interventions in the model included HPV vaccination and cervical screening. Condom use and post-exposure treatment were also considered as background interventions. The ongoing strategies for cervical cancer elimination in China were assumed as follows: 1) Prophylactic HPV vaccination: providing 2v (domestic Cocolin), 4v (imported Gardasil), or 9v (imported Gardasil) HPV vaccines to women aged 9–45, with a basic coverage in the initial state and a timely vaccinating rate referring to the National Immunization Program Information Monitoring System 15 . 2) Cervical screening: providing women aged 35–64 years old with primary HPV DNA testing and TCT triage method 17 , with stratified participation rates estimated from real-world data, and a time interval assumed as 3–10 years according to WHO recommendations. 3) Condom use: with a coverage ranging from 0.74 to 1 18 . 4) CIN and CC treatment: including cryotherapy, thermal ablation (TA), cold knife conization (CKC) and loop electrosurgical excision procedure (LEEP) for early-stage patients, and hysterectomy, long-term radiation therapy and chemotherapy for terminal-stage patients. Patients eligible for treatment choose specific methods based on their eligibility rate (Figure S5). The intervention scenarios in this study included: 1) Target strategy: based on ongoing strategies and the coverage levels, calculating the annual HPV vaccinating and cervical screening participation rate required to achieve the goal of accelerating cervical cancer elimination in 2030 as the target strategy. After calculation, the overall annual vaccinating rate was 23.25%, the screening rate was 1.22 times higher than before, and the treatment rates were set at 90%. 2) Full vaccination: allocating 3 doses of 2v, 4v or 9vHPV vaccine to different age groups among women aged 9–45 years. 3) Reducing doses vaccination: primarily vaccinating the girls aged ≤ 14 years at a rate of 90%, providing 1 or 2 doses and reallocating the saved vaccines before 25 years old. 4) Different screening pathways: conducting ongoing screening pathway and the 7 WHO-recommended pathways at 70% participation rate. 5) AI-TCT screening: conducting AI-TCT screening with HPV DNA testing and colposcopy triage every 3 years at 70% participation rate. We assumed that, the efficacy of 2 dose and 1 dose vaccination is 0.8837 and 0.8372 times that of 3 doses 19 , respectively, and the sensitivity of AI-TCT is 1.06 times that of manual TCT 20 . (Figure S9-S10) 2.4 Calibration Model calibration in this study was realized using the population-based model. The fitting values of overall, age-stratified and genotype-specific hr-HPV prevalences were calculated in comparison with the real-world counterparts. The real-world epidemiological data were estimated from 132,282 cervical screening records in Shenzhen Baoan Women’s and Children’s Hospital, a Class 3A Hospital targeted at the prevention of maternal and fetal diseases of over 5.1 million residents. The period for model calibration was selected as July 2020 to December 2023 with complete records. All records were divided into quarterly subsets, and randomly sampled into the training and the testing set (6:4) based on the same age distribution for internal validation. During calibration, Latin hypercube sampling was performed to generate 10,000 parameter combinations. The overall and stratified epidemic trends of hr-HPV infection were simulated under each combination. The mean square error (MSE) weighted by inverse variance was calculated to obtain the top 1% optimal parameter combinations and the merged calibrated ranges. The overall determination coefficient (R 2 ) was calculated to evaluate the calibration effect. Bootstrap sampling was performed on the optimal combinations for validation. Since the time of collected data covers COVID-19 epidemic period, during which low HPV prevalence and screening participation were observed as a result of non-pharmaceutical interventions (NPIs) (Figure S6), we constructed a segmented model consisting of the lockdown and the opening period of COVID-19 taking the fourth quarter of 2022 as the breakpoint (Figure S7). Parameters cd and sd were added to simulate the reduction of sexual exposure and screening participation caused by NPIs respectively. The calibration results are shown in Figure S8. 2.5 Simulation We conducted 10-year trend prediction and effect evaluation based on the calibrated parameters. The baseline scenario was assumed to be no vaccination or cervical screening. As it has been observed that benefits of strategies may not appear in a short term 21 , the duration of effect evaluation was set to be 20 years. The primary outcomes of trend prediction included the number of current cases in all model compartments. The outcomes of health economics benefit evaluation were the prevented cases, increased costs, quality-adjusted life years (QALYs), and incremental cost-utility ratio (ICUR) compared to baseline. The cost included the prices of HPV vaccine, cervical screening and cancer treatment, as well as all indirect costs incurred. All prices were conversed to the 2023 international US dollar (USD) currency with an annual discount rate. QALY was calculated as the total multiplier of life quality among women at different health states. The criteria for cost-utility analysis referred to that proposed by WHO. When ICUR is less than China's per capita gross domestic product (pcGDP, 13,013.18 USD in 2023), strategy is considered to be with high cost-utility; when ICUR is 1–3 times the pcGDP, strategy is considered to be with cost-utility; else the strategy is with no cost-utility. The point estimates and 95% CIs were generated using Monte Carlo method. All computations were based on R 4.4.1. 3. Results 3.1 Epidemic trends under ongoing strategies The model shows that in 10 years from 2023, under ongoing cervical cancer elimination strategies, the prevalence of hr-HPV among women in China will decrease from 0.1930 (95% CI, 0.1882–0.1978) to 0.0125 (0.0122–0.0128), peak at 0.1973 (0.1924–0.2022) in 2024, and tend to be stable after 2030. The proportion of women who are naturally immune will decline from the sixth year, while increase from 0.4076 (0.3974–0.4178) to 0.6309 (0.6151–0.6467) by 2033 in overall. The total prevalence of CIN will decrease from 1.5924% (1.5526–1.6322%) to 0.3532% (0.344–0.3620%). The prevalence of cervical cancer also shows an overall downward trend, decreases from 1.8417‰ (1.7957–1.8877‰) to 1.0778‰ (1.0509–1.1047‰) except for a slight increase in 2017. The increase rate of the cumulative proportion of deaths and five-year survivals due to cervical cancer will steadily decline. (Fig. 2 ) 3.2 Characteristics of stratified infections As hr-HPV infection deepens and the degree of cancer worsens, the proportion of women aged ≥ 45 years and in urban areas will gradually increase. In 10 years, the proportion of infected women aged 25–34 and 65–74 years will increase among all infected women, while the proportion of those aged 35–64 years will decrease, demonstrating a trend of bimodal distribution. Among CC patients, a significant increase was observed in the proportion of women aged 55 years and above (Fig. 3 (A)). The proportion of urban women who are infected with hr-HPV, CIN and CC among all correspondingly infected women will consistently decline (Fig. 3 (B)). The number of rural patients will gradually surpass that in urban (Figure S11). In the 10th year, among the unvaccinated group, the top five 9v genotypes with the highest proportion are HPV-52 (14.88%, 14.51–15.25%), HPV-16 (11.84%, 11.54–12.14%), HPV-58 (11.41%, 11.12–11.70%), HPV-18 (5.54%, 5.40–5.68%), and HPV-31 (4.75%, 4.63–4.87%). The top five 9v genotypes in the vaccinated group with the highest proportion are HPV-52 (12.92%, 12.60-13.24%), HPV-58 (9.98%, 9.73–10.23%), HPV-16 (4.28%, 4.17–4.38%), HPV-31 (4.23%, 4.12–4.34%), and HPV-33 (3.90%, 3.80–3.99%). The proportion of 9vHPV in the vaccinated group is 16.17% (15.77–16.57%) less than that in the unvaccinated group in overall. Compared with the initial-stage distribution, it is observed that HPV vaccination has significantly reduced the proportion of 9vHPV genotype in the vaccinated group and have a herd immunity effect on the unvaccinated group (Fig. 3 (C)). The number of HPV-52 infections will exceed that of HPV-16 infections since 2025 in the vaccinated group (Figure S12). 3.3 Health and economic benefits of ongoing and target strategies The model shows that, in 20 years under ongoing cervical cancer elimination strategies, compared to baseline, 28,575.91 (27,861.51-29,290.31) thousands of cumulative hr-HPV infections and 2,150.51 (2,096.75-2,204.27) thousands of CC patients will be prevented. The total QALYs increased is 14,811.06 (14,440.78-15,181.34) thousands and the ICUR value is 16,456.75 (16,045.33-16,868.17) USD/QALY. Without screening, the ICUR will increase to 69,459.83 (67,723.33-71,196.33) USD/QALY. In 20 years under the target strategies, compared to baseline, 166,237.74 (162,081.80–170,393.70) thousands of cumulative hr-HPV infections and 4,489.38 (4,377.15-4,601.61) thousands of CC patients will be prevented. The total QALYs increased is 42,020.46 (40,969.95-43,070.97) thousands, and the ICUR value is 22,532.04 (21,968.74-23,095.34) USD/QALY. Under the target HPV vaccination only, the QALYs increased is 32,281.72 (31,474.68-33,080.76) thousands, and the ICUR is 29,913.68 (29,165.84-30,661.52) USD/QALY. Under the target cervical screening only, the QALYs increased is 16,970.99 (16,546.72-17,395.26) thousands, and the ICUR is 14,869.12 (14,497.39-15,240.85) USD/QALY (Fig. 4 (B)). The trend of cost and QALYs changes over decades are shown in Fig. 4 (C) and (D). 3.4 Sensitivity analyses The model shows that improving the vaccinating rate among different age groups of women in China can prevent more hr-HPV infections and cervical cancers, but will lead to higher ICUR. When the vaccinating rates increase at the same degree among a separate age group, the CIN, CC and related deaths among the 25–34 age group enjoy the highest reduction, with the highest increase in QALYs; the HPV infections among the 15–24 age group enjoy the highest decease, with the lowest ICUR (Table 2 ). When the vaccinating rate of 9v vaccine is 5% and that of 2v and 4v vaccines is 0%, the QALYs compared to the baseline is 21,536.72 (20,998.30–22,075.14) thousands in 20 years, and the ICUR value is 28,510.24 (27,797.48-29,223.00) USD/QALY. When the vaccinating rate of 2v vaccine is 5% and that of 4v and 9v vaccines is 0%, the QALYs compared to the baseline is 16,203.90 (15,798.80–16,609.00) thousands in 20 years, and the ICUR value is 12,101.04 (11,798.51-12,403.57) USD/QALY (Fig. 5 (A)-(C)). Meanwhile, higher screening frequency and participation rate can contribute to more cervical cancer cases prevented and lower ICUR (Table 2 ). Expanding the target screening age from 35–44 years old to 64 years old presents greater health and health economics benefits than to 15 years old (Figure S13). In 20 years, when the vaccinating rate separately increases by 50%, the QALYs rises to 16,167.45 (15,763.26-16,571.64) thousands, while the ICUR value is 20,298.32 (19,790.86-20,805.78) USD/QALY. When the screening rate separately increases by 50%, the ICUR value decreases to 13,548.05 (13,209.35-13,886.75) USD/QALY. When all interventions consistently increase by 50%, the QALYs is 26,355.63 (25,696.74-27,014.52) thousands, and the ICUR value is 12,687.47 (12,370.28-13,004.66) USD/QALY (Fig. 5 (D)-(F)). Besides, improving the efficacy of treatment, reducing the cost and increasing the discount rate significantly reduce the ICUR. (Figure S14-S15) Table 2 The prevented infections and cervical cancer, increased per capita cost, increased QALYs and ICUR after parameter adjustment based on ongoing strategies in sensitivity analyses, compared with baseline. Parameters Index Prevented infections (×10 4 ) Prevented cervical cancers (×10 4 ) Increased cost (per capita) Increased QALYs (×10 4 ) ICUR (×10 2 ) HPV vaccinating rate Age-stratified 14- years old + 25% 293.52 21.52 36.35 148.65 168.59 -25% 277.61 21.49 34.35 147.55 160.53 15–24 years old + 25% 299.65 21.54 35.97 149.39 165.99 -25% 271.28 21.47 34.74 146.79 163.19 25–34 years old + 25% 299.25 21.55 36.40 149.80 167.53 -25% 271.99 21.46 34.31 146.40 161.58 35–44 years old + 25% 295.15 21.53 36.35 149.42 167.73 -25% 276.21 21.47 34.36 146.78 161.40 Vaccine type 2v + 5% 372.09 21.79 28.44 162.04 121.01 + 10% 647.56 22.62 41.76 197.20 146.00 4v + 5% 374.29 21.80 58.12 162.30 246.92 + 10% 651.37 22.64 88.38 197.66 308.31 9v + 5% 978.54 23.42 89.05 215.36 285.10 + 10% 1,643.86 25.46 136.90 290.71 324.69 Cervical screening Participation rate (35–44 years old) + 25% 285.47 22.72 35.75 154.80 159.25 -25% 286.05 20.18 34.97 140.82 171.21 Time interval + 25% 286.51 17.92 34.27 127.59 185.20 -25% 284.52 27.01 37.22 179.68 142.82 Targeted age (70% coverage) 35–44 285.14 22.72 35.59 154.63 158.71 + 25–34 283.89 24.69 35.92 165.08 150.03 + 15–34 283.00 29.89 39.55 199.33 136.79 + 45–54 283.97 26.99 36.37 179.79 139.49 + 45–64 283.84 32.11 39.44 215.07 126.45 NOTE : The values in the table are the average of 1000 simulations. 3.5 Scenario analyses The individual-based model shows that in the absence of vaccination and screening, the 75-year simulation yields 150,840.14 (147,069.10–154,611.10) cumulative hr-HPV infections, 9,358.54 (9,124.58-9,592.50) CINs, 545.89 (532.24-559.54) CCs and 170.64 (166.37-174.91) related deaths among the susceptible cohort, respectively. Under ongoing strategies, the peak of hr-HPV infections, CINs and CCs will be reduced, the prevented number of cumulative hr-HPV infections among the 75-year cohort decreases to 9,125.25 (8,897.12-9,353.38), that of cumulative CIN cases is 792.67 (772.85-812.49), and that of CC and related deaths are 100.18 (97.68-102.68) and 41.00 (39.98–42.03), respectively. The increment in QALYs is 2,540.96 (2,477.44-2,604.48) and the ICUR value is 4,152.50 (4,048.69-4,256.31) USD/QALY. (Figure S16-S17) In 75 years among the cohort, when vaccinating those before the age of 14 with 3 doses and an annual rate of 90%, 9vHPV vaccines will lead to the most prevented hr-HPV infections and related cervical cancers, while the cost-utility of 2vHPV vaccines (ICUR: 4,069.08 USD/QALY, 3,967.35-4,170.81) is significantly higher than that of 4v and 9vHPV vaccines. When vaccinating with 2vHPV vaccines, postponing the vaccination age to 15–24 years old will result in a decrease in ICUR, but a reduction in the number of prevented cases. Assuming that the priority is given to girls under the age of 14 and 2vHPV vaccine is provided, reducing 3 doses vaccination to 2 doses and reallocating the excess vaccines to women before 25 will increase the QALYs to 5,643.08 (5,502.00–5,784.16), and decrease the ICUR to 2,678.82 (2,611.85-2,745.79) USD/QALY. Providing single dose and reallocating the excess vaccines to women before 25 will increase the QALYs to 5,716.37 (5,573.46-5,859.28), and decrease the ICUR to 1,378.06 (1,343.61-1,412.51) USD/QALY. In 75 years among the cohort, with 70% participation rate, ongoing cervical screening pathway results in an ICUR value of 2,829.66 (2,758.92-2,900.40) USD/QALY. Among the screening-and-treatment pathways recommended by WHO, HPV DNA testing once every 5–10 years loses QALYs compared to VIA once every 3 years but shows higher cost-utility (ICUR: 1,922.56 USD/QALY, 1,874.50-1,970.62). Among the screening-triage-and-treatment pathways recommended by WHO, the ICUR reaches the lowest when implementing HPV genotyping + colposcopy once every 3–10 years, and the ICUR reaches the highest when implementing HPV genotyping + VIA once every 3–10 years, compared to baseline. On the basis of a 3-year TCT + HPV DNA testing + colposcopy pathway, replacing manual TCT with AI-TCT will result in an increase in the QALYs (to 295.10, 287.72-302.48) and a decrease in the ICUR (to 1,343.83, 1,310.23-1,377.43 USD/QALY), indicating the best health and economics effect among all pathways. (Table 3 ) Table 3 The health and health economics results of alternative strategies. Scenario I- CIN- CC- D- COSTpc+ QALY+ ICUR HPV vaccination 3 doses 2v to 14- 22,254.06 1,494.53 52.48 15.92 218.16 5,361.31 4,069.08 4v to 14- 22,368.40 1,502.21 52.90 16.05 500.08 5,391.37 9,275.54 9v to 14- 33,660.29 2,979.20 123.84 38.56 786.35 8,702.88 9,035.52 2v to 15–24 19,517.74 1,310.63 45.76 13.89 86.52 4,712.06 1,836.16 2 doses 2v to 14- + catch-up to 15–24 23,335.86 1,568.22 54.83 16.72 151.17 5,643.08 2,678.82 1 doses 2v to 14- + catch-up to 15–24 23,613.73 1,587.23 55.42 16.93 78.78 5,716.37 1,378.06* Cervical screening pathway Ongoing -54.93 53.29 32.12 12.38 5.63 198.86 2,829.66 Screening-treatment VIA /3 -42.56 49.81 33.55 12.70 5.56 215.96 2,575.46 HPV DNA /5–10 -27.21 31.52 22.90 8.85 2.89 150.51 1,922.56 Screening-triage-treatment TCT + HPV DNA +colposcope /3 -30.63 52.56 39.95 15.76 7.16 284.22 2,519.95 HPV DNA + VIA /3–10 -44.07 34.26 19.28 7.10 2.86 103.74 2,753.98 HPV geno + VIA /3–10 -46.35 36.12 20.20 7.43 3.11 108.53 2,866.95 HPV geno +colposcope /3–10 -32.89 38.25 27.00 10.35 3.75 176.06 2,132.51 HPV DNA + TCT +colposcope /3–10 -36.91 35.21 22.70 8.92 3.31 143.91 2,303.01 AI-TCT + HPV DNA +colposcope /3 -32.52 55.54 41.64 16.35 3.97 295.10 1,343.83* NOTE : * denotes the strategies with the highest cost-utility. Under the optimal combined strategy, the peak values of hr-HPV infections, CINs and CCs are lower than that under ongoing strategies, and the time when reaching the peak is earlier (Figure S18). 23,586.15 (22,996.5–24,175.8) hr-HPV infections and 93.20 (90.87–95.53) CC would be prevented compared with baseline, and the ICUR value is 1,374.53 (1,340.17-1,408.89) USD/QALY. 4. Discussion The ongoing cervical cancer elimination strategies in China can effectively prevent HPV-related cervical cancer among women and demonstrate good cost-utility (ICUR: 16,456.75 USD/QALY, 16,045.33-16,868.17). Increasing the intervention rates to meet the global goal by 2030 results in the prevention of more cases while maintaining cost-utility (22,532.04 USD/QALY, 21,968.74-23,095.34). Increasing HPV vaccinating rates cannot improve cost-utility under current efficacy and cost. 9vHPV vaccine yields the greatest increase in QALYs compared to the baseline, while 2v vaccine has relatively better cost-utility. Under the assumption of limited supply, implementing single-dose vaccination for girls under the age of 14 and reallocating excess doses to women under 25 shows higher health economic benefits than two- or three-dose scenarios. At a screening rate of 70%, the ICUR of the AI-TCT screening pathway among women aged 35–64 years is lower than both the ongoing and WHO recommended screening pathways. The optimal combination strategy exhibits extremely high cost-utility (1,374.53 USD/QALY, 1,340.17-1,408.89) among the intervention cohort. Under ongoing strategies, the predicted prevalences of hr-HPV among women exhibit a trend of bimodal distribution by age, which is consistent with the findings from other cross-sectional surveys 22 . The higher incidence of HPV infections in younger women may be attributed to higher levels of sexual activity and an immature immune system, while the hormonal changes and immune disorders among postmenopausal women can reactivate previously acquired HPV infections 23 . On the other hand, this study finds that the probability of developing cervical cancer is higher among women aged 45 and older compared to those under 45. However, at present, HPV vaccination in China primarily targets women aged 9–45 years, and cervical screening programs are aimed at women aged 35–64 years, leaving the elderly women largely unprotected. With the acceleration of population aging, it is necessary to expand the age limit for vaccination and screening. Simultaneously, in this study, the number of hr-HPV infections among rural women is expected to surpass the among urban women. Zhao et al. also found that the HPV incidence among rural women was higher than that in urban areas in a nationwide real-world study 24 . In urban areas, the availability of high-quality medical equipment for cervical pathology diagnosis and adequate HPV testing infrastructure results in significantly higher screening participation rates compared to rural areas. Local governments should increase financial investment in rural healthcare infrastructure. Besides, studies have shown that the primary risk factors associated with HPV incidence in rural areas include low education levels 25 . Attention should be paid on health education in these areas. We find that the ongoing HPV vaccination strategy reduces the proportion of genotype-specific infections protected by the vaccine, and contributes to herd immunity. However, the prevalences of non-vaccine-targeted hr-HPV genotypes increase over time, which is consistent with a study conducted in Guangzhou 26 . These results underscore the importance of monitoring non-protected HPV genotypes and the associated cancer risks following the large-scale promotion of HPV vaccines. Meanwhile, although the proportion of HPV-16 and 18 infections have decreased, these genotypes remain the primary causes of cervical cancer with a high potential for progression, indicating that the application of HPV-16 and 18 genotyping in cervical screening is still of great significance. In addition, among the vaccinated population in this study, HPV-52 is projected to replace HPV-16 as the dominant genotype within 10 years. A study conducted in southern China also identified HPV-52 (5.12%), 16 (2.96%) and 58 (2.51%) as the three most common hr-HPV genotypes among all identified types 27 . Accordingly, promoting 9v vaccines or developing vaccines that cover more genotypes is crucial for the prevention of HPV-related cancer at current. In this study, maintaining the screening strategy with primary HPV testing, HPV genotyping and TCT triage under current HPV vaccination rate can reduce the risk of cervical cancer, and demonstrates cost-utility. When the target intervention coverage is achieved, the health benefits of HPV vaccination exceed those of screening alone, while the health economics benefits of cervical screening alone are higher. Zhang et al. found that HPV vaccination at a high rate could prevent 60% more cervical cancer cases and deaths than screening alone 28 . However, a model study in urban areas of China showed that when the background HPV vaccination rate reached 90%, the implementation of primary HPV testing and TCT triage screening strategies did not yield health economic benefits unless the screening frequency was increased to once every 3 years and the screening age expanded to 25 years 29 . In fact, data from both developed and developing countries have indicated that neither traditional screening programs nor vaccination alone can achieve optimal effectiveness in preventing cervical cancer. For instance, a modelling study conducted in rural China showed that the combination of continuous vaccination and two rounds of screening could strike a balance between high health and health economics benefits, resulting in a 33% reduction in cervical cancer incidence by 2030 30 . The findings highlight the importance of synchronizing the promotion of HPV vaccination and screening in the context of accelerating cervical cancer elimination. The ICUR of intervention strategy is associated with multiple factors. Our analyses show that the cost and efficacy of HPV vaccines impact the cost-utility. However, the cost of vaccines in China remains prohibitively high, especially the 4v and 9v vaccines. Given the large population base, it is unrealistic for the government to provide large-scale financial subsidies for HPV vaccination. As a result, many of the direct costs associated with vaccination must be borne by individuals, which has led to limited willingness among women to pay for HPV vaccines. A survey in China revealed that over 60% of women stated that the acceptable price for 3 doses of HPV vaccines was less than 7 USD 31 , which was much lower than the current cost. Efforts should be made to accelerate the inclusion of domestic vaccines into the NIP, and healthcare sectors has the responsibility to negotiate more competitive prices with manufacturers. Determining the target age for routine HPV vaccination is another critical issue. Our study finds that the short-term effect of increasing vaccination rates in the ≤ 14 age group is limited, likely due to the low level of sexual activity among girls aged 9–14. According to the latest national sexual behavior survey in China, the cumulative probability of sexual activity among 15-year-old girls is less than 5% 32 . However, our study suggests that QALYs would be maximized when vaccinating girls before the age of 14, emphasizing the long-term benefits of early vaccination. The target age of cervical screening also affected the health economics outcomes. Evidence has suggested that expanding the starting age to under 30 years improved the cost-utility of screening programs 33 . Our study further shows that expanding the screening age to 65 years on the basis of 35–44 years yields higher benefits than expanding to 15 years, which may be due to the higher risk of cervical cancer among elderly women 26 . Besides, the cost and efficacy of treatment for advanced cancer significantly influence the ICUR, indicating the need to ensure the life quality for late-stage survivors. Promoting ongoing strategies to the target level faces many challenges, particularly in terms of insufficient supply, poor accessibility, and high costs of HPV vaccines 34 . In our study, under the assumption of limited supply and reduction in protective effect with fewer doses, we find that the health economics benefits of single dose vaccination for girls under 14 years followed by supplementary vaccination before 25 years are greater than those of similar two or three doses scenarios. This result complements a previous comparison between two doses and single dose catch-up vaccination strategies 35 , and provides a valuable reference for alleviating vaccine supply constraints, as well as supporting the adoption of single-dose vaccination programs in China. As regards cervical screening, the main challenges include optimizing personnel utilization and improve screening efficiency, which could be achieved through AI-assisted screening 36 . In this study, we find that among the ongoing and WHO-recommended screening pathways, HPV testing once every 5–10 years has the highest cost-utility, which is align with previous assessments conducted in developing countries 37 . On this basis, replacing the manual TCT method with AI-TCT would yield the highest cost-utility and simultaneously increase the QALYs, supporting the potential application of AI-TCT in China. However, this conclusion largely relies on the assumption that AI-TCT offers higher sensitivity and lower cost than manual TCT 20 . Quality control and high utilization of devices should be prioritized in AI-TCT promotion. This study clarified the intervention effect of ongoing cervical cancer elimination strategies in China, confirming that continued promotion of the strategies to achieve the 2030 goal yields health economic benefits. The model was calibrated using real-world screening records, incorporating segmented model assumptions referring to COVID-19 lockdown level, thereby enhancing the accuracy of modeling. This study thoroughly considered the potential development of HPV vaccination and cervical screening and evaluated the combined effects of interventions. However, there exists several limitations. First, this study only considered first-time HPV infection and ignored the co-infections involving different genotypes, which may have led to an underestimation of HPV prevalence. Second, since the ongoing strategies primarily target the women population, this study simplified the development status of HPV-related cancers among heterosexual men. Further studies focusing on men is necessary. Finally, the lack of multicenter real-world data for external validation may have introduced bias in parameter calibration. We assumed that regional discrepancies in parameters were solely attributable to differences in population structure and intervention participation rates, and parameters reflecting the actual situation at different regional levels were incorporated, ensuring a reasonable degree of consistency in the calibrated transmission parameters. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The real-world epidemiological data were gathered from Shenzhen Baoan Women's and Children's Hospital, which are not publicly available due patient privacy, but are available from the corresponding author on reasonable request. All model parameters that support the findings of this study are available from open accessed websites, according to the references in Table 1. Competing interests The authors declare that they have no competing interests. Funding This study was supported by Shenzhen Science and Technology Program (A2302001), Shenzhen Natural Science Foundation (JCYJ20240813141023031), Guangdong Science and Technology Program (2024A050505008), National Natural Science Foundation of China (82203291), Medical Scientific Research Foundation of Guangdong Province of China (A2025145). All funding parties did not have any role in the design of the study or in the explanation of the data. Authors' contributions Siyang Liu, Yuwei Li and Jianxin Zhen conceived the idea and protocol. Yuwei Li and Yi-Fan Lin built the model and interpreted the findings. Yuwei Li finalized the analysis and wrote the manuscript. Siyang Liu and Jianxin Zhen revised the manuscript. Jianxin Zhen and Fangfang Chen provided the data. Boyu Cai and Quanfu Zhang provided clinical guidance for the analysis. All authors read and approved the final manuscript. Acknowledgements We thank all members for carefully reading and commenting on the manuscript. 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Zhen","email":"","orcid":"","institution":"Shenzhen Baoan Women’s and Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jianxin","middleName":"","lastName":"Zhen","suffix":""}],"badges":[],"createdAt":"2025-10-14 07:08:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7855155/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7855155/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12916-026-04881-1","type":"published","date":"2026-04-22T15:58:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":96094869,"identity":"e8b18131-2498-40dc-88e1-09afb19f3aca","added_by":"auto","created_at":"2025-11-17 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14:16:03","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":191659,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7855155/v1/c3d96fbb5a685186d6da48cc.html"},{"id":96247934,"identity":"889c84cf-431e-42fa-9b44-29eee7e101f3","added_by":"auto","created_at":"2025-11-19 07:27:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":206257,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe study design of modelling the hr-HPV transmission dynamics and intervention evaluation. \u003c/strong\u003eThe flowchart in the middle illustrates the process of model development and simulation. Details of the following 4 steps are further displayed.\u003c/p\u003e\n\u003cp\u003e(1) Natural history construction: susceptible women are infected with hr-HPV thorough heterosexual partnership under genotype-specific rates. Infected individuals can naturally clear HPV infection or develop CIN and cervical cancer.\u003c/p\u003e\n\u003cp\u003e(2) Model assumption: susceptible women will be vaccinated at annual rates, and get lifelong immunity against targeted hr-HPV genotypes based on the vaccine efficacy. Cervical screening with primary HPV testing (PCR) and TCT triage is regularly implemented. Individuals with positive screening result are considered to be treated.\u003c/p\u003e\n\u003cp\u003e(3) Individual-based (MCMC): individuals are numbered with 1-3. Lines of different colors represent the disease development trajectories of individuals 1-3. Shield represents immune status. For each individual, conduct random sampling from uniform distribution of 0-1. Move on to the next state if it is less than the transition probability; otherwise maintain the original state.\u003c/p\u003e\n\u003cp\u003e(4) Scenario analysis:\u003c/p\u003e\n\u003cp\u003eHPV vaccination: allocate different vaccine types to age-stratified women, or primarily provide reduced doses vaccination to girls before 14 and provide catch-up vaccination to those before 24 with remained doses.\u003c/p\u003e\n\u003cp\u003eCervical screening: 7 types of WHO recommended pathways and AI-assisted TCT method. The blue circle represents different screening methods, and the arrow represents the order that the methods are conducted.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7855155/v1/3d8df02b2ec876ea6097e7a3.png"},{"id":96094861,"identity":"c3ef027f-e8eb-4285-8385-2e3ccd58d90f","added_by":"auto","created_at":"2025-11-17 14:16:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":518646,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe predicted 10-year trends of hr-HPV infections and related cervical cancers among women under ongoing strategies. \u003c/strong\u003eThe x-axis represents the year. The y-axis represents the prevalence of each model compartment. Cubic spline interpolation was used to smooth the curve. The height of the bar chart represents the increments.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7855155/v1/d287a6128daf48e5a8e89fa2.png"},{"id":96094866,"identity":"5ec65145-896f-462a-995a-c55c01a7f20f","added_by":"auto","created_at":"2025-11-17 14:16:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":935502,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe stratification characteristics of hr-HPV, CIN and cervical cancer epidemic trends. \u003c/strong\u003e(A) The age-stratified proportions in different status in 10 years. (B) The urban- and rural-stratified proportions in different status in 10 years. (C) The genotype distribution among unvaccinated, vaccinated and overall infected women in the initial year of model simulation. (D) The genotype distribution among unvaccinated, vaccinated and overall infected women in the 10th year.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7855155/v1/6e0ad07ffc8f04760d650ad1.png"},{"id":96248817,"identity":"45ce6196-f7e9-4974-afe9-d52dd2db0f52","added_by":"auto","created_at":"2025-11-19 07:29:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":551435,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe health and economics benefits of ongoing and target cervical cancer elimination strategies. \u003c/strong\u003e(A) The health and economics benefits of ongoing strategies. (B) The health and economics benefits of target strategies. (C) The annual trends of Cost per capita and overall QALYs under ongoing strategies. (D) The annual trends of Cost per capita and overall QALYs under target strategies. I-, CIN-, CC- and D- denotes the prevented cases in corresponding status. Cost+ and QALY+ denotes the incremental value of cost and QALYs compared with baseline.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7855155/v1/0e528e3b74823e0b0b79a39c.png"},{"id":96246883,"identity":"06971ac0-69cb-4189-b500-d30c0aae0b8a","added_by":"auto","created_at":"2025-11-19 07:26:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":765345,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe sensitivity analyses result of combined intervention acceptance rates. \u003c/strong\u003e(A)-(C) represents the per capita cost, increased QALYs and ICUR under the combinations of vaccinating rates with different vaccine types, respectively. (D)-(F) represents the per capita cost, increased QALYs and ICUR under the combinations of different vaccination, screening and treatment rates, respectively.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7855155/v1/f80f0561adfd17b6e3b2ec41.png"},{"id":107927880,"identity":"955d8996-19ec-42ee-a127-f9e196823ac8","added_by":"auto","created_at":"2026-04-27 16:05:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3453574,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7855155/v1/0ca3f127-dc14-483a-9b74-8cc45cc98d6e.pdf"},{"id":96248572,"identity":"967fbb39-8c3c-4dd1-820b-609bca21ca8d","added_by":"auto","created_at":"2025-11-19 07:28:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":3595011,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7855155/v1/4760db43fd88fa0fed6144bc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Modelling the epidemic dynamics of HPV among women in China and optimization of ongoing cervical cancer elimination strategies","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCervical cancer has remained to be a severe threat to women health. As of 2020, approximately 604,000 cumulative cervical cancer cases and 342,000 related deaths were reported worldwide\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. China bears the second largest burden of cervical cancer\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. According to statistics, an average of 100,000 new cases and 30,000 deaths are reported in China annually, with the incidence and mortality rates increasing by 8.5% and 5.4% respectively\u003csup\u003e2\u003c/sup\u003e. The persistent infection of high-risk human papillomavirus (hr-HPV) is the primary cause of cervical cancer. Research has indicated that HPV can be detected from over 99% of cervical cancer patients, and the detection rate increases with the severity of cervical lesions\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Among more than 100 HPV genotypes, HPV-16 and 18 are responsible for approximately 75% of global cervical cancer cases\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. In China, HPV-52 and 58 are gradually recognized as the major contributors besides HPV-16 due to their continuously rising infection rates\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFortunately, cervical cancer can be effectively prevented through Grade I-III interventions. HPV vaccination can protect individuals from the most common carcinogenic HPV genotypes, and is considered as the primary preventive measure against cervical cancer. There are three categories of HPV vaccines approved at present, including bivalent (2v), quadrivalent (4v) and nonavalent (9v) vaccines. The 2v and 4v vaccines cover HPV-16 and 18, preventing approximately 70% of cervical cancers; the 9v vaccine additionally covers HPV-31, 33, 45, 52 and 58, providing protection against roughly 90% of cervical cancers\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Several randomized controlled trials (RCTs) have demonstrated that full HPV vaccination with multiple doses is safe and elicits strong immunogenic responses\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In April 2022, researchers confirmed that single dose of HPV vaccination can provide similar protection with multiple doses in preventing persistent HPV infections\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, highlighting the importance of vaccination efficiency in situations of limited supply. In China, a clinical trial for single-dose 9vHPV vaccine was launched in March 2024\u003csup\u003e9\u003c/sup\u003e, supporting the potential future expansion of reduced-dose vaccination.\u003c/p\u003e\u003cp\u003eThe early detection and diagnosis through cervical screening are also crucial. According to a study conducted in Australia, over 70% of cervical cancer occurred in women who were either insufficiently screened or had never participated in screening\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The widely used cervical screening methods at current include visual inspection with acetic acid (VIA), HPV nucleic acid (DNA) testing, thin layer liquid-based cytology test (TCT) and colposcopy examination. Among these, HPV DNA testing has garnered particular attention due to its high sensitivity and non-invasive characteristic, and has become the primary screening method recommended by WHO\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In addition to manual methods, artificial intelligence (AI)-assisted TCT is emerging as a promising tool. Studies have shown that AI-TCT achieves comparable sensitivity (odds ratio [OR]: 1.01, 95% confidence interval [CI]: 0.97\u0026ndash;1.05) and higher specificity (1.26, 1.20\u0026ndash;1.32) compared to skilled cytology experts\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In China, the national AI cervical screening project has been carried out since 2017, during which 5.86% positive cases out of 10.08\u0026nbsp;million screenings were detected\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn 2020, WHO released the Global Strategy for Accelerating Cervical Cancer Elimination, which set the 2030 targets of vaccinating 90% of girls, screening 70% of women, and providing treatment to 90% of diagnosed patients\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In response, China is actively promoting HPV vaccination along with the screening pathway of primary HPV testing followed by cytology triage. However, there is a lack of health economic evidence supporting the scaling-up of interventions to meet the 2030 targets. Moreover, studies have shown that between 2018 and 2020, the full-course HPV vaccination rate among women aged 9\u0026ndash;45 in China was only 2.24%\u003csup\u003e15\u003c/sup\u003e. and the cervical screening rate among women aged 35\u0026ndash;64 as of 2023 was only 36.8%\u003csup\u003e16\u003c/sup\u003e, falling significantly short of the 2030 goals. The supply restrictions and high costs have continued to hinder the widespread implementation of vaccination. TCT-based screening remains prevalent, despite a growing mismatch between the demand for screening and the availability of trained cytologists. Therefore, this study aims to predict the epidemic trends of hr-HPV under ongoing strategies among women in China, evaluate the health economics effects, and assess the potential benefits of alternative intervention scenarios including dose-reduction regimens and AI-TCT adoption for strategy optimization.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study design and data sources\u003c/h2\u003e\u003cp\u003eIn this study, a population-based dynamic model was established to predict HPV epidemics under ongoing cervical cancer elimination strategies among women in China. Sensitivity analyses were conducted based on this model to provide suggestions for strategy optimization. An individual-based stochastic model was thereafter established to observe the long-term effects of alternative intervention scenarios among susceptible young women. The optimal strategy was determined by comparing the health economics benefits between scenarios. The population-based model was simulated among all women at current health state distribution in China. All-cause mortality rates and a background birth rate were considered. Ordinary differential equations (ODEs) were constructed to realize model formulation. The parameters required in the equations were calibrated using real-world epidemiological data. The individual-based model was simulated among a 75-year intervention cohort of 100,000 women, who were assumed to be initially susceptible and follow a uniform distribution within 14 years old. Markov Chain Monte Carlo (MCMC) algorithm was applied to achieve the formulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All parameters in this study were collected from public database and published literatures (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Details are shown in Supplementary Materials.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe summary of main parameters used in the model.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSymbol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImplication\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eTransition parameters\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eα\u003csub\u003ef\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe rate of waning innate immunity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.015\u0026ndash;0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e38\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eγ\u003csub\u003ecin1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe backward transition rate from CIN1 to I\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.5044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4732\u0026ndash;0.5561\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eγ\u003csub\u003ecin2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe backward transition rate from CIN2 to CIN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2494\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1994\u0026ndash;0.2992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eγ\u003csub\u003ecin3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe backward transition rate from CIN3 to CIN2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0101\u0026ndash;0.0169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e40,41\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ\u003csub\u003eif\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe forward transition rate from I to CIN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0450\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0279\u0026ndash;0.0661\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ\u003csub\u003ecin1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe forward transition rate from CIN1 to CIN2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1608\u0026ndash;0.2972\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e40,41\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ\u003csub\u003ecin2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe forward transition rate from CIN2 to CIN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.2623\u0026ndash;0.4372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e40,41\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ\u003csub\u003ecin3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe forward transition rate from CIN3 to ACC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0764\u0026ndash;0.1274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e40,41\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ\u003csub\u003eacc1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe forward transition rate from ACC1 to ACC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.4377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.3283\u0026ndash;0.5471\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21,42\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ\u003csub\u003eacc2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe forward transition rate from ACC2 to ACC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.5358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4019\u0026ndash;0.6698\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21,42\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ\u003csub\u003eacc3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe forward transition rate from ACC3 to ACC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.6838\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5129\u0026ndash;0.8548\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21,42\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003es\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esymptom development rate from ACC1 to CC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.11\u0026ndash;0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003es\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esymptom development rate from ACC2 to CC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.17\u0026ndash;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003es\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esymptom development rate from ACC3 to CC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.45\u0026ndash;0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003es\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esymptom development rate from ACC4 to CC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.68-1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eωd\u003csub\u003eacc1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe death rate of ACC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.012\u0026ndash;0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eωd\u003csub\u003eacc2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe death rate of ACC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.024\u0026ndash;0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eωd\u003csub\u003eacc3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe death rate of ACC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.064\u0026ndash;0.191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eωd\u003csub\u003eacc4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe death rate of ACC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.191\u0026ndash;0.450\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eωs\u003csub\u003eacc1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe 5-year survival rate of ACC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82\u0026ndash;0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43,44\u003c/sup\u003e; calculated\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eωs\u003csub\u003eacc2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe 5-year survival rate of ACC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.68\u0026ndash;0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43,44\u003c/sup\u003e; calculated\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eωs\u003csub\u003eacc3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe 5-year survival rate of ACC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.05\u0026ndash;0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43,44\u003c/sup\u003e; calculated\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eωs\u003csub\u003eacc4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe 5-year survival rate of ACC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.00-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43,44\u003c/sup\u003e; calculated\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIntervention parameters\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVE\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe efficacy of bivalent vaccine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80.00\u0026ndash;99.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVE\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe efficacy of quadrivalent vaccine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65.20\u0026ndash;99.90%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e45,46\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVE\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe efficacy of ninvalent vaccine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96.70%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80.90\u0026ndash;99.80%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e47\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eκ\u003csub\u003eVIA\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe sensitivity of VIA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.45\u0026ndash;0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eκ\u003csub\u003e1hc2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe sensitivity of HPV testing (HC2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.79-1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e48\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eκ\u003csub\u003e1pcr\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe sensitivity of HPV testing (PCR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.93-1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e49\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eκ\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe sensitivity of LBC to detect LSIL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.53\u0026ndash;0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eκ\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe sensitivity of LBC to detect HSIL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.78\u0026ndash;0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eκ\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe sensitivity of LBC to detect cell carcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.90\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUtility parameters (QALYs)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecin1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in CIN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.730-1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e51\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecin23\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in CIN2/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.900\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.873\u0026ndash;0.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecint\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in treated CIN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.960\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.945\u0026ndash;0.976\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecc1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in CC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.830\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.788\u0026ndash;0.873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecc2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in CC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.773\u0026ndash;0.907\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecc3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in CC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.650\u0026ndash;0.780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecc4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in CC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.430\u0026ndash;0.770\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecc1t\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in treated CC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.490\u0026ndash;0.810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecc2t\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in treated CC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.605\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.420\u0026ndash;0.670\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecc3t\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in treated CC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.560\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.420\u0026ndash;0.700\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003ecc4t\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in treated CC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.360\u0026ndash;0.600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eq\u003csub\u003eccs\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ethe life quality of individual in CCs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.930\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.700\u0026ndash;0.990\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003csup\u003e41,43\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNOTE\u003c/b\u003e: I, infectious; CIN, cervical intraepithelial neoplasia; ACC, asymptomatic cervical cancer (undiagnosed); CC, cervical cancer (diagnosed).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Model overview\u003c/h2\u003e\u003cp\u003eThe model was stratified and compartmental, consisting of a dynamic pattern to simulate hr-HPV transmission, and a natural history pattern to predict cervical carcinogenesis trends. Susceptible-infectious-recovered-susceptible (SIRS) structure was applied to illustrate the HPV transmission pattern. We assumed that susceptible women (S) would be infected with hr-HPV (I) through heterosexual partnership at age- and region-stratified force of infection (FOI). Infected individuals could get rid of HPV infection and remain naturally immune (Im) until antibodies waned. The FOI was determined by HPV prevalence among opposite sex counterpart, sexual mixing matrices and the transmission probability. The natural history pattern was divided into cervical intraepithelial neoplasia (CIN, grade 1\u0026ndash;3) and cervical cancer (CC, stage I-IV). The staging of cervical carcinogenesis was according to the International Federation of Gynecology and Obstetrics (FIGO). Patients with cervical cancer were assumed to be initially asymptomatic (ACC, stage I-IV), who would enter the advanced asymptomatic state or display detectable symptoms at independent probabilities. Individuals in precancerous stage could clear their infection, while those progressing to cancer would never naturally recover. Early, advanced and terminal cancer were subjected to different death rates (Rd). Cancer patients who remained alive for no less than 5 years (Rs) were break from subsequent simulation (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). A total of 18 hr-HPV genotypes were considered. The natural history among men and the sexual mixing pattern are shown in Figure S2-S3.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Interventions\u003c/h2\u003e\u003cp\u003eThe primary interventions in the model included HPV vaccination and cervical screening. Condom use and post-exposure treatment were also considered as background interventions. The ongoing strategies for cervical cancer elimination in China were assumed as follows: 1) Prophylactic HPV vaccination: providing 2v (domestic Cocolin), 4v (imported Gardasil), or 9v (imported Gardasil) HPV vaccines to women aged 9\u0026ndash;45, with a basic coverage in the initial state and a timely vaccinating rate referring to the National Immunization Program Information Monitoring System \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. 2) Cervical screening: providing women aged 35\u0026ndash;64 years old with primary HPV DNA testing and TCT triage method\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, with stratified participation rates estimated from real-world data, and a time interval assumed as 3\u0026ndash;10 years according to WHO recommendations. 3) Condom use: with a coverage ranging from 0.74 to 1\u003csup\u003e18\u003c/sup\u003e. 4) CIN and CC treatment: including cryotherapy, thermal ablation (TA), cold knife conization (CKC) and loop electrosurgical excision procedure (LEEP) for early-stage patients, and hysterectomy, long-term radiation therapy and chemotherapy for terminal-stage patients. Patients eligible for treatment choose specific methods based on their eligibility rate (Figure S5).\u003c/p\u003e\u003cp\u003eThe intervention scenarios in this study included: 1) Target strategy: based on ongoing strategies and the coverage levels, calculating the annual HPV vaccinating and cervical screening participation rate required to achieve the goal of accelerating cervical cancer elimination in 2030 as the target strategy. After calculation, the overall annual vaccinating rate was 23.25%, the screening rate was 1.22 times higher than before, and the treatment rates were set at 90%. 2) Full vaccination: allocating 3 doses of 2v, 4v or 9vHPV vaccine to different age groups among women aged 9\u0026ndash;45 years. 3) Reducing doses vaccination: primarily vaccinating the girls aged\u0026thinsp;\u0026le;\u0026thinsp;14 years at a rate of 90%, providing 1 or 2 doses and reallocating the saved vaccines before 25 years old. 4) Different screening pathways: conducting ongoing screening pathway and the 7 WHO-recommended pathways at 70% participation rate. 5) AI-TCT screening: conducting AI-TCT screening with HPV DNA testing and colposcopy triage every 3 years at 70% participation rate. We assumed that, the efficacy of 2 dose and 1 dose vaccination is 0.8837 and 0.8372 times that of 3 doses\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, respectively, and the sensitivity of AI-TCT is 1.06 times that of manual TCT\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. (Figure S9-S10)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Calibration\u003c/h2\u003e\u003cp\u003eModel calibration in this study was realized using the population-based model. The fitting values of overall, age-stratified and genotype-specific hr-HPV prevalences were calculated in comparison with the real-world counterparts. The real-world epidemiological data were estimated from 132,282 cervical screening records in Shenzhen Baoan Women\u0026rsquo;s and Children\u0026rsquo;s Hospital, a Class 3A Hospital targeted at the prevention of maternal and fetal diseases of over 5.1\u0026nbsp;million residents. The period for model calibration was selected as July 2020 to December 2023 with complete records. All records were divided into quarterly subsets, and randomly sampled into the training and the testing set (6:4) based on the same age distribution for internal validation.\u003c/p\u003e\u003cp\u003eDuring calibration, Latin hypercube sampling was performed to generate 10,000 parameter combinations. The overall and stratified epidemic trends of hr-HPV infection were simulated under each combination. The mean square error (MSE) weighted by inverse variance was calculated to obtain the top 1% optimal parameter combinations and the merged calibrated ranges. The overall determination coefficient (R\u003csup\u003e2\u003c/sup\u003e) was calculated to evaluate the calibration effect. Bootstrap sampling was performed on the optimal combinations for validation. Since the time of collected data covers COVID-19 epidemic period, during which low HPV prevalence and screening participation were observed as a result of non-pharmaceutical interventions (NPIs) (Figure S6), we constructed a segmented model consisting of the lockdown and the opening period of COVID-19 taking the fourth quarter of 2022 as the breakpoint (Figure S7). Parameters cd and sd were added to simulate the reduction of sexual exposure and screening participation caused by NPIs respectively. The calibration results are shown in Figure S8.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Simulation\u003c/h2\u003e\u003cp\u003eWe conducted 10-year trend prediction and effect evaluation based on the calibrated parameters. The baseline scenario was assumed to be no vaccination or cervical screening. As it has been observed that benefits of strategies may not appear in a short term\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, the duration of effect evaluation was set to be 20 years. The primary outcomes of trend prediction included the number of current cases in all model compartments. The outcomes of health economics benefit evaluation were the prevented cases, increased costs, quality-adjusted life years (QALYs), and incremental cost-utility ratio (ICUR) compared to baseline. The cost included the prices of HPV vaccine, cervical screening and cancer treatment, as well as all indirect costs incurred. All prices were conversed to the 2023 international US dollar (USD) currency with an annual discount rate. QALY was calculated as the total multiplier of life quality among women at different health states. The criteria for cost-utility analysis referred to that proposed by WHO. When ICUR is less than China's per capita gross domestic product (pcGDP, 13,013.18 USD in 2023), strategy is considered to be with high cost-utility; when ICUR is 1\u0026ndash;3 times the pcGDP, strategy is considered to be with cost-utility; else the strategy is with no cost-utility. The point estimates and 95% CIs were generated using Monte Carlo method. All computations were based on R 4.4.1.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Epidemic trends under ongoing strategies\u003c/h2\u003e\u003cp\u003eThe model shows that in 10 years from 2023, under ongoing cervical cancer elimination strategies, the prevalence of hr-HPV among women in China will decrease from 0.1930 (95% CI, 0.1882\u0026ndash;0.1978) to 0.0125 (0.0122\u0026ndash;0.0128), peak at 0.1973 (0.1924\u0026ndash;0.2022) in 2024, and tend to be stable after 2030. The proportion of women who are naturally immune will decline from the sixth year, while increase from 0.4076 (0.3974\u0026ndash;0.4178) to 0.6309 (0.6151\u0026ndash;0.6467) by 2033 in overall. The total prevalence of CIN will decrease from 1.5924% (1.5526\u0026ndash;1.6322%) to 0.3532% (0.344\u0026ndash;0.3620%). The prevalence of cervical cancer also shows an overall downward trend, decreases from 1.8417\u0026permil; (1.7957\u0026ndash;1.8877\u0026permil;) to 1.0778\u0026permil; (1.0509\u0026ndash;1.1047\u0026permil;) except for a slight increase in 2017. The increase rate of the cumulative proportion of deaths and five-year survivals due to cervical cancer will steadily decline. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Characteristics of stratified infections\u003c/h2\u003e\u003cp\u003eAs hr-HPV infection deepens and the degree of cancer worsens, the proportion of women aged\u0026thinsp;\u0026ge;\u0026thinsp;45 years and in urban areas will gradually increase. In 10 years, the proportion of infected women aged 25\u0026ndash;34 and 65\u0026ndash;74 years will increase among all infected women, while the proportion of those aged 35\u0026ndash;64 years will decrease, demonstrating a trend of bimodal distribution. Among CC patients, a significant increase was observed in the proportion of women aged 55 years and above (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (A)). The proportion of urban women who are infected with hr-HPV, CIN and CC among all correspondingly infected women will consistently decline (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (B)). The number of rural patients will gradually surpass that in urban (Figure S11).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the 10th year, among the unvaccinated group, the top five 9v genotypes with the highest proportion are HPV-52 (14.88%, 14.51\u0026ndash;15.25%), HPV-16 (11.84%, 11.54\u0026ndash;12.14%), HPV-58 (11.41%, 11.12\u0026ndash;11.70%), HPV-18 (5.54%, 5.40\u0026ndash;5.68%), and HPV-31 (4.75%, 4.63\u0026ndash;4.87%). The top five 9v genotypes in the vaccinated group with the highest proportion are HPV-52 (12.92%, 12.60-13.24%), HPV-58 (9.98%, 9.73\u0026ndash;10.23%), HPV-16 (4.28%, 4.17\u0026ndash;4.38%), HPV-31 (4.23%, 4.12\u0026ndash;4.34%), and HPV-33 (3.90%, 3.80\u0026ndash;3.99%). The proportion of 9vHPV in the vaccinated group is 16.17% (15.77\u0026ndash;16.57%) less than that in the unvaccinated group in overall. Compared with the initial-stage distribution, it is observed that HPV vaccination has significantly reduced the proportion of 9vHPV genotype in the vaccinated group and have a herd immunity effect on the unvaccinated group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (C)). The number of HPV-52 infections will exceed that of HPV-16 infections since 2025 in the vaccinated group (Figure S12).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Health and economic benefits of ongoing and target strategies\u003c/h2\u003e\u003cp\u003eThe model shows that, in 20 years under ongoing cervical cancer elimination strategies, compared to baseline, 28,575.91 (27,861.51-29,290.31) thousands of cumulative hr-HPV infections and 2,150.51 (2,096.75-2,204.27) thousands of CC patients will be prevented. The total QALYs increased is 14,811.06 (14,440.78-15,181.34) thousands and the ICUR value is 16,456.75 (16,045.33-16,868.17) USD/QALY. Without screening, the ICUR will increase to 69,459.83 (67,723.33-71,196.33) USD/QALY. In 20 years under the target strategies, compared to baseline, 166,237.74 (162,081.80\u0026ndash;170,393.70) thousands of cumulative hr-HPV infections and 4,489.38 (4,377.15-4,601.61) thousands of CC patients will be prevented. The total QALYs increased is 42,020.46 (40,969.95-43,070.97) thousands, and the ICUR value is 22,532.04 (21,968.74-23,095.34) USD/QALY. Under the target HPV vaccination only, the QALYs increased is 32,281.72 (31,474.68-33,080.76) thousands, and the ICUR is 29,913.68 (29,165.84-30,661.52) USD/QALY. Under the target cervical screening only, the QALYs increased is 16,970.99 (16,546.72-17,395.26) thousands, and the ICUR is 14,869.12 (14,497.39-15,240.85) USD/QALY (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (B)). The trend of cost and QALYs changes over decades are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (C) and (D).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Sensitivity analyses\u003c/h2\u003e\u003cp\u003eThe model shows that improving the vaccinating rate among different age groups of women in China can prevent more hr-HPV infections and cervical cancers, but will lead to higher ICUR. When the vaccinating rates increase at the same degree among a separate age group, the CIN, CC and related deaths among the 25\u0026ndash;34 age group enjoy the highest reduction, with the highest increase in QALYs; the HPV infections among the 15\u0026ndash;24 age group enjoy the highest decease, with the lowest ICUR (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). When the vaccinating rate of 9v vaccine is 5% and that of 2v and 4v vaccines is 0%, the QALYs compared to the baseline is 21,536.72 (20,998.30\u0026ndash;22,075.14) thousands in 20 years, and the ICUR value is 28,510.24 (27,797.48-29,223.00) USD/QALY. When the vaccinating rate of 2v vaccine is 5% and that of 4v and 9v vaccines is 0%, the QALYs compared to the baseline is 16,203.90 (15,798.80\u0026ndash;16,609.00) thousands in 20 years, and the ICUR value is 12,101.04 (11,798.51-12,403.57) USD/QALY (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e (A)-(C)). Meanwhile, higher screening frequency and participation rate can contribute to more cervical cancer cases prevented and lower ICUR (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Expanding the target screening age from 35\u0026ndash;44 years old to 64 years old presents greater health and health economics benefits than to 15 years old (Figure S13). In 20 years, when the vaccinating rate separately increases by 50%, the QALYs rises to 16,167.45 (15,763.26-16,571.64) thousands, while the ICUR value is 20,298.32 (19,790.86-20,805.78) USD/QALY. When the screening rate separately increases by 50%, the ICUR value decreases to 13,548.05 (13,209.35-13,886.75) USD/QALY. When all interventions consistently increase by 50%, the QALYs is 26,355.63 (25,696.74-27,014.52) thousands, and the ICUR value is 12,687.47 (12,370.28-13,004.66) USD/QALY (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e (D)-(F)). Besides, improving the efficacy of treatment, reducing the cost and increasing the discount rate significantly reduce the ICUR. (Figure S14-S15)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe prevented infections and cervical cancer, increased per capita cost, increased QALYs and ICUR after parameter adjustment based on ongoing strategies in sensitivity analyses, compared with baseline.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e\u003cp\u003eIndex\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrevented infections (\u0026times;10\u003csup\u003e4\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrevented cervical cancers (\u0026times;10\u003csup\u003e4\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIncreased cost\u003c/p\u003e\u003cp\u003e(per capita)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eIncreased QALYs\u003c/p\u003e\u003cp\u003e(\u0026times;10\u003csup\u003e4\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eICUR\u003c/p\u003e\u003cp\u003e(\u0026times;10\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eHPV vaccinating rate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge-stratified\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e14- \u003cb\u003eyears old\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e293.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e148.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e168.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e277.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e147.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e160.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e15\u0026ndash;24 years old\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e299.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e149.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e165.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e271.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e146.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e163.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e25\u0026ndash;34 years old\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e299.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e149.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e167.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e271.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e146.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e161.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e35\u0026ndash;44 years old\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e295.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e149.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e167.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e276.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e146.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e161.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVaccine type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2v\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e372.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e162.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e121.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e647.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e197.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e146.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4v\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e374.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e162.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e246.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e651.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e197.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e308.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9v\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e978.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e89.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e215.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e285.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,643.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e136.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e290.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e324.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCervical screening\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eParticipation rate (35\u0026ndash;44 years old)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e285.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e154.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e159.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e286.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e140.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e171.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTime interval\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e286.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e127.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e185.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e284.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e179.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e142.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTargeted age (70% coverage)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e285.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e154.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e158.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;25\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e283.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e165.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e150.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;15\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e283.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e199.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e136.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;45\u0026ndash;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e283.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e179.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e139.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;45\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e283.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e215.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e126.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNOTE\u003c/b\u003e: The values in the table are the average of 1000 simulations.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Scenario analyses\u003c/h2\u003e\u003cp\u003eThe individual-based model shows that in the absence of vaccination and screening, the 75-year simulation yields 150,840.14 (147,069.10\u0026ndash;154,611.10) cumulative hr-HPV infections, 9,358.54 (9,124.58-9,592.50) CINs, 545.89 (532.24-559.54) CCs and 170.64 (166.37-174.91) related deaths among the susceptible cohort, respectively. Under ongoing strategies, the peak of hr-HPV infections, CINs and CCs will be reduced, the prevented number of cumulative hr-HPV infections among the 75-year cohort decreases to 9,125.25 (8,897.12-9,353.38), that of cumulative CIN cases is 792.67 (772.85-812.49), and that of CC and related deaths are 100.18 (97.68-102.68) and 41.00 (39.98\u0026ndash;42.03), respectively. The increment in QALYs is 2,540.96 (2,477.44-2,604.48) and the ICUR value is 4,152.50 (4,048.69-4,256.31) USD/QALY. (Figure S16-S17)\u003c/p\u003e\u003cp\u003eIn 75 years among the cohort, when vaccinating those before the age of 14 with 3 doses and an annual rate of 90%, 9vHPV vaccines will lead to the most prevented hr-HPV infections and related cervical cancers, while the cost-utility of 2vHPV vaccines (ICUR: 4,069.08 USD/QALY, 3,967.35-4,170.81) is significantly higher than that of 4v and 9vHPV vaccines. When vaccinating with 2vHPV vaccines, postponing the vaccination age to 15\u0026ndash;24 years old will result in a decrease in ICUR, but a reduction in the number of prevented cases. Assuming that the priority is given to girls under the age of 14 and 2vHPV vaccine is provided, reducing 3 doses vaccination to 2 doses and reallocating the excess vaccines to women before 25 will increase the QALYs to 5,643.08 (5,502.00\u0026ndash;5,784.16), and decrease the ICUR to 2,678.82 (2,611.85-2,745.79) USD/QALY. Providing single dose and reallocating the excess vaccines to women before 25 will increase the QALYs to 5,716.37 (5,573.46-5,859.28), and decrease the ICUR to 1,378.06 (1,343.61-1,412.51) USD/QALY.\u003c/p\u003e\u003cp\u003eIn 75 years among the cohort, with 70% participation rate, ongoing cervical screening pathway results in an ICUR value of 2,829.66 (2,758.92-2,900.40) USD/QALY. Among the screening-and-treatment pathways recommended by WHO, HPV DNA testing once every 5\u0026ndash;10 years loses QALYs compared to VIA once every 3 years but shows higher cost-utility (ICUR: 1,922.56 USD/QALY, 1,874.50-1,970.62). Among the screening-triage-and-treatment pathways recommended by WHO, the ICUR reaches the lowest when implementing HPV genotyping\u0026thinsp;+\u0026thinsp;colposcopy once every 3\u0026ndash;10 years, and the ICUR reaches the highest when implementing HPV genotyping\u0026thinsp;+\u0026thinsp;VIA once every 3\u0026ndash;10 years, compared to baseline. On the basis of a 3-year TCT\u0026thinsp;+\u0026thinsp;HPV DNA testing\u0026thinsp;+\u0026thinsp;colposcopy pathway, replacing manual TCT with AI-TCT will result in an increase in the QALYs (to 295.10, 287.72-302.48) and a decrease in the ICUR (to 1,343.83, 1,310.23-1,377.43 USD/QALY), indicating the best health and economics effect among all pathways. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe health and health economics results of alternative strategies.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScenario\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI-\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCIN-\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCC-\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eD-\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCOSTpc+\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eQALY+\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eICUR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eHPV vaccination\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3 doses\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2v to 14-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22,254.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,494.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e218.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5,361.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4,069.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4v to 14-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22,368.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,502.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e500.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5,391.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e9,275.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9v to 14-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33,660.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2,979.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e123.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e786.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8,702.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e9,035.52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2v to 15\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19,517.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,310.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e86.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4,712.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,836.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2 doses\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2v to 14- +\u003c/p\u003e\u003cp\u003ecatch-up to 15\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23,335.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,568.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e151.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5,643.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,678.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e1 doses\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2v to 14- +\u003c/p\u003e\u003cp\u003ecatch-up to 15\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23,613.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,587.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e78.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5,716.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,378.06*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCervical screening pathway\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOngoing\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-54.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e198.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,829.66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eScreening-treatment\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIA /3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-42.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e215.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,575.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV DNA /5\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-27.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e150.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,922.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eScreening-triage-treatment\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTCT\u0026thinsp;+\u0026thinsp;HPV DNA\u003c/p\u003e\u003cp\u003e+colposcope /3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-30.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e284.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,519.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV DNA\u0026thinsp;+\u0026thinsp;VIA /3\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-44.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e103.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,753.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV geno\u0026thinsp;+\u0026thinsp;VIA /3\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-46.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e108.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,866.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV geno\u003c/p\u003e\u003cp\u003e+colposcope /3\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-32.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e176.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,132.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV DNA\u0026thinsp;+\u0026thinsp;TCT\u003c/p\u003e\u003cp\u003e+colposcope /3\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-36.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e143.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,303.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAI-TCT\u0026thinsp;+\u0026thinsp;HPV DNA\u003c/p\u003e\u003cp\u003e+colposcope /3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-32.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e295.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,343.83*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNOTE\u003c/b\u003e: * denotes the strategies with the highest cost-utility.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eUnder the optimal combined strategy, the peak values of hr-HPV infections, CINs and CCs are lower than that under ongoing strategies, and the time when reaching the peak is earlier (Figure S18). 23,586.15 (22,996.5\u0026ndash;24,175.8) hr-HPV infections and 93.20 (90.87\u0026ndash;95.53) CC would be prevented compared with baseline, and the ICUR value is 1,374.53 (1,340.17-1,408.89) USD/QALY.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe ongoing cervical cancer elimination strategies in China can effectively prevent HPV-related cervical cancer among women and demonstrate good cost-utility (ICUR: 16,456.75 USD/QALY, 16,045.33-16,868.17). Increasing the intervention rates to meet the global goal by 2030 results in the prevention of more cases while maintaining cost-utility (22,532.04 USD/QALY, 21,968.74-23,095.34). Increasing HPV vaccinating rates cannot improve cost-utility under current efficacy and cost. 9vHPV vaccine yields the greatest increase in QALYs compared to the baseline, while 2v vaccine has relatively better cost-utility. Under the assumption of limited supply, implementing single-dose vaccination for girls under the age of 14 and reallocating excess doses to women under 25 shows higher health economic benefits than two- or three-dose scenarios. At a screening rate of 70%, the ICUR of the AI-TCT screening pathway among women aged 35\u0026ndash;64 years is lower than both the ongoing and WHO recommended screening pathways. The optimal combination strategy exhibits extremely high cost-utility (1,374.53 USD/QALY, 1,340.17-1,408.89) among the intervention cohort.\u003c/p\u003e\u003cp\u003eUnder ongoing strategies, the predicted prevalences of hr-HPV among women exhibit a trend of bimodal distribution by age, which is consistent with the findings from other cross-sectional surveys\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The higher incidence of HPV infections in younger women may be attributed to higher levels of sexual activity and an immature immune system, while the hormonal changes and immune disorders among postmenopausal women can reactivate previously acquired HPV infections\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. On the other hand, this study finds that the probability of developing cervical cancer is higher among women aged 45 and older compared to those under 45. However, at present, HPV vaccination in China primarily targets women aged 9\u0026ndash;45 years, and cervical screening programs are aimed at women aged 35\u0026ndash;64 years, leaving the elderly women largely unprotected. With the acceleration of population aging, it is necessary to expand the age limit for vaccination and screening. Simultaneously, in this study, the number of hr-HPV infections among rural women is expected to surpass the among urban women. Zhao et al. also found that the HPV incidence among rural women was higher than that in urban areas in a nationwide real-world study\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In urban areas, the availability of high-quality medical equipment for cervical pathology diagnosis and adequate HPV testing infrastructure results in significantly higher screening participation rates compared to rural areas. Local governments should increase financial investment in rural healthcare infrastructure. Besides, studies have shown that the primary risk factors associated with HPV incidence in rural areas include low education levels\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Attention should be paid on health education in these areas.\u003c/p\u003e\u003cp\u003eWe find that the ongoing HPV vaccination strategy reduces the proportion of genotype-specific infections protected by the vaccine, and contributes to herd immunity. However, the prevalences of non-vaccine-targeted hr-HPV genotypes increase over time, which is consistent with a study conducted in Guangzhou\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. These results underscore the importance of monitoring non-protected HPV genotypes and the associated cancer risks following the large-scale promotion of HPV vaccines. Meanwhile, although the proportion of HPV-16 and 18 infections have decreased, these genotypes remain the primary causes of cervical cancer with a high potential for progression, indicating that the application of HPV-16 and 18 genotyping in cervical screening is still of great significance. In addition, among the vaccinated population in this study, HPV-52 is projected to replace HPV-16 as the dominant genotype within 10 years. A study conducted in southern China also identified HPV-52 (5.12%), 16 (2.96%) and 58 (2.51%) as the three most common hr-HPV genotypes among all identified types\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Accordingly, promoting 9v vaccines or developing vaccines that cover more genotypes is crucial for the prevention of HPV-related cancer at current.\u003c/p\u003e\u003cp\u003eIn this study, maintaining the screening strategy with primary HPV testing, HPV genotyping and TCT triage under current HPV vaccination rate can reduce the risk of cervical cancer, and demonstrates cost-utility. When the target intervention coverage is achieved, the health benefits of HPV vaccination exceed those of screening alone, while the health economics benefits of cervical screening alone are higher. Zhang et al. found that HPV vaccination at a high rate could prevent 60% more cervical cancer cases and deaths than screening alone\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. However, a model study in urban areas of China showed that when the background HPV vaccination rate reached 90%, the implementation of primary HPV testing and TCT triage screening strategies did not yield health economic benefits unless the screening frequency was increased to once every 3 years and the screening age expanded to 25 years\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. In fact, data from both developed and developing countries have indicated that neither traditional screening programs nor vaccination alone can achieve optimal effectiveness in preventing cervical cancer. For instance, a modelling study conducted in rural China showed that the combination of continuous vaccination and two rounds of screening could strike a balance between high health and health economics benefits, resulting in a 33% reduction in cervical cancer incidence by 2030\u003csup\u003e30\u003c/sup\u003e. The findings highlight the importance of synchronizing the promotion of HPV vaccination and screening in the context of accelerating cervical cancer elimination.\u003c/p\u003e\u003cp\u003eThe ICUR of intervention strategy is associated with multiple factors. Our analyses show that the cost and efficacy of HPV vaccines impact the cost-utility. However, the cost of vaccines in China remains prohibitively high, especially the 4v and 9v vaccines. Given the large population base, it is unrealistic for the government to provide large-scale financial subsidies for HPV vaccination. As a result, many of the direct costs associated with vaccination must be borne by individuals, which has led to limited willingness among women to pay for HPV vaccines. A survey in China revealed that over 60% of women stated that the acceptable price for 3 doses of HPV vaccines was less than 7 USD\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, which was much lower than the current cost. Efforts should be made to accelerate the inclusion of domestic vaccines into the NIP, and healthcare sectors has the responsibility to negotiate more competitive prices with manufacturers. Determining the target age for routine HPV vaccination is another critical issue. Our study finds that the short-term effect of increasing vaccination rates in the \u0026le;\u0026thinsp;14 age group is limited, likely due to the low level of sexual activity among girls aged 9\u0026ndash;14. According to the latest national sexual behavior survey in China, the cumulative probability of sexual activity among 15-year-old girls is less than 5%\u003csup\u003e32\u003c/sup\u003e. However, our study suggests that QALYs would be maximized when vaccinating girls before the age of 14, emphasizing the long-term benefits of early vaccination. The target age of cervical screening also affected the health economics outcomes. Evidence has suggested that expanding the starting age to under 30 years improved the cost-utility of screening programs\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Our study further shows that expanding the screening age to 65 years on the basis of 35\u0026ndash;44 years yields higher benefits than expanding to 15 years, which may be due to the higher risk of cervical cancer among elderly women\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Besides, the cost and efficacy of treatment for advanced cancer significantly influence the ICUR, indicating the need to ensure the life quality for late-stage survivors.\u003c/p\u003e\u003cp\u003ePromoting ongoing strategies to the target level faces many challenges, particularly in terms of insufficient supply, poor accessibility, and high costs of HPV vaccines\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. In our study, under the assumption of limited supply and reduction in protective effect with fewer doses, we find that the health economics benefits of single dose vaccination for girls under 14 years followed by supplementary vaccination before 25 years are greater than those of similar two or three doses scenarios. This result complements a previous comparison between two doses and single dose catch-up vaccination strategies\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, and provides a valuable reference for alleviating vaccine supply constraints, as well as supporting the adoption of single-dose vaccination programs in China. As regards cervical screening, the main challenges include optimizing personnel utilization and improve screening efficiency, which could be achieved through AI-assisted screening\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In this study, we find that among the ongoing and WHO-recommended screening pathways, HPV testing once every 5\u0026ndash;10 years has the highest cost-utility, which is align with previous assessments conducted in developing countries\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. On this basis, replacing the manual TCT method with AI-TCT would yield the highest cost-utility and simultaneously increase the QALYs, supporting the potential application of AI-TCT in China. However, this conclusion largely relies on the assumption that AI-TCT offers higher sensitivity and lower cost than manual TCT\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Quality control and high utilization of devices should be prioritized in AI-TCT promotion.\u003c/p\u003e\u003cp\u003eThis study clarified the intervention effect of ongoing cervical cancer elimination strategies in China, confirming that continued promotion of the strategies to achieve the 2030 goal yields health economic benefits. The model was calibrated using real-world screening records, incorporating segmented model assumptions referring to COVID-19 lockdown level, thereby enhancing the accuracy of modeling. This study thoroughly considered the potential development of HPV vaccination and cervical screening and evaluated the combined effects of interventions. However, there exists several limitations. First, this study only considered first-time HPV infection and ignored the co-infections involving different genotypes, which may have led to an underestimation of HPV prevalence. Second, since the ongoing strategies primarily target the women population, this study simplified the development status of HPV-related cancers among heterosexual men. Further studies focusing on men is necessary. Finally, the lack of multicenter real-world data for external validation may have introduced bias in parameter calibration. We assumed that regional discrepancies in parameters were solely attributable to differences in population structure and intervention participation rates, and parameters reflecting the actual situation at different regional levels were incorporated, ensuring a reasonable degree of consistency in the calibrated transmission parameters.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe real-world epidemiological data were gathered from Shenzhen Baoan Women\u0026apos;s and Children\u0026apos;s Hospital, which are not publicly available due patient privacy, but are available from the corresponding author on reasonable request. All model parameters that support the findings of this study are available from open accessed websites, according to the references in Table 1.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by Shenzhen Science and Technology Program (A2302001), Shenzhen Natural Science Foundation (JCYJ20240813141023031), Guangdong Science and Technology Program (2024A050505008), National Natural Science Foundation of China (82203291), Medical Scientific Research Foundation of Guangdong Province of China (A2025145). All funding parties did not have any role in the design of the study or in the explanation of the data.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eSiyang Liu, Yuwei Li and Jianxin Zhen conceived the idea and protocol. Yuwei Li and Yi-Fan Lin built the model and interpreted the findings. Yuwei Li finalized the analysis and wrote the manuscript. Siyang Liu and Jianxin Zhen revised the manuscript. Jianxin Zhen and Fangfang Chen provided the data. Boyu Cai and Quanfu Zhang provided clinical guidance for the analysis. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank all members for carefully reading and commenting on the manuscript. We thank staff members at disease control institutions, hospitals, and health administrations across China where epidemics occurred for field investigation, administration, and data collection. We thank all open source website for sharing data. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, et al. 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BMC Med. 2023;21:48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12916-023-02748-3\u003c/span\u003e\u003cspan address=\"10.1186/s12916-023-02748-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Human papillomavirus (HPV), HPV vaccination, Cervical screening, Evaluation of preventive interventions, Mathematical model of infectious diseases","lastPublishedDoi":"10.21203/rs.3.rs-7855155/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7855155/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe infection of high-risk human papillomavirus (hr-HPV) and related cervical cancer have greatly threatened women health. However, the benefits of ongoing strategies in China remains unclear. Insufficient vaccine supply and excessive screening workload have hindered the widespread implementation of HPV immunization plans.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe constructed stratified mathematical models to simulate the transmission of hr-HPV among women under ongoing strategies, and calculated the incremental cost-utility ratio (ICUR) to compare the health-economics benefits among different intervention pathways, including different vaccine type and dose schedules, commonly recommended screening algorithms as well as AI-assisted TCT method. The model parameters were calibrated according to real-world HPV prevalences, incorporating segmented model assumptions reflecting the levels of COVID-19 lockdown.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe model shows that ongoing strategies in China are projected to reducing cervical cancer prevalence continuously and demonstrate good cost-utility (ICUR: 22,532.04 USD/QALY, 21,968.74-23,095.34), when increasing the participation rate to achieve the global goal by 2030. HPV vaccination provides substantial health benefits, while cannot improve the cost-utility at current cost. Offering single-dose of 2vHPV vaccine to girls before the age of 14 and reallocating excess doses to women under 25 yields a lower ICUR compared to two- or three-dose scenarios. Cervical screening can significantly reduce the ICUR. Among the screening methods, HPV testing demonstrates higher cost-utility, while AI-TCT outperforms all recommended traditional pathways.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe ongoing strategies demonstrate substantial health and economic benefits in achieving the 2030 global target; however, neither screening nor vaccination alone can deliver optimal effectiveness. The findings highlight the importance of combining vaccination and screening, and provide evidence for the promotion of single-dose vaccination and AI-TCT projects to alleviate resource burdens.\u003c/p\u003e","manuscriptTitle":"Modelling the epidemic dynamics of HPV among women in China and optimization of ongoing cervical cancer elimination strategies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-17 14:15:58","doi":"10.21203/rs.3.rs-7855155/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-02T11:14:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-31T02:11:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-30T15:52:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"221370428636457745207650945033613192458","date":"2026-01-07T07:43:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78230438288695682435635406598122302433","date":"2026-01-07T04:05:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-30T01:27:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51214622178135460197962906660407566926","date":"2025-12-18T11:31:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-15T08:17:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128695944780056499593173527051366205717","date":"2025-12-15T08:08:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226111785927701669442771780753885074945","date":"2025-12-13T01:12:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110846967095125757398903387986597123827","date":"2025-11-06T09:10:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-06T09:07:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-14T07:13:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-14T07:12:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medicine","date":"2025-10-14T07:02:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4809ef52-486b-4ad4-aaec-2a0407d1af64","owner":[],"postedDate":"November 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T16:03:40+00:00","versionOfRecord":{"articleIdentity":"rs-7855155","link":"https://doi.org/10.1186/s12916-026-04881-1","journal":{"identity":"bmc-medicine","isVorOnly":false,"title":"BMC Medicine"},"publishedOn":"2026-04-22 15:58:25","publishedOnDateReadable":"April 22nd, 2026"},"versionCreatedAt":"2025-11-17 14:15:58","video":"","vorDoi":"10.1186/s12916-026-04881-1","vorDoiUrl":"https://doi.org/10.1186/s12916-026-04881-1","workflowStages":[]},"version":"v1","identity":"rs-7855155","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7855155","identity":"rs-7855155","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}