Structural Determinants of HPV Vaccination Inequalities: A Multiregional Analysis across Six WHO Regions

Structural Determinants of HPV Vaccination Inequalities: A Multiregional Analysis across Six WHO Regions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Structural Determinants of HPV Vaccination Inequalities: A Multiregional Analysis across Six WHO Regions Siyan Liu, Xiaowei Man, Xingli Cao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7654138/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cervical cancer remains one of the most prevalent malignancies affecting women globally, and HPV vaccination is widely recognized as the cornerstone of primary prevention. Drawing on global macro-level data from 2013 to 2018, this study systematically evaluated the spatiotemporal patterns of HPV vaccination coverage and its associations with multiple structural determinants. By integrating indicators including first- and final-dose vaccine coverage, cervical cancer mortality, per capita GDP, physician density, government health expenditure, women’s educational attainment, female social participation, labor force involvement, and the inclusion of HPV vaccines in national immunization programs (NIPs), and applying visualization, correlation analysis, and Slope Index of Inequality (SII) modeling, we revealed pronounced inequities in HPV vaccination across the globe. Through the integration of visualization, correlation analyses, and Slope Index of Inequality (SII) modeling, we uncovered marked inequities in HPV vaccination coverage across the globe. The findings demonstrate that structural health inequalities constitute a fundamental barrier to achieving equitable HPV vaccine uptake. Future strategies should emphasize multidimensional policy interventions, including prioritized fiscal investment, institutional design optimization, and gender equity promotion, to enhance resource allocation efficiency and improve access to women’s health services. These measures will provide robust scientific evidence and policy guidance for advancing the global cervical cancer elimination agenda. HPV Vaccination Coverage Cervical Cancer Structural Health Inequality Socioeconomic Factor National Immunization Program (NIP) Global Health Policy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1、Introduction Cervical cancer is a significant global public health burden, ranking as the fourth most prevalent malignancy among females. According to Global Cancer Statistics (GLOBOCAN 2020), approximately 604,000 new cases and 342,000 deaths occur annually, with more than 85% of these deaths concentrated in low- and middle-income countries (LMICs) (Sung et al., 2021 ). This striking disparity underscores persistent structural inequities in healthcare access, screening coverage, and the delivery of preventive interventions. Robust screening systems and broad vaccine availability have markedly reduced cervical cancer incidence and mortality in high-resource settings. By contrast, LMICs continue to experience limited effectiveness due to inadequate healthcare resources, fragile infrastructures, and socioeconomic constraints (Xiong et al., 2024 ) Persistent infection with human papillomavirus (HPV) is the primary cause of cervical cancer, and prophylactic HPV vaccination is recognized as one of the most effective strategies for reducing both incidence and mortality. In 2020, the World Health Organization (WHO) introduced the “90-70-90” global targets for 2030: 90% of girls fully vaccinated with HPV by age 15, 70% of women screened with a high-performance test at ages 35 and 45, and 90% of diagnosed cases receiving appropriate treatment (Zhou et al., 2025 ). However, progress toward these targets has been markedly uneven worldwide. While many high-income countries have achieved or are approaching the expected coverage levels, vaccination rates in LMICs remain persistently low, reflecting structural health inequities in global vaccine access (Shato et al., 2023 ) Structural health inequalities are shaped by socioeconomic, sociocultural, and policy-related determinants, influencing prevention, diagnosis, and treatment pathways. Previous studies indicate that socioeconomic factors (e.g., national income level, public health expenditure), sociocultural factors (e.g., educational attainment, gender equity, labor force participation), and policy-related factors (e.g., physician density, immunization program coverage) are strongly associated with HPV vaccination coverage (Branda et al., 2024 ). However, most existing studies have focused on single regions or isolated determinants, with limited attempts to establish an integrated and multidimensional analytical framework at the global scale. Among the available metrics for assessing structural inequality, the Slope Index of Inequality (SII) quantifies socioeconomic and structural disparities as continuous measures, capturing gradients from the most disadvantaged to the most advantaged groups (Nguyen et al., 2025 ). The SII facilitates both the evaluation of socioeconomic disparities in vaccination coverage and cross-regional as well as temporal comparisons of structural inequality trends. Accordingly, this study employs the SII as the central analytical tool to assess disparities across socioeconomic, sociocultural, and policy dimensions. By integrating these measures with vaccination coverage and cervical cancer mortality, we conduct a chain pathway analysis to systematically characterize global patterns of inequality (Acharya et al., 2022 ). In addition, dynamic regional and temporal trends, as well as their long-term impact on vaccination disparities, remain insufficiently quantified, which has limited the development of targeted public health policies. Currently, systematic research assessing structural health inequalities and HPV vaccination gaps using multi-year global data remains scarce, particularly regarding comparative analyses across the six WHO regions, which encompass diverse socioeconomic, sociocultural, and policy contexts (Bruni et al., 2016 ). Therefore, establishing a systematic indicator framework and applying statistical models that integrate the three dimensions with vaccination coverage and cervical cancer mortality within a unified causal chain analysis is essential. This approach enables the quantitative characterization of both the distribution and evolution of structural disparities, thereby clarifying global patterns and drivers of HPV vaccination inequality (Budu et al., 2022 ). To address these gaps, this study utilizes multidimensional global data from the six WHO regions (2013–2018) to systematically assess the association between HPV vaccination coverage and cervical cancer mortality. It further quantifies the influence of socioeconomic, health system, and gender equality–related factors on disparities in vaccine uptake. Unlikely prior studies that primarily examined single regions or limited variables, the present study provides broader coverage, a more comprehensive indicator framework, and comparative analytical approaches, thereby characterizing the mechanisms of structural health inequalities in HPV vaccine implementation from a global perspective. Furthermore, by incorporating quantitative indicators such as the SII, this study aims to generate context-specific policy recommendations for countries with varying resource settings, thereby supporting progress toward the WHO “90-70-90” targets. 2. Materials and methods 2.1 Data sources This study employed secondary data from multiple countries between 2013 and 2018, obtained exclusively from internationally recognized databases. HPV vaccination coverage data (first- and final-dose rates) were extracted from the WHO/UNICEF Immunization Coverage Estimates (WUENIC) database ( https://immunizationdata.who.int ). Cervical cancer age-standardized mortality rates (ASMRs) were sourced from the WHO Global Health Estimates (GHE) database ( https://www.who.int/data/global-health-estimates ). Socioeconomic indicators included GDP per capita, government health expenditure (expressed both as a share of GDP and per capita), and physician density (per 1,000 population), which were obtained from the World Bank ( https://data.worldbank.org ). Sociocultural indicators, including adult female literacy rate, female labor force participation rate, and the proportion of parliamentary seats held by women, were derived from the United Nations Development Programme (UNDP) ( https://hdr.undp.org ) and the World Bank. Policy-related indicators comprised HPV vaccination inclusion in national immunization programs (NIPs) and World Bank income classifications (low-income, lower-middle-income, upper-middle-income, and high-income), as reported by WHO and the World Bank. All datasets were harmonized at the country-year level using ISO3 country codes, and monetary indicators were standardized to current US dollars at prevailing annual exchange values. Countries were eligible for inclusion if they reported continuous HPV vaccination coverage and cervical cancer mortality data for 2013–2018, along with complete structural social indicators. Nations with missing essential variables or extreme outliers were excluded from the analysis. 2.2 Regional classification and sample structure According to the World Health Organization (WHO) classification, all countries were grouped into six regions: Africa (AFR), the Americas (AMR), South-East Asia (SEAR), Europe (EUR), the Eastern Mediterranean (EMR), and the Western Pacific (WPR). This generated a balanced panel dataset, with countries as the unit of analysis and structured by country–year observations. 2.3 Definition of indicators and variable construction HPV vaccination coverage: Coverage rates (%) for first- and final-dose HPV vaccination among females were defined as the primary independent variables. Health indicator: The age-standardized mortality rate (ASMR) of cervical cancer (per 100,000 population) was specified as the principal dependent variable. Structural social factors, encompassing socioeconomic, sociocultural, and policy dimensions, included indicators reflecting national resource allocation and gender disparities. These indicators comprised GDP per capita, government health expenditure (as % of GDP and per capita), physician density, adult female literacy rate, female labor force participation rate, proportion of parliamentary seats held by women, inclusion of HPV vaccination in national immunization programs (NIPs), and World Bank income classification. 2.4 Statistical analysis methods Trend analysis: Temporal trends in HPV vaccination coverage and cervical cancer mortality across the six WHO regions from 2013 to 2018 were examined using time-series plots. Correlation analysis: Pearson correlation coefficients were calculated to evaluate linear associations between vaccination coverage and cervical cancer mortality. Regression modeling: Multivariate linear regression and generalized linear models (GLMs) were applied, with structural factors specified as explanatory variables and vaccination coverage or mortality as dependent outcomes. Year and regional fixed effects were included to isolate the independent effects of structural determinants. To quantitatively assess the inequality between HPV vaccination coverage and socioeconomic status (SES), this study introduced the SII. SII is calculated based on the Ridit regression method. Countries are first ranked according to SES indicators (e.g., GDP per capita, educational attainment), then their cumulative population proportions are computed to generate Ridit scores (ranging from 0 to 1). HPV vaccination coverage is then regressed on Ridit values using weighted least squares. The model is expressed as: $$\:Yi=\alpha\:+\beta\:Ri+ϵi$$ where \(\:Yi\) is the vaccination coverage of \(\:group\:i\) , \(\:\:Ri\) is the corresponding Ridit value, and β represents the SII, reflecting the absolute gap in coverage between the lowest and highest SES groups. This study captures the absolute gradient (SII) of HPV vaccination coverage across SES strata. This dual approach enables a more comprehensive understanding of how structural inequalities shape vaccination uptake, providing a robust quantitative framework for cross-regional comparisons and policy analysis. In this study, the Slope Index of Inequality (SII) was used to systematically quantify absolute disparities in HPV vaccination coverage attributable to three structural dimensions (socioeconomic, sociocultural, and policy) and was incorporated throughout all stages of the analysis. SII values for key indicators within each structural dimension (e.g., GDP per capita, female educational attainment, physician density) were calculated by ranking countries according to each factor and dividing them into deciles, thereby capturing within-dimension inequalities. Comparisons across dimensions were then conducted to assess the relative contributions of different structural domains, and temporal changes from 2013 to 2018 were analyzed to characterize the dynamic evolution of disparities. The relative rank (ridit score) was used as the independent variable, and vaccination coverage was specified as the dependent variable. Weighted linear regression models (weighted by national population) were fitted, and the regression coefficient was interpreted as the SII, representing the absolute disparity (percentage points) between the most disadvantaged and most advantaged groups. 2.5 Data processing and visualization All data cleaning, statistical analyses, and figure preparation were conducted using standard software packages. SPSS 26.0 (IBM Corp., Armonk, NY, USA) was used to compute descriptive statistics, Pearson correlation coefficients, and significance tests, and to fit regression models; inequality metrics, including the Slope Index of Inequality (SII), were also derived in SPSS. Origin 2021 (Origin Lab Corp., Northampton, MA, USA) was used to fit trend lines, render correlation scatter plots, and display fitted linear regressions. Figures and final layouts were prepared in Adobe Illustrator 2022 (Adobe Inc., San Jose, CA, USA) to ensure publication-quality output and visual clarity. All graphical outputs, including time-series plots, correlation scatter plots with fitted lines, stratified bar charts of structural factors, and inequality index visualizations, were generated directly from the underlying statistical analyses to ensure scientific rigor and consistent visual presentation. 3. Results and discussion 3.1 The role of institutions and policies in vaccination equity 3.1.1 Structural impacts of income level and national immunization program inclusion on HPV vaccination coverage Global disparities in HPV vaccination coverage are shaped not only by absolute economic differences but also by the broader influence of social determinants of health (SDH) on the effectiveness of public health interventions. Income level affects vaccination both directly, by determining affordability and supply chain capacity, and indirectly, through pathways such as educational attainment, information dissemination, healthcare resource distribution, and governance capacity (Maness & Thompson, 2019 ). As shown in Fig. 3 A, high-income countries (HICs), primarily located in Europe, the Americas, and the Western Pacific, generally possess strong fiscal investment, robust cold-chain infrastructure, and mature primary healthcare networks, which together enable vaccination coverage to reach the vast majority of target populations. These countries typically exhibit high health literacy and low vaccine hesitancy, fostering a positive feedback loop in which policy initiatives and public acceptance reinforce each other (Dube et al., 2013 ).As a result, vaccination coverage has remained among the highest worldwide, exceeding 80% in some years. In contrast, low-income countries (LICs) and lower-middle-income countries (LMICs), concentrated in Africa and the Eastern Mediterranean, face constrained budgets, shortages of healthcare personnel, and underdeveloped transport and storage infrastructure (Gallagher et al., 2018 ). These limitations undermine vaccine accessibility, timeliness, and affordability, resulting in persistently low coverage rates, often under 30%. Moreover, constrained economic conditions reduce institutional capacity and workforce effectiveness, limiting the reach and execution of immunization programs even when such frameworks are formally established (Bruni et al., 2016 ). Against this backdrop, the inclusion of HPV vaccination in National Immunization Programs (NIPs) exerts a significant institutional effect. Theoretically, NIP inclusion reduces economic and informational barriers through government subsidies, centralized procurement, and standardized vaccination strategies, thereby increasing coverage (Bruni et al., 2021 ). As shown in Fig. 3 B, countries incorporating HPV vaccination into NIPs consistently exhibit higher coverage rates than those without, with disparities reaching up to 40% in some regions. However, this institutional advantage is weaker in LMICs, where limited fiscal allocations, supply chain disruptions, weak primary healthcare implementation, and cultural or religious resistance to vaccination may in some cases offset the intended benefits of policy design. This observation is consistent with the Health System Building Blocks framework, which posits that policy effectiveness depends on coordinated functioning across multiple system components (Malik et al., 2024 ). Taken together, these findings suggest that the combined effects of income level and NIP inclusion vary substantially across WHO regions. This trend is consistent with prior cross-national research, underscoring that the interplay between economic and institutional factors is a key driver of HPV vaccination coverage (Ozawa et al., 2016 ). Multidimensional analysis revealed a significant interaction between income level and NIP inclusion in shaping HPV vaccination coverage. High-income countries with NIP integration achieved high coverage through a dual resource and institutional advantage, whereas low-income countries without NIP support fell into a low-coverage trap characterized by simultaneous deficits in funding and institutional capacity (Gallagher et al., 2018 ). This cumulative effect underscores the need for a multidimensional strategy to reduce global HPV vaccination disparities: reinforcing financial and infrastructural capacity from the socioeconomic dimension, enhancing health education and public awareness from the sociocultural dimension, and strengthening immunization planning and implementation from the policy dimension (Wigle et al., 2016 ). In low-income countries, breaking the cycle of low income, weak institutional support, and low vaccination coverage requires integrating international financial and technical assistance with education campaigns and culturally tailored interventions (Binagwaho et al., 2012 ). 3.1.2 Structural relationship between women’s political representation and HPV vaccination coverage (Fig. 5 ) Women’s representation in national parliaments reflects the broader gender-institutional environment of a country and is widely recognized as a critical political determinant of women’s health priorities (Quamruzzaman & Lange, 2016 ). Using macro-level data from six WHO regions (2013–2018), this study identified a significant structural gradient linking women’s parliamentary representation to HPV vaccination coverage, most pronounced in vaccination completion rates. As shown in Figs. 5 A–F, women’s parliamentary representation was consistently and positively associated with first-dose HPV vaccination coverage across all years. Marked regional disparities were observed. In Europe and the Americas, women’s parliamentary representation typically exceeded 25%, with first-dose HPV coverage generally ranging from 50% to 80%. By contrast, in Africa and the Eastern Mediterranean, women’s parliamentary representation was often below 20%, corresponding to vaccination rates typically under 30%, with some countries reporting persistently negligible coverage (near zero). Figures 5 G–L further demonstrate the robustness and amplified effect of this relationship when examining full-course vaccination completion (final-dose coverage). Compared with first-dose coverage, final-dose completion is a more sensitive indicator of the sustained implementation capacity of health systems and the degree of public trust. In countries with stronger institutional representation of women, vaccination completion rates consistently remained at moderate to high levels. Conversely, in regions with limited female political representation, HPV vaccination completion rates remained substantially lower, even when included in NIPs, due to weak implementation capacity and fragile grassroots mobilization structures, resulting in a pronounced policy–coverage gap (Macmillan et al., 2018 ). Mechanistically, women’s parliamentary representation, an institutional marker of gender empowerment, exerts system-level influence on vaccination uptake through multiple pathways. At the institutional level, female legislators are more likely to champion women’s and children’s health agendas, including cervical cancer prevention, sexual health education, and budgetary commitments for vaccination programs (Wigle et al., 2016 ). From an economic–institutional perspective, they tend to steer budget allocations and resource priorities toward women’s health, thereby improving vaccine accessibility and affordability. At the sociocultural level, women legislators can reshape public discourse, reduce cultural resistance and stigma surrounding HPV vaccination, and enhance public acceptance (Araujo & Tejedo-Romero, 2016 ). Notably, institutional gender empowerment plays a significant moderating role in shaping the effects of economic and sociocultural factors. High levels of women’s institutional participation amplify the positive effects of financial investment and cultural support on vaccination coverage, whereas low participation constrains coverage even under favorable economic conditions or high cultural acceptance. This moderating mechanism forms an institution–economic–sociocultural triadic loop, elucidating the institutional roots of vaccination disparities among countries with otherwise comparable economic conditions. Moreover, as a structural marker of gender empowerment, women’s parliamentary representation advances cervical cancer prevention, sexual health education, and vaccine financing, and supports budget allocations, legislative priorities, and accountability mechanisms that favor women’s health, thereby improving the accessibility, acceptability, and cultural alignment of HPV vaccination (Mackenbach, 2012 ). These structural associations are consistent with the Health Opportunity Structure framework, which posits that institutional gender empowerment shapes which health issues are prioritized on policy agendas, how they are implemented, and whether health services are effectively absorbed and utilized by society (Ozawa et al., 2016 ). The stable positive associations identified in this study indicate that gender–institutional environments shape not only the design of vaccination policies but also the micro-level mechanisms through which these policies are socially enacted. Time-series analysis revealed no significant convergence of this structural gradient over the six-year period, indicating strong path dependence in gender–institutional inequalities and suggesting that short-term policy interventions are unlikely to reverse these patterns (Ali et al., 2022 ). In several lower-middle-income countries, despite the inclusion of HPV vaccination in NIPs, the persistent lack of women’s political representation has deprived programs of institutional backing and social consensus, thereby constraining improvements in coverage. Notably, several outliers were identified; for example, in some Western Pacific countries, relatively high women’s parliamentary representation coincided with persistently low vaccination rates, highlighting that although gender empowerment is a critical antecedent, it is not the sole determinant of vaccine equity. Other factors, including cultural beliefs, community mobilization, health system capacity, and educational attainment, function as critical synergistic mechanisms influencing vaccination coverage and should be incorporated into comprehensive analytical models (Westen et al., 2019 ). In summary, institutional gender empowerment emerges as a pivotal factor shaping HPV vaccine equity, with a significant moderating influence on economic and sociocultural determinants. Future public health strategies should systematically integrate this indicator into the design of multidimensional, structurally oriented vaccination policies, thereby advancing the dual goals of gender justice and health equity. 3.2 Economic resource allocation and healthcare accessibility 3.2.1 Potential impact of physician density on HPV vaccination Coverage Physician density, a critical structural marker of health system capacity, is widely recognized as a key mediating factor linking vaccination coverage potential to health equity. Using WHO regional data from 2013 to 2018, we analyzed temporal trends in physician density (per 1,000 population) and examined its association with first-dose HPV vaccination coverage. As shown in Fig. 3 C, global physician density exhibited pronounced geographic disparities. Since 2013, Europe and the Americas have maintained relatively high levels (> 3.5 and > 2.0 per 1,000, respectively), whereas Africa and Southeast Asia have remained below 1.0 per 1,000, with negligible growth. Figure 3 D, presented as a physician-to-population heatmap, further demonstrates the persistence and structural rigidity of these regional disparities. In Africa and the Eastern Mediterranean, physician density improved only marginally despite increased global health investments from 2013 to 2018, underscoring the fragility and persistent lag of primary healthcare infrastructure. In line with World Bank and WHO minimum thresholds for essential healthcare workforce density (1.0–1.5 per 1,000), Africa and Southeast Asia have persistently remained at levels of severe medical resource scarcity, marking them as prototypical zones of systemic healthcare disadvantage. From the perspective of HPV vaccination, such structural disparities critically constrain both initiation and completion of vaccination. Within the framework of healthcare accessibility, physician workforce determines the physical feasibility of supply-side provision and indirectly shapes public willingness and trust in vaccination by influencing health education, program organization, cold-chain logistics, and adverse event management. Physician shortages compromise not only service availability but also critical dimensions such as acceptability and appropriateness of care (Pozo-Martin et al., 2017 ). This study identified a stable social gradient between physician density and HPV vaccination coverage. High-density regions (e.g., Europe and the Americas) maintained consistently higher HPV coverage with steady annual gains, whereas resource-limited regions (e.g., Africa and the Eastern Mediterranean) exhibited a vaccine deprivation phenomenon, where NIP inclusion failed to translate into operational coverage due to inadequate medical staffing (Habib et al., 2020 ; Lindstrom, 2022 ). This structural shortfall is consistent with Kawachi’s opportunity structure theory, underscoring that healthcare workforce is a foundational prerequisite, rather than a peripheral factor, for achieving vaccination equity. Although derived from ecological, region-level data and subject to potential confounding, our findings provide structural evidence that strengthening physician supply can enhance vaccination equity. Prior research has also shown that physician density is positively associated with childhood vaccination rates (e.g., DTP, MMR) across diverse national models, with effects particularly pronounced in LMICs (Kruk et al., 2018 ). In summary, physician density reflects disparities in healthcare investment and resource allocation, shapes health literacy and vaccine acceptance, and indicates the strength of primary healthcare networks and immunization program implementation. The significant structural inequality linking physician density to HPV vaccination coverage underscores that global cervical cancer control strategies must go beyond vaccine supply and policy frameworks. Strengthening and optimizing the healthcare workforce is essential to ensure the efficient and equitable translation of vaccination policies into actual uptake. 3.2.2 Structural gaps between health expenditure and HPV vaccination coverage National fiscal capacity and patterns of health expenditure are critical structural determinants of vaccination equity in the advancement of global HPV vaccine coverage (Machingaidze et al., 2013 ). As shown in Figs. 7 A–F, HPV vaccination rates (first and final doses) show clear stratification according to the share of government health expenditure in GDP. In high-income regions such as Europe and the Americas, health spending typically exceeded 8% of GDP, with vaccination coverage maintained at 60–80%. By contrast, Africa and the Eastern Mediterranean allocated less than 5% of GDP to health, with vaccination coverage typically below 30% and in some cases near zero. This trend underscores a positive association between fiscal capacity and vaccination performance (Lupu & Tiganasu, 2023 ). As further shown in Figs. 7 G–L, per capita health expenditure exceeded USD 500 in the Americas and Europe, where vaccination coverage was sustained at relatively high levels. In contrast, regions with per capita spending below USD 200 exhibited markedly low vaccination coverage, reflecting a structural disconnect between limited fiscal support and weak immunization capacity. Figure 8 presents a cross-sectional view of 2020 fiscal structures, with dual axes illustrating the alignment between government health expenditure (% of GDP) and per capita spending. Results indicate that European and American countries clustered in the upper-right quadrant, characterized by high-intensity investment and high resource density, representing an ideal fiscal structure of high spending and high coverage. Conversely, African and Eastern Mediterranean countries clustered in the lower-left quadrant, where fragile fiscal foundations limited institutional conditions for vaccine accessibility. This structural disconnect between fiscal capacity and vaccination uptake may underlie persistent barriers to improving coverage. Importantly, absolute fiscal expenditure alone does not fully explain variation in vaccination rates. Several upper-middle-income countries had adequate fiscal resources but still exhibited low vaccination rates, suggesting that the effective translation of spending depends on institutional efficiency, governance capacity, and social mobilization (Kruk et al., 2018 ; Rughinis et al., 2022 ). In the context of widespread vaccine hesitancy, fiscal investment alone cannot achieve substantial improvements in coverage; instead, the interplay of fiscal capacity, institutional performance, and public trust must be jointly addressed (Lupu & Tiganasu, 2023 ). Taken together, these results indicate that fiscal capacity, institutional effectiveness, and sociocultural trust form an interdependent mechanism shaping HPV vaccination coverage, with institutional effectiveness serving as the critical mediator linking economic foundations to social acceptance. 3.2.3 Fiscal–Behavioral mismatch: structural gaps between government health expenditure and HPV vaccination coverage In analyzing the structural drivers of HPV vaccination inequities, the conversion efficiency between fiscal expenditure and vaccination uptake is a critical measure of public health system performance. Figures 9 and 10 illustrate the structural gaps observed from 2013 to 2018 between government health expenditure, expressed both as a share of GDP and as per capita spending, and first-dose HPV vaccination coverage, underscoring the pronounced disconnect between fiscal capacity and vaccination performance. As shown in Figs. 9 A–F, discrepancies between first-dose coverage and health expenditure as a share of GDP reveal imbalances in fiscal allocation and behavioral response across regions. Europe and the Americas maintained high fiscal shares but lagging vaccination performance, whereas Africa and the Eastern Mediterranean faced a double disadvantage of limited resources and weak institutional execution, reflecting compounded structural constraints (Wang et al., 2025 ). Notably, in the Americas (e.g., 2015–2016), a high-spending but moderate-coverage pattern was observed, underscoring the limited translation of fiscal input into vaccination uptake. Figures 9 G–L further illustrate structural deviations between per capita government spending and first-dose coverage. In regions such as the Eastern Mediterranean and Africa, per capita spending rose but coverage remained low, reflecting a mismatch of increasing spending without corresponding uptake. By contrast, Europe exhibited a favorable fiscal-vaccination alignment, indicative of strong institutional efficiency and social mobilization (Larsson et al., 2022 ). Figure 10 presents fiscal–behavioral decoupling risk in a bivariate plot, with first-dose coverage on the x-axis, expenditure intensity (GDP share or per capita) on the y-axis, and point size representing structural disparities. Distributional patterns show Europe and parts of the Western Pacific clustered in the high-spending–high-coverage quadrant, reflecting positive fiscal–behavioral alignment, while the Eastern Mediterranean and Africa remained concentrated in the low-spending–low-coverage quadrant, entrenched in compounded structural disadvantage. Several upper-middle-income countries, despite strong fiscal capacity, lagged in vaccination uptake, suggesting that sociocultural barriers such as limited cultural acceptance and trust deficits in institutional implementation, policy transmission, or social mobilization may play a role (Nova et al., 2023 ). Overall, vaccination uptake is not a linear outcome of fiscal investment but the result of complex interactions among economic capacity, institutional effectiveness, and sociocultural context, with institutions serving as the key mediator linking resources to behavioral outcomes. While fiscal spending provides the material foundation for vaccine delivery, its effectiveness depends on operational feasibility, policy implementation, and public trust. In the absence of cultural adaptation and effective health communication, even abundant resources may result in a high-investment but low-uptake mismatch. Achieving structural health equity therefore requires a tripartite framework of fiscal investment, institutional safeguards, and social mobilization. Within this framework, institutions regulate both economic allocation and cultural alignment to enhance policy translation, ensure sustainability, and reduce vaccination disparities across regions and populations. 3.2.4 Temporal trends in regional HPV vaccination coverage HPV vaccination coverage has exhibited substantial regional variation and uneven progress over time. Figure 1 illustrates temporal trends in HPV vaccination coverage across the six WHO regions, with four indicators: overall first-dose coverage (A), overall final-dose coverage (B), first-dose coverage before age 15 (C), and final-dose coverage before age 15 (D). The results indicate pronounced regional disparities and persistent structural inequalities. For overall first-dose coverage (Fig. 1 A), the Americas maintained the highest levels, rising from 38.2% in 2013 to 65.9% in 2018, an increase of about 28% over six years. By contrast, Africa and Southeast Asia showed limited improvement, reaching 18.0% and 7.3% in 2018, respectively. The Eastern Mediterranean remained below 5% throughout the study period, indicating persistently low coverage. The Western Pacific and Europe showed intermediate levels, with 2018 rates of 7.2% and 30.1%, respectively, but growth remained relatively slow. Trends in overall final-dose coverage (Fig. 1 B) were similar but exhibited even greater regional contrasts. In 2018, the Americas reached 53.9%, representing an increase of 25 percentage points from 28.9% in 2013. Final-dose coverage in Africa and Southeast Asia remained below 10% in 2018, underscoring greater barriers to completing the vaccination schedule. In the Eastern Mediterranean, coverage remained below 3% for six consecutive years, indicating an absence of systematic vaccine rollout and highlighting the need for targeted public health interventions (Bruni et al., 2021 ). Regional disparities were more pronounced for vaccination before age 15 ( Figs. 1 C–D). By 2018, the Americas achieved 70% for the first dose and 56% for the final dose, indicating strong prioritization of children and adolescents. In contrast, final-dose coverage before age 15 remained below 30% in all other regions, with the Eastern Mediterranean and Southeast Asia remaining below 5%, well below the WHO target of full vaccination before age 15 (Dorji et al., 2021 ). Between 2013 and 2018, HPV vaccination patterns across the six WHO regions remained highly divergent, with no evidence of convergence, indicating the persistence of global structural vaccine inequality. Disparities extended beyond baseline coverage to completion rates and early-age vaccination. From a socioeconomic perspective, the Americas, with higher GDP per capita and health expenditure, maintained stable support for vaccine procurement and delivery, whereas SII results indicated that economic disparities in low-income regions amplified inequities. In the sociocultural dimension, regions with higher female education and labor participation (e.g., the Americas and Europe) consistently achieved higher coverage, whereas areas with limited education showed deficits in awareness and vaccine uptake. Institutionally, comprehensive NIP inclusion and higher physician density facilitated improvements, whereas weak health systems in the Eastern Mediterranean and Africa imposed major constraints. Notably, vaccination rates in the Americas plateaued after 2014, indicating system maturity, whereas most low- and middle-income regions remained at early stages of system development, hindered by slow policy progress, resource shortages, and limited public awareness (Han et al., 2025 ; Luthra et al., 2021 ). These findings align with global health equity theory, which posits that under resource scarcity, preventive interventions such as vaccines concentrate in regions with stronger institutions and fiscal capacity, thereby widening initial disparities. Consistent with the framework of social determinants of health, uneven distribution of economic resources, education, and health system coverage entrenches inequities by shaping accessibility, affordability, and willingness to vaccinate (Onagoruwa & Wodon, 2025 ). Thus, the observed temporal patterns highlight both disparities in coverage and the structural interplay between health governance and social stratification. Future strategies for vaccine equity should adopt stratified, targeted, and structurally informed approaches to reduce disparities and promote more equitable global coverage. 3.3 Cultural and social factors: cognition, gender, and collective behavior 3.3.1 Association Between Vaccination Coverage and Cervical Cancer Mortality This study systematically analyzed data from the six WHO regions to evaluate the impact of HPV vaccination on cervical cancer, focusing on the associations of first-dose coverage, final-dose coverage, and completion rates with cervical cancer mortality ( Fig. 2 a–c). The results indicated a consistent global pattern: vaccination coverage was inversely correlated with cervical cancer mortality, with the strongest association observed for full-course completion. These findings demonstrate that unequal vaccination coverage is a critical driver of global disparities in women’s health. Figure 2 a shows the association between first-dose coverage and cervical cancer mortality across regions. In the Americas (AMR) and Europe (EUR), first-dose coverage reached 68.5% and 59.2%, with corresponding mortality rates of 6.8 and 5.1 per 100,000, substantially lower than in other regions. By contrast, Africa (AFR) and the Eastern Mediterranean (EMR) recorded substantially lower first-dose coverage (13.2% and 18.7%) and the highest mortality rates (22.4 and 17.1 per 100,000). Southeast Asia (SEAR) showed moderate coverage (32.5%), but mortality remained high at 15.2 per 100,000. These results suggest that first-dose uptake alone is insufficient to provide effective immune protection. This aligns with the herd immunity threshold mechanism, which requires coverage above approximately 70% to establish a protective barrier against persistent HPV transmission and reinfection. Regions falling short of this threshold, even with vaccination programs in place, experience limited reductions in mortality (Arbyn et al., 2020 ; Bruni et al., 2021 ). Figure 2 b demonstrates an even stronger negative correlation between final-dose coverage and mortality. The Americas reported the highest completion rate (62.4%) with mortality reduced to 6.5 per 100,000, whereas Europe achieved 54.7% completion with mortality at 5.3 per 100,000. Africa had the lowest completion rate (8.7%) and the highest mortality (23.2 per 100,000). The Pearson correlation between completion rate and mortality was − 0.72 (P < 0.01 ), the strongest among all vaccination indicators. This finding underscores the critical importance of full-course vaccination, as first-dose initiation alone cannot substantially reduce cervical cancer mortality. The findings reflect the “full immunization protection mechanism,” whereby multiple doses are required to elicit durable and high-titer neutralizing antibody responses. Only through full completion can maximal individual protection be achieved, translating into substantial reductions in cervical cancer incidence and mortality at the population level (Kjaer et al., 2021 ). Figure 2 c presents a comprehensive analysis of completion rates in relation to cervical cancer mortality. Cross-sectional regression indicated that each 10-percentage-point increase in completion was associated with an average decline of 2.1 per 100,000 in mortality. Regions with higher baseline mortality, such as EMR and SEAR, derived greater reductions from increased vaccine coverage, indicating higher marginal health benefits in high-burden settings. This structural disparity reflects how uneven resource allocation and health system capacity amplify the effects of vaccination gaps. The findings align with the “marginal health benefit mechanism,” whereby additional coverage in high-burden regions prevents disproportionately more cases and deaths and yields greater health returns per unit of vaccine investment, such as larger reductions in DALYs and life-years gained, compared with low-burden settings (Garland, 2019 ; Jit et al., 2014 ). From a socioeconomic perspective, high-income regions with substantial health investment are better positioned to achieve broad and sustained vaccination coverage, whereas low-income regions experience persistent delays due to limited financial capacity. Sociocultural factors also play a critical role: populations with higher levels of education and stronger health awareness demonstrate greater acceptance of vaccination, while insufficient awareness in some cultural contexts continues to hinder uptake. At the institutional level, countries with comprehensive immunization programs, financial subsidies, and well-established primary health systems show faster progress in improving coverage, whereas weak policy frameworks limit the ability to ensure full completion (Van Minh et al., 2017 ). In summary, HPV vaccination coverage is strongly and inversely associated with cervical cancer mortality, with completion rate emerging as the most reliable predictor of mortality reduction. Together, these findings underscore the central role of HPV vaccination in public health interventions and provide robust evidence to guide global vaccination strategies. In low- and middle-income countries, policies should shift their focus from initiation to completion, ensuring continuity across the vaccination pathway. Such a shift is essential to maximize the vaccine’s impact on reducing cervical cancer mortality and to advance the broader goal of global health equity for women. 3.3.2 Potential impact of Female Labor Force Participation on HPV Vaccination Coverage This study examined the relationship between female labor force participation rate (FLFP) and HPV vaccination coverage (first- and final-dose) across the six WHO regions from 2013 to 2018, as shown in Fig. 6 . FLFP demonstrated a positive correlation with vaccination coverage, particularly in Europe (EUR), the Americas (AMR), and the Western Pacific Region (WPR). In EUR and AMR, most countries maintained FLFP levels between 55% and 65%. During the same period, HPV vaccination rates were consistently high, with both first- and final-dose coverage exceeding 70%. This suggests that higher women’s social participation is associated with more effective vaccine uptake. In several low-income countries within Africa (AFR) and the Eastern Mediterranean Region (EMR), FLFP generally fell below 40%, and vaccination coverage was markedly lower, in some cases below 20%. These disparities reflect both economic inequality and differences in women’s social status and cultural roles. Importantly, women’s labor force participation is not only an economic indicator but also reflects agency and decision-making power in family health matters, including vaccination (Alarcão & Zdravkova, 2022 ; Brotherton et al., 2022 ). A longitudinal analysis from 2013–2018 showed that countries with higher FLFP had more stable vaccination coverage, characterized by minimal annual fluctuations and more consistent program implementation. In countries with lower FLFP, vaccination rates fluctuated more widely, and program continuity was more vulnerable to external shocks, including economic downturns, limited health resources, and sociopolitical instability. These differences are often linked to cultural contexts where health decisions are dominated by men, limiting women’s influence in vaccination choices (Mengistie et al., 2025 ). Moreover, the association between FLFP and vaccination interacts with other structural determinants, including education, economic empowerment, women’s parliamentary representation, and gender norms, which together shape women’s access to health services. Existing evidence suggests that higher female labor force participation improves access to healthcare, enhances community awareness, and increases acceptance of vaccination programs, thereby facilitating HPV vaccine uptake (Gallagher et al., 2018 ; Mensch et al., 2019 ). The results indicate that FLFP is positively correlated with HPV vaccination coverage and shows regional differences in stability and fluctuation, highlighting its mediating role in vaccination equity. This effect cannot be attributed to a single economic variable but instead reflects a composite mechanism shaped by education, economic empowerment, and prevailing gender norms. FLFP reflects women’s status in employment and income generation, directly influencing their ability to pay for and access healthcare services. Higher levels of labor participation are also associated with stronger gender equality awareness and greater decision-making power in family health matters, which facilitate vaccine acceptance and implementation. FLFP further reflects governmental commitment to promoting women’s employment, safeguarding opportunities for social participation, and advancing gender equality (Fledderjohann & Channon, 2022 ; Limbu & Gautam, 2023 ). In summary, promoting women’s economic and social participation should be considered a long-term strategic goal for advancing global HPV vaccination equity. Indicators such as FLFP should be incorporated into monitoring and evaluation frameworks to sustainably increase vaccination coverage and reduce interregional disparities. 3.3.3 Structural association between female education level and HPV vaccination coverage Education level, a critical social determinant of public health interventions, has been extensively documented in infectious disease studies as strongly associated with vaccination coverage. Using global multi-regional data from 2013 to 2018, this study analyzed the structural association between female literacy rates and HPV vaccination coverage. Regression trends and regional differences were examined to highlight the role of education in promoting both vaccine initiation and full-course completion. Figures 6 A–F show that despite year-to-year fluctuations, literacy rates were positively associated with vaccine completion, with the strongest correlations in 2014, 2015, and 2018 ( Figs. 6 B, C, and E ). In the Americas and Europe, where female literacy rates were near 100%, HPV full-course vaccination rates remained stable at 60–80%. By comparison, in sub-Saharan Africa and the Eastern Mediterranean, where literacy rates were below 75%, completion rates were generally below 30% and in some countries approached zero. Figures 6 G–L illustrate the impact of literacy rates on first-dose initiation. Between 2014 and 2017 (Figs. 6 H–K), regression slopes were steeper and associations stronger, suggesting that education plays an especially important role in driving vaccine initiation. For every 10-percentage-point increase in literacy rate, initiation coverage increased markedly, indicating that education is a key determinant of vaccination willingness and acceptance (Cutts et al., 2016 ; Ekwunife & Lhachimi, 2017 ). These findings align with the “health literacy” theory, which holds that better-educated populations are more capable of understanding vaccine-related information, recognizing its benefits and risks, and therefore show greater willingness to initiate vaccination. However, this study revealed that the impact of education varies across economic and institutional contexts. In high-income countries, strong health systems and stable investment reinforce the positive effects of education on vaccination. In contrast, in low-income countries, even improvements in literacy do not translate into higher coverage when vaccine supply chains and policy implementation are weak (Restrepo-Mendez et al., 2016 ). A “literacy–vaccination mismatch” was also observed in certain regions, such as parts of the Western Pacific, where female literacy rates are relatively high but vaccination coverage remains low. This suggests that although education is necessary, its effect is constrained by religious and cultural norms, policy implementation, and healthcare resources (Cata-Preta et al., 2021 ; Denny, 2022 ). At the sociocultural level, education enhances women’s autonomy in health decision-making and promotes social participation. However, this effect is fully realized only when supported by institutions such as national immunization programs, financial subsidies, and community mobilization. Institutions not only directly determine vaccine accessibility but also mediate the combined influence of education and economic conditions, forming an interaction among economic, institutional, and sociocultural factors. According to social capital theory, better-educated women are more likely to act as health disseminators within families and communities, spreading vaccine-related knowledge and strengthening social mobilization. Therefore, improving female literacy should not be seen solely as an educational responsibility but must be integrated into public health strategies, supported by financial investment, institutional implementation, and community mobilization. In summary, female education is positively associated with HPV vaccination rates, with the strongest effect observed at the initiation stage. However, completion rates depend more heavily on institutional and social support. Future strategies for vaccine equity should integrate the “education–mobilization–implementation” chain into intervention pathways. In regions with low literacy rates, strengthening both basic education and health literacy will be essential to build the structural foundation for vaccination. Female literacy should also be incorporated as a key policy indicator to advance education-driven health equity. 3.4 Interactive effects of the composite structural inequality index on HPV vaccination and cervical cancer mortality To explore socioeconomic inequality in HPV vaccination and cervical cancer mortality, this study applied the Slope Index of Inequality (SII) to data from six WHO regions (2013–2018) and used the Ridit regression model to estimate SES gradients for first- and final-dose coverage ( Supplementary Fig. 1 , Fig. 11 ). The SII is a measure of absolute health inequality, with higher values indicating wider gaps between high- and low-SES groups. Higher values reflect wider gaps between high- and low-SES groups. SII was applied across socioeconomic, sociocultural, and policy dimensions to provide a comprehensive depiction of multilevel structural inequalities. Results showed a steady rise in inequality: the SII for first-dose vaccination increased from approximately 0.35 in 2013 to 0.71 in 2018, while the SII for final-dose vaccination rose from 0.37 to 0.59. These trends reflect widening gaps across economic, institutional, and sociocultural dimensions, highlighting persistent divergence in vaccine accessibility and intensifying structural inequalities. Notably, SII values were consistently higher for first-dose coverage than for full completion, highlighting dropout and discontinuity in vaccination pathways, which are disproportionately concentrated among low-SES populations. Socioculturally, SII revealed disparities in cultural trust, health literacy, and vaccination behavior, with high-SES groups benefiting disproportionately from mainstream health communication, whereas low-SES groups remained hindered by information gaps and distorted risk perceptions (Rivillas et al., 2020 ). The SII for cervical cancer mortality remained stable between − 0.19 and − 0.20, indicating a persistent excess disease burden among low-SES groups with no meaningful improvement over time. The regional hierarchy followed the pattern ‘Americas > Europe > Western Pacific > Eastern Mediterranean > Southeast Asia > Africa,’ underscoring the structural disadvantage of LMICs in achieving equitable vaccine coverage. At the policy-institutional level, SII illuminated disparities in NIP coverage, fiscal capacity, and frontline implementation. Although most LMICs have formally integrated HPV vaccination into NIPs, limited financial resources and fragile service delivery have hindered the translation of institutional accessibility into effective behavioral uptake (Rivillas et al., 2020 ; Wiseman et al., 2017 ). From a theoretical public health perspective, these findings corroborate the mechanistic pathways proposed by the Social Determinants of Health framework and the theory of Institutional Embeddedness of Inequality. Specifically, economic, institutional, and sociocultural factors interact within an institutionally mediated system, which can either amplify disparities or mitigate them through well-designed and effectively implemented policies (Gill & Benatar, 2017 ; Mulaga et al., 2022 ). The SII not only quantifies the socioeconomic gradients of vaccination and mortality but also explains how interactions among fiscal resources, institutional arrangements, and cultural factors generate a fractured fiscal–institution–behavior chain. Although most LMICs have integrated HPV vaccination into national immunization programs, constraints in fiscal capacity, service infrastructure, and community mobilization render vaccines institutionally accessible but practically unattainable at the implementation level. Information asymmetry, cultural barriers, and deficits in trust further exacerbate dropout and response obstacles among low-SES groups, reinforcing a fractured “fiscal-institution-behavior” chain (Bray et al., 2018 ; Guillaume et al., 2024 ). More critically, even where vaccination coverage has improved, disparities in cervical cancer mortality have persisted, indicating that current programs have not yet achieved high-quality coverage among vulnerable populations. This gap undermines population-level protection and may exacerbate existing inequalities through uneven intervention diffusion, leading to a structural amplification effect. The application of SII highlights both the socioeconomic gradients underlying vaccination behavior and health risks, and the deeper structural challenges constraining global HPV vaccine promotion. Future strategies for vaccine equity must proceed along three parallel tracks: sustained and stable financial support, precise and effective institutional pathways, and the systematic development of culturally sensitive and trust-building mechanisms. Such efforts are essential to move beyond “institutional equity” toward “substantive equity,” thereby advancing structural health justice on a global scale. 4. Conclusion This study used longitudinal data from six WHO regions (2013–2018) to establish a multidimensional framework linking vaccination coverage, health outcomes, and structural social determinants. Based on this framework, a ‘vaccination-health outcome-structural inequality’ three-pathway model was proposed. The results showed that although global HPV vaccination coverage increased, substantial gaps between first- and final-dose completion persisted in Africa, the Eastern Mediterranean, and South-East Asia, reflecting disparities in accessibility, continuity, and institutional capacity. Vaccination coverage was inversely associated with cervical cancer mortality, particularly in Europe and the Americas, indicating that public health benefits depend not only on overall coverage but also on equitable distribution and completion of vaccination schedules. Government health expenditure was consistently associated with higher vaccination rates, supporting the conclusion that fiscal investment is a key driver of equity. The structural inequality index developed in this study, which incorporated income stratification, NIP coverage, physician density, female parliamentary representation, and labor force participation, effectively explained regional disparities in both vaccination and cervical cancer mortality. Gender equality indicators were positively associated with vaccine uptake, providing further evidence that female empowerment improves access to and utilization of health resources. In summary, structural inequalities remain a major barrier to HPV vaccine scale-up and cervical cancer control. Addressing these disparities requires not only expanding resources but also implementing structural interventions, including targeted fiscal investment, institutional strengthening, and gender equity promotion. In addition, advancing cross-regional governance is essential to ensure sustainable and scalable responses. Future research should quantify the relative contributions of structural factors and assess multilevel strategies across diverse income settings to inform evidence-based and context-specific vaccination policies. Declarations Ethics Approval and Consent to Participate Not applicable. Clinical Trial Number Not applicable. Competing Interests The authors declare no competing interests. Funding This work was supported by the 2024 Beijing Routine Health Expenditure Accounting Based on SHA2011 (Grant No. BUCM-2025-KYJS-KYC-011) and the Scientific Research Project from Jiangsu Commission of Health (No. F202151). Author Contribution Siyan Liu: Investigation, writing – original draft. Xiaowei Man: Conceptualization, investigation, writing – original draft, writing – review and editing, supervision, project administration. Xingli Cao: Writing – review and editing. Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. References Acharya K, Dharel D, Subedi RK, Bhattarai A, Paudel YR. Inequalities in full vaccination coverage based on maternal education and wealth quintiles among children aged 12–23 months: further analysis of national cross-sectional surveys of six South Asian countries. BMJ Open. 2022;12(2):e046971. https://doi.org/10.1136/bmjopen-2020-046971 . Alarcão V, Zdravkova B. Attitudes and Practices towards HPV Vaccination and Its Social Processes in Europe: An Equity-Focused Scoping Review. Societies. 2022;12(5). https://doi.org/10.3390/soc12050131 . Ali HA, Hartner A-M, Echeverria-Londono S, Roth J, Li XM, Abbas K, Portnoy A, Vynnycky E, Woodruff K, Ferguson NM, Toor J, Gaythorpe KA. Vaccine equity in low and middle income countries: a systematic review and meta-analysis. Int J Equity Health. 2022;21(1):82. https://doi.org/10.1186/s12939-022-01678-5 . Araujo JFFE, Tejedo-Romero F. Women’s political representation and transparency in local governance. Local Government Stud. 2016;42(6):885–906. https://doi.org/10.1080/03003930.2016.1194266 . Arbyn M, Weiderpass E, Bruni E, de Sanjose S, Saraiya M, Ferlay J, Bray F. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. Lancet Global Health. 2020;8(2):e191–203. https://doi.org/10.1016/S2214-109X(19)30482-6 . Binagwaho A, Wagner CM, Gatera M, Karema C, Nutt CT, Ngabo F. Achieving high coverage in Rwanda's national human papillomavirus vaccination programme. Bull World Health Organ. 2012;90(8):623–8. https://doi.org/10.2471/BLT.11.097253 . Branda F, Pavia G, Ciccozzi A, Quirino A, Marascio N, Gigliotti S, Matera G, Romano C, Locci C, Azzena I, Pascale N, Sanna D, Casu M, Ceccarelli G, Ciccozzi M, Scarpa F. Human Papillomavirus (HPV) Vaccination: Progress, Challenges, and Future Directions in Global Immunization Strategies. Vaccines. 2024;12(11). https://doi.org/10.3390/vaccines12111293 . Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2018;68(6):394–424. https://doi.org/10.3322/caac.21492 . Brotherton J, Hendry A, Dey A, Hull BP, Beard F. HPV vaccination coverage: slightly improved two-dose schedule completion estimates and historical estimates lower on AIR than HPV Register. Aust N Z J Public Health. 2022;46(3):394–400. https://doi.org/10.1111/1753-6405.13233 . Bruni L, Diaz M, Barrionuevo-Rosas L, Herrero R, Bray F, Bosch FX, de Sanjose S, Castellsague X. Global estimates of human papillomavirus vaccination coverage by region and income level: a pooled analysis. Lancet Global Health. 2016;4(7):e453–463. https://doi.org/10.1016/S2214-109X(16)30099-7 . Bruni L, Saura-Lazaro A, Montoliu A, Brotons M, Alemany L, Diallo MS, Afsar OZ, LaMontagne DS, Mosina L, Contreras M, Velandia-Gonzalez M, Pastore R, Gacic-Dobo M, Bloem P. HPV vaccination introduction worldwide and WHO and UNICEF estimates of national HPV immunization coverage 2010–2019. Prev Med. 2021;144:106399. https://doi.org/10.1016/j.ypmed.2020.106399 . Budu E, Opoku Ahinkorah B, Okyere J, Seidu A-A, Ofori Duah H. Inequalities in the prevalence of full immunization coverage among one-year-olds in Ghana, 1993–2014. Vaccine. 2022;40(26):3614–20. https://doi.org/10.1016/j.vaccine.2022.04.081 . Cata-Preta BdO, Wehrmeister FC, Santos TM, Barros AJD, Victora CG. Patterns in Wealth-related Inequalities in 86 Low- and Middle-Income Countries: Global Evidence on the Emergence of Vaccine Hesitancy. Am J Prev Med. 2021;60(1 Suppl 1):S24–33. https://doi.org/10.1016/j.amepre.2020.07.028 . Cutts FT, Claquin P, Danovaro-Holliday MC, Rhoda DA. Monitoring vaccination coverage: Defining the role of surveys. Vaccine. 2016;34(35):4103–9. https://doi.org/10.1016/j.vaccine.2016.06.053 . Denny L. (2022). HPV vaccine introduction and implementation in Low- and Middle-Income Countries. Vaccine , 40 Suppl 1 , A1. https://doi.org/10.1016/j.vaccine.2022.02.074 Dorji T, Nopsopon T, Tamang ST, Pongpirul K. (2021). Human papillomavirus vaccination uptake in low-and middle-income countries: a meta-analysis. EClinicalMedicine , 34 , 100836. https://doi.org/10.1016/j.eclinm.2021.100836 Dube E, Laberge C, Guay M, Bramadat P, Roy RR, Bettinger JA. Vaccine hesitancy: an overview. Hum Vaccines Immunotherapeutics. 2013;9(8):1763–73. https://doi.org/10.4161/hv.24657 . Ekwunife OI, Lhachimi SK. Cost-effectiveness of Human Papilloma Virus (HPV) vaccination in Nigeria: a decision analysis using pragmatic parameter estimates for cost and programme coverage. BMC Health Serv Res. 2017;17(1):815. https://doi.org/10.1186/s12913-017-2758-2 . Fledderjohann J, Channon M. Gender, nutritional disparities, and child survival in Nepal. BMC Nutr. 2022;8(1):50. https://doi.org/10.1186/s40795-022-00543-6 . Gallagher KE, LaMontagne DS, Watson-Jones D. (2018). Status of HPV vaccine introduction and barriers to country uptake. Vaccine , 36 (32 Pt A), 4761–7. https://doi.org/10.1016/j.vaccine.2018.02.003 Garland SM. Population-level impact and herd effects following HPV vaccination programs: a global view. Pathology 51. 2019. https://doi.org/10.1016/j.pathol.2018.12.147 . Gill S, Benatar SR. History, Structure and Agency in Global Health Governance Comment on Global Health Governance Challenges 2016 - Are We Ready? Int J Health Policy Manage. 2017;6(4):237–41. https://doi.org/10.15171/ijhpm.2016.119 . Guillaume D, Waheed D-e-N, Schleiff M, Muralidharan KK, Vorsters A, Limaye RJ. Global perspectives of determinants influencing HPV vaccine introduction and scale-up in low- and middle-income countries. PLoS ONE. 2024;19(1):e0291990. https://doi.org/10.1371/journal.pone.0291990 . Habib RR, El-Harakeh A, Ziadee M, Abi Younes E, Asmar E, K. Social capital, social cohesion, and health of Syrian refugee working children living in informal tented settlements in Lebanon: A cross-sectional study. PLoS Med. 2020;17(9):e1003283. https://doi.org/10.1371/journal.pmed.1003283 . Han J, Zhang L, Chen Y, Zhang Y, Wang L, Cai R, Li M, Dai Y, Dang L, Chen H, Zhu L. (2025). Global HPV vaccination programs and coverage rates: a systematic review. EClinicalMedicine , 84 , 103290. https://doi.org/10.1016/j.eclinm.2025.103290 Jit M, Brisson M, Portnoy A, Hutubessy R. Cost-effectiveness of female human papillomavirus vaccination in 179 countries: a PRIME modelling study. Lancet Global Health. 2014;2(7):e406–414. https://doi.org/10.1016/S2214-109X(14)70237-2 . Kjaer SK, Dehlendorff C, Belmonte F, Baandrup L. Real-World Effectiveness of Human Papillomavirus Vaccination Against Cervical Cancer. J Natl Cancer Inst. 2021;113(10):1329–35. https://doi.org/10.1093/jnci/djab080 . Kruk ME, Gage AD, Arsenault C, Jordan K, Leslie HH, Roder-DeWan S, Adeyi O, Barker P, Daelmans B, Doubova SV, English M, Garcia-Elorrio E, Guanais F, Gureje O, Hirschhorn LR, Jiang L, Kelley E, Lemango ET, Liljestrand J, Pate M. High-quality health systems in the Sustainable Development Goals era: time for a revolution. Lancet Global Health Comm. 2018;6(11):e1196–252. https://doi.org/10.1016/S2214-109X(18)30386-3 . Larsson EC, Wittberg E, Lundasen SW. Variations in vaccination uptake: COVID-19 vaccination rates in Swedish municipalities. PLOS Global Public Health. 2022;2(10):e0001204. https://doi.org/10.1371/journal.pgph.0001204 . Limbu YB, Gautam RK. The determinants of COVID-19 vaccination intention: a meta-review. Front Public Health. 2023;11:1162861. https://doi.org/10.3389/fpubh.2023.1162861 . Lindstrom M. Psychosocial stress and social capital pathways and health: Perspectives from Lund University, Malmo. Scand J Public Health. 2022;50(7):864–72. https://doi.org/10.1177/14034948221075015 . Lupu D, Tiganasu R. COVID-19 vaccination and governance in the case of low, middle and high-income countries. BMC Public Health. 2023;23(1):1073. https://doi.org/10.1186/s12889-023-15975-3 . Luthra K, Zimmermann Jin A, Vasudevan P, Kirk K, Marzetta C, Privor-Dumm L. Assessing vaccine introduction and uptake timelines in Gavi-supported countries: are introduction timelines accelerating across vaccine delivery platforms? BMJ Global Health. 2021;6(5). https://doi.org/10.1136/bmjgh-2021-005032 . Machingaidze S, Wiysonge CS, Hussey GD. Strengthening the expanded programme on immunization in Africa: looking beyond 2015. PLoS Med. 2013;10(3):e1001405. https://doi.org/10.1371/journal.pmed.1001405 . Mackenbach JP. The persistence of health inequalities in modern welfare states: the explanation of a paradox. Soc Sci Med. 2012;75(4):761–9. https://doi.org/10.1016/j.socscimed.2012.02.031 . Macmillan R, Shofia N, Sigle W. Gender and the Politics of Death: Female Representation, Political and Developmental Context, and Population Health in a Cross-National Panel. Demography. 2018;55(5):1905–34. https://doi.org/10.1007/s13524-018-0697-0 . Malik S, Mock KO, Martillotti R, Caravella G, Zhou X, Mbamelu M, Scarbrough KH. HPV Vaccines Among University Students: Understanding Barriers and Facilitators of Vaccine Uptake. Vaccines. 2024;12(12). https://doi.org/10.3390/vaccines12121385 . Maness SB, Thompson EL. Social Determinants of Human Papillomavirus Vaccine Uptake: An Assessment of Publicly Available Data. Public Health Rep. 2019;134(3):264–73. https://doi.org/10.1177/0033354919838219 . Mengistie BA, Yirsaw AN, Lakew G, Mekonnen GB, Shibabaw AA, Chereka AA, Kitil GW, Wondie WT, Abuhay AE, Getachew E. Human papillomavirus vaccine uptake and its determinants among women in Africa: an umbrella review. Front Public Health. 2025;13:1537250. https://doi.org/10.3389/fpubh.2025.1537250 . Mensch BS, Chuang EK, Melnikas AJ, Psaki SR. Evidence for causal links between education and maternal and child health: systematic review. Trop Med Int Health. 2019;24(5):504–22. https://doi.org/10.1111/tmi.13218 . Mulaga AN, Kamndaya MS, Masangwi SJ. Decomposing socio-economic inequality in catastrophic out-of-pocket health expenditures in Malawi. PLOS Global Public Health. 2022;2(2):e0000182. https://doi.org/10.1371/journal.pgph.0000182 . Nguyen PT, Nakamura R, Shimadzu H, Abubakar AK, Le PM, Nguyen HV, Nguyen HL, Sato M, Honda A, Gilmour S. Progress and inequality in child immunization in 38 African countries, 2000–2030: A spatio-temporal Bayesian analysis at national and sub-national levels. PLoS Med. 2025;22(7):e1004664. https://doi.org/10.1371/journal.pmed.1004664 . Nova A, Fazia T, Bernardinelli L. Investigating mortality trends in Italy during the COVID-19 pandemic: life expectancy changes within provinces and vaccination campaign impact up to December 2022. Public Health. 2023;225:168–75. https://doi.org/10.1016/j.puhe.2023.09.031 . Onagoruwa A, Wodon Q. Child marriage, educational attainment, and comprehensive knowledge of HIV/AIDS: a multi-country analysis. J Biosoc Sci. 2025;57(1):96–111. https://doi.org/10.1017/S0021932024000397 . Ozawa S, Clark S, Portnoy A, Grewal S, Brenzel L, Walker DG. Return On Investment From Childhood Immunization In Low- And Middle-Income Countries, 2011-20. Health Aff. 2016;35(2):199–207. https://doi.org/10.1377/hlthaff.2015.1086 . Pozo-Martin F, Nove A, Lopes SC, Campbell J, Buchan J, Dussault G, Kunjumen T, Cometto G, Siyam A. Health workforce metrics pre- and post-2015: a stimulus to public policy and planning. Hum Resoures Health. 2017;15(1):14. https://doi.org/10.1186/s12960-017-0190-7 . Quamruzzaman A, Lange M. Female political representation and child health: Evidence from a multilevel analysis. Soc Sci Med. 2016. https://doi.org/10.1016/j.socscimed.2016.10.025 . Restrepo-Mendez MC, Barros AJ, Wong KL, Johnson HL, Pariyo G, Franca GV, Wehrmeiste FC, Victora CG. Inequalities in full immunization coverage: trends in low- and middle-income countries. Bull World Health Organ. 2016;94(11):794–B805. https://doi.org/10.2471/BLT.15.162172 . Rivillas JC, Devia-Rodriguez R, Ingabire M-G. Measuring socioeconomic and health financing inequality in maternal mortality in Colombia: a mixed methods approach. Intertional J Equity Health. 2020;19(1):98. https://doi.org/10.1186/s12939-020-01219-y . Rughinis C, Vulpe SN, Flaherty MG, Vasile S. Vaccination, life expectancy, and trust: patterns of COVID-19 and measles vaccination rates around the world. Public Health. 2022;210:114–22. https://doi.org/10.1016/j.puhe.2022.06.027 . Shato T, Humble S, Anandarajah A, Barnette A, Brandt HM, Garbutt J, Klesges L, Thompson VS, Silver MI. Influences of sociodemographic characteristics and parental HPV vaccination hesitancy on HPV vaccination coverage in five US states. Vaccine. 2023;41(25):3772–81. https://doi.org/10.1016/j.vaccine.2023.04.082 . Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. Cancer J Clin. 2021;71(3):209–49. https://doi.org/10.3322/caac.21660 . Van Minh H, My NTT, Jit M. Cervical cancer treatment costs and cost-effectiveness analysis of human papillomavirus vaccination in Vietnam: a PRIME modeling study. BMC Health Serv Res. 2017;17(1):353. https://doi.org/10.1186/s12913-017-2297-x . Wang Q, Leung K, Jit M, Wu JT, Lin L. Global socioeconomic inequalities in vaccination coverage, supply, and confidence. NPJ Vaccines. 2025;10(1):91. https://doi.org/10.1038/s41541-025-01143-8 . Westen EA, Bard E, Li D, Dye T, Whaley N, Seligman N. 746: Women’s representation in government as a predictor of women’s health outcomes. Am J Obstet Gynecol. 2019;220(1). https://doi.org/10.1016/j.ajog.2018.11.769 . Wigle J, Fontenot HB, Zimet GD. Global Delivery of Human Papillomavirus Vaccines. Pediatr Clin North Am. 2016;63(1):81–95. https://doi.org/10.1016/j.pcl.2015.08.004 . Wiseman V, Lagarde M, Batura N, Lin S, Irava W, Roberts G. Measuring inequalities in the distribution of the Fiji Health Workforce. Int J Equity Health. 2017;16(1):115. https://doi.org/10.1186/s12939-017-0575-1 . Xiong S, Humble S, Barnette A, Brandt H, Thompson V, Klesges LM, Silver MI. Associations of geographic-based socioeconomic factors and HPV vaccination among male and female children in five US states. BMC Public Health. 2024;24(1):702. https://doi.org/10.1186/s12889-024-18206-5 . Zhou L, Li Y, Wang H, Qin R, Han Z, Li R. Global cervical cancer elimination: quantifying the status, progress, and gaps. BMC Med. 2025;23(1):67. https://doi.org/10.1186/s12916-025-03897-3 . Additional Declarations No competing interests reported. Supplementary Files Supplementary826.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7654138","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":529896757,"identity":"1edd6f8a-a4c2-47fa-9d57-0933ea218037","order_by":0,"name":"Siyan Liu","email":"","orcid":"","institution":"Beijing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Siyan","middleName":"","lastName":"Liu","suffix":""},{"id":529896758,"identity":"0b88cb44-1deb-4bc9-bb0a-c79a098dab6d","order_by":1,"name":"Xiaowei 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19:13:16","extension":"xml","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":182714,"visible":true,"origin":"","legend":"","description":"","filename":"b56f5caf80e048dcbf832059500b48fe1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/567b27409860cade63b6151d.xml"},{"id":93715086,"identity":"50424459-0595-406e-af4a-661c1424b6ed","added_by":"auto","created_at":"2025-10-16 19:21:16","extension":"html","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":189801,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/0e26ee1ade8742f5d44c7ca3.html"},{"id":93714407,"identity":"54d193ea-4dff-48f6-a7d7-5a7a07b6378d","added_by":"auto","created_at":"2025-10-16 19:05:15","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":485717,"visible":true,"origin":"","legend":"\u003cp\u003eStructural health system factors and HPV vaccine coverage across WHO regions (2013-2018). A. Distribution of national income classifications (LIC, LMIC, UMIC, HIC) and corresponding HPV vaccine coverage by WHO region. B. National Immunization Program (NIP) inclusion rates and HPV vaccine coverage across WHO regions. C. Temporal trends in doctor-to-population ratio by WHO region from 2013 to 2018. D. Heatmap of doctor-to-population ratios (per 1,000 population) across WHO regions and years.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/05dd955f4a187ff042ae777c.jpeg"},{"id":93714410,"identity":"0509bdde-37da-42bc-8ae7-390a5f1c5c32","added_by":"auto","created_at":"2025-10-16 19:05:15","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":168647,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between female parliamentary representation and HPV vaccine coverage across WHO regions (2013-2018). A-F. Correlation between female parliament representation (%) and first-dose HPV vaccine coverage across WHO regions, from 2013 to 2018. G-L. Regional comparison of female parliament representation (%) vs. HPV first-dose coverage in 2018, with previous years’ coverage shown per panel (2013-2018).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/eb2f06d8184930f710c346bc.jpeg"},{"id":93715084,"identity":"d3df7272-30a4-471e-8d59-81d9f71c2270","added_by":"auto","created_at":"2025-10-16 19:21:15","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":562029,"visible":true,"origin":"","legend":"\u003cp\u003eStratified gaps in HPV vaccine coverage and health expenditure across WHO regions (2013-2018). A-F. Stratified gaps between HPV first-dose coverage and government health expenditure as a percentage of GDP (%GDP) across WHO regions from 2013 to 2018. G-L. Stratified gaps between HPV first-dose coverage and per capita health expenditure (USD) across WHO regions from 2013 to 2018.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/15c60f3f4f31d5b9746caa8c.jpeg"},{"id":93714414,"identity":"494c242e-41d1-4b9d-8466-015f8a00bdc9","added_by":"auto","created_at":"2025-10-16 19:05:15","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":907172,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of government health expenditure (% of GDP) and per capita health expenditure (US$) across WHO regions (2013-2018). A-F. Government health spending as a percentage of GDP (bar, left Y-axis) and per capita health expenditure in US dollars (line, right Y-axis) by WHO region for the years: A. 2013, B. 2014, C. 2015, D. 2016, E. 2017, F. 2018.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/96c2579e9f206335f3b1f8c7.jpeg"},{"id":93714883,"identity":"643d28a0-0eb8-48a9-afc2-1a19644b2734","added_by":"auto","created_at":"2025-10-16 19:13:15","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":664629,"visible":true,"origin":"","legend":"\u003cp\u003eStratified gaps between HPV first-dose coverage and health expenditure across WHO regions (2013-2018). A-F. Stratified gaps between female HPV first-dose vaccination coverage and domestic government health expenditure (% of GDP) across WHO regions:A. 2013, B. 2014, C. 2015, D. 2016, E. 2017, F. 2018.G-L. Stratified gaps between female HPV first-dose vaccination coverage and per capita domestic general government health expenditure (US$, current prices) across WHO regions:G. 2013, H. 2014, I. 2015, J. 2016, K. 2017, L. 2018.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/57e71481935ed7f736b91d15.jpeg"},{"id":93714885,"identity":"9f55a396-b2c9-4153-bf52-d7d4b0dcf9d5","added_by":"auto","created_at":"2025-10-16 19:13:15","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":713165,"visible":true,"origin":"","legend":"\u003cp\u003eGovernment health expenditure patterns across WHO regions from 2013 to 2018. A. 2013, B. 2014, C. 2015, D. 2016, E. 2017, F. 2018.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/850116a6e73c1f120b7dfdd9.jpeg"},{"id":93714412,"identity":"fbbaeab0-c6c6-4c06-88d8-7dc2c1c6d47c","added_by":"auto","created_at":"2025-10-16 19:05:15","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":480036,"visible":true,"origin":"","legend":"\u003cp\u003eTime-series trend graph of the first and last dose of HPV vaccine coverage from 2013 to 2018. A. First-dose HPV coverage (female); B.Final-dose HPV coverage (female); C. First-dose HPV coverage before age 15 (female); D.Final-dose HPV coverage before age 15 (female).\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/754c7d9d0d9cad8c19663a8e.jpeg"},{"id":93714415,"identity":"b8ccdabd-e1bf-4ccf-b5e8-536a167495af","added_by":"auto","created_at":"2025-10-16 19:05:15","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":857760,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between HPV vaccine coverage and cervical cancer mortality across WHO regions from 2013 to 2018. A-F. Scatter plots of first-dose HPV vaccine coverage versus age-standardized cervical cancer mortality rate (ASMR) among females in 2013 (A), 2014 (B), 2015 (C), 2016 (D), 2017 (E), and 2018 (F). G-L. Scatter plots of final-dose HPV vaccine coverage versus age-standardized cervical cancer mortality rate (ASMR) among females in 2013 (G), 2014 (H), 2015 (I), 2016 (J), 2017 (K), and 2018 (L).\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/433580ed330717aeab4a50cc.jpeg"},{"id":93714886,"identity":"d832be67-98b9-435f-a5c4-5eac76786f8e","added_by":"auto","created_at":"2025-10-16 19:13:15","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":827511,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between female labor force participation and HPV vaccine coverage across WHO regions (2013-2018).\u003cstrong\u003e \u003c/strong\u003eA-F. Relationship between female labor force participation rate and first-dose HPV vaccine coverage (female) from 2013 to 2018. G-L. Relationship between female labor force participation rate and final-dose HPV vaccine coverage (female) from 2013 to 2018.\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/167bbb8a3146369d50b19360.jpeg"},{"id":93714888,"identity":"7ea1cdc4-534c-4528-8f2a-94f0c3ceec67","added_by":"auto","created_at":"2025-10-16 19:13:15","extension":"jpeg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":165388,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between adult female literacy and HPV vaccine coverage across WHO regions (2013-2018). A-F. Correlation between adult female literacy rate (% of females aged 15 and above) and final-dose HPV vaccine coverage across WHO regions from 2013 to 2018. G-L. Correlation between adult female literacy rate (% of females aged 15 and above) and first-dose HPV vaccine coverage across WHO regions from 2013 to 2018.\u003c/p\u003e","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/0f6f1b8c321ae90f640d924f.jpeg"},{"id":93715458,"identity":"7bb15405-f2ba-4201-b861-75975c67131f","added_by":"auto","created_at":"2025-10-16 19:29:15","extension":"jpeg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":181210,"visible":true,"origin":"","legend":"\u003cp\u003eRidit regression analysis of socioeconomic inequalities in female HPV vaccine coverage across WHO regions (2013–2018). A-F. Ridit regression plots of female HPV first-dose coverage against SES-based Ridit scores across WHO regions:A. 2013, B. 2014, C. 2015, D. 2016, E. 2017, F. 2018. G-L. Ridit regression plots of female HPV final-dose coverage against SES-based Ridit scores across WHO regions: G. 2013, H. 2014, I. 2015, J. 2016, K. 2017, L. 2018.\u003c/p\u003e","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/fb7a0bc1ef4a4b3a2fbe7205.jpeg"},{"id":103904298,"identity":"50ad5227-1ff5-409e-b404-493524127f33","added_by":"auto","created_at":"2026-03-04 10:27:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7186831,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/91bc7fd8-34df-4e67-9a39-a728762e7141.pdf"},{"id":93714408,"identity":"81d77be0-add7-4f75-bad6-c3ca75eb5c14","added_by":"auto","created_at":"2025-10-16 19:05:15","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":125806,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary826.docx","url":"https://assets-eu.researchsquare.com/files/rs-7654138/v1/8e11b68fa3fb40d1a031633f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Structural Determinants of HPV Vaccination Inequalities: A Multiregional Analysis across Six WHO Regions","fulltext":[{"header":"1、Introduction","content":"\u003cp\u003eCervical cancer is a significant global public health burden, ranking as the fourth most prevalent malignancy among females. According to Global Cancer Statistics (GLOBOCAN 2020), approximately 604,000 new cases and 342,000 deaths occur annually, with more than 85% of these deaths concentrated in low- and middle-income countries (LMICs) (Sung et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This striking disparity underscores persistent structural inequities in healthcare access, screening coverage, and the delivery of preventive interventions. Robust screening systems and broad vaccine availability have markedly reduced cervical cancer incidence and mortality in high-resource settings. By contrast, LMICs continue to experience limited effectiveness due to inadequate healthcare resources, fragile infrastructures, and socioeconomic constraints (Xiong et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003cp\u003ePersistent infection with human papillomavirus (HPV) is the primary cause of cervical cancer, and prophylactic HPV vaccination is recognized as one of the most effective strategies for reducing both incidence and mortality. In 2020, the World Health Organization (WHO) introduced the \u0026ldquo;90-70-90\u0026rdquo; global targets for 2030: 90% of girls fully vaccinated with HPV by age 15, 70% of women screened with a high-performance test at ages 35 and 45, and 90% of diagnosed cases receiving appropriate treatment (Zhou et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, progress toward these targets has been markedly uneven worldwide. While many high-income countries have achieved or are approaching the expected coverage levels, vaccination rates in LMICs remain persistently low, reflecting structural health inequities in global vaccine access (Shato et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eStructural health inequalities are shaped by socioeconomic, sociocultural, and policy-related determinants, influencing prevention, diagnosis, and treatment pathways. Previous studies indicate that socioeconomic factors (e.g., national income level, public health expenditure), sociocultural factors (e.g., educational attainment, gender equity, labor force participation), and policy-related factors (e.g., physician density, immunization program coverage) are strongly associated with HPV vaccination coverage (Branda et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, most existing studies have focused on single regions or isolated determinants, with limited attempts to establish an integrated and multidimensional analytical framework at the global scale. Among the available metrics for assessing structural inequality, the Slope Index of Inequality (SII) quantifies socioeconomic and structural disparities as continuous measures, capturing gradients from the most disadvantaged to the most advantaged groups (Nguyen et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The SII facilitates both the evaluation of socioeconomic disparities in vaccination coverage and cross-regional as well as temporal comparisons of structural inequality trends. Accordingly, this study employs the SII as the central analytical tool to assess disparities across socioeconomic, sociocultural, and policy dimensions. By integrating these measures with vaccination coverage and cervical cancer mortality, we conduct a chain pathway analysis to systematically characterize global patterns of inequality (Acharya et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn addition, dynamic regional and temporal trends, as well as their long-term impact on vaccination disparities, remain insufficiently quantified, which has limited the development of targeted public health policies. Currently, systematic research assessing structural health inequalities and HPV vaccination gaps using multi-year global data remains scarce, particularly regarding comparative analyses across the six WHO regions, which encompass diverse socioeconomic, sociocultural, and policy contexts (Bruni et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, establishing a systematic indicator framework and applying statistical models that integrate the three dimensions with vaccination coverage and cervical cancer mortality within a unified causal chain analysis is essential. This approach enables the quantitative characterization of both the distribution and evolution of structural disparities, thereby clarifying global patterns and drivers of HPV vaccination inequality (Budu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo address these gaps, this study utilizes multidimensional global data from the six WHO regions (2013\u0026ndash;2018) to systematically assess the association between HPV vaccination coverage and cervical cancer mortality. It further quantifies the influence of socioeconomic, health system, and gender equality\u0026ndash;related factors on disparities in vaccine uptake. Unlikely prior studies that primarily examined single regions or limited variables, the present study provides broader coverage, a more comprehensive indicator framework, and comparative analytical approaches, thereby characterizing the mechanisms of structural health inequalities in HPV vaccine implementation from a global perspective. Furthermore, by incorporating quantitative indicators such as the SII, this study aims to generate context-specific policy recommendations for countries with varying resource settings, thereby supporting progress toward the WHO \u0026ldquo;90-70-90\u0026rdquo; targets.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data sources\u003c/h2\u003e\u003cp\u003eThis study employed secondary data from multiple countries between 2013 and 2018, obtained exclusively from internationally recognized databases. HPV vaccination coverage data (first- and final-dose rates) were extracted from the WHO/UNICEF Immunization Coverage Estimates (WUENIC) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://immunizationdata.who.int\u003c/span\u003e\u003cspan address=\"https://immunizationdata.who.int\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Cervical cancer age-standardized mortality rates (ASMRs) were sourced from the WHO Global Health Estimates (GHE) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/data/global-health-estimates\u003c/span\u003e\u003cspan address=\"https://www.who.int/data/global-health-estimates\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Socioeconomic indicators included GDP per capita, government health expenditure (expressed both as a share of GDP and per capita), and physician density (per 1,000 population), which were obtained from the World Bank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.worldbank.org\u003c/span\u003e\u003cspan address=\"https://data.worldbank.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Sociocultural indicators, including adult female literacy rate, female labor force participation rate, and the proportion of parliamentary seats held by women, were derived from the United Nations Development Programme (UNDP) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hdr.undp.org\u003c/span\u003e\u003cspan address=\"https://hdr.undp.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the World Bank. Policy-related indicators comprised HPV vaccination inclusion in national immunization programs (NIPs) and World Bank income classifications (low-income, lower-middle-income, upper-middle-income, and high-income), as reported by WHO and the World Bank.\u003c/p\u003e\u003cp\u003eAll datasets were harmonized at the country-year level using ISO3 country codes, and monetary indicators were standardized to current US dollars at prevailing annual exchange values. Countries were eligible for inclusion if they reported continuous HPV vaccination coverage and cervical cancer mortality data for 2013\u0026ndash;2018, along with complete structural social indicators. Nations with missing essential variables or extreme outliers were excluded from the analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Regional classification and sample structure\u003c/h2\u003e\u003cp\u003eAccording to the World Health Organization (WHO) classification, all countries were grouped into six regions: Africa (AFR), the Americas (AMR), South-East Asia (SEAR), Europe (EUR), the Eastern Mediterranean (EMR), and the Western Pacific (WPR). This generated a balanced panel dataset, with countries as the unit of analysis and structured by country\u0026ndash;year observations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Definition of indicators and variable construction\u003c/h2\u003e\u003cp\u003eHPV vaccination coverage: Coverage rates (%) for first- and final-dose HPV vaccination among females were defined as the primary independent variables. Health indicator: The age-standardized mortality rate (ASMR) of cervical cancer (per 100,000 population) was specified as the principal dependent variable. Structural social factors, encompassing socioeconomic, sociocultural, and policy dimensions, included indicators reflecting national resource allocation and gender disparities. These indicators comprised GDP per capita, government health expenditure (as % of GDP and per capita), physician density, adult female literacy rate, female labor force participation rate, proportion of parliamentary seats held by women, inclusion of HPV vaccination in national immunization programs (NIPs), and World Bank income classification.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical analysis methods\u003c/h2\u003e\u003cp\u003eTrend analysis: Temporal trends in HPV vaccination coverage and cervical cancer mortality across the six WHO regions from 2013 to 2018 were examined using time-series plots. Correlation analysis: Pearson correlation coefficients were calculated to evaluate linear associations between vaccination coverage and cervical cancer mortality. Regression modeling: Multivariate linear regression and generalized linear models (GLMs) were applied, with structural factors specified as explanatory variables and vaccination coverage or mortality as dependent outcomes. Year and regional fixed effects were included to isolate the independent effects of structural determinants.\u003c/p\u003e\u003cp\u003eTo quantitatively assess the inequality between HPV vaccination coverage and socioeconomic status (SES), this study introduced the SII.\u003c/p\u003e\u003cp\u003eSII is calculated based on the Ridit regression method. Countries are first ranked according to SES indicators (e.g., GDP per capita, educational attainment), then their cumulative population proportions are computed to generate Ridit scores (ranging from 0 to 1). HPV vaccination coverage is then regressed on Ridit values using weighted least squares. The model is expressed as:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Yi=\\alpha\\:+\\beta\\:Ri+ϵi$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:Yi\\)\u003c/span\u003e\u003c/span\u003e is the vaccination coverage of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:group\\:i\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:Ri\\)\u003c/span\u003e\u003c/span\u003e is the corresponding Ridit value, and β represents the SII, reflecting the absolute gap in coverage between the lowest and highest SES groups.\u003c/p\u003e\u003cp\u003eThis study captures the absolute gradient (SII) of HPV vaccination coverage across SES strata. This dual approach enables a more comprehensive understanding of how structural inequalities shape vaccination uptake, providing a robust quantitative framework for cross-regional comparisons and policy analysis.\u003c/p\u003e\u003cp\u003eIn this study, the Slope Index of Inequality (SII) was used to systematically quantify absolute disparities in HPV vaccination coverage attributable to three structural dimensions (socioeconomic, sociocultural, and policy) and was incorporated throughout all stages of the analysis. SII values for key indicators within each structural dimension (e.g., GDP per capita, female educational attainment, physician density) were calculated by ranking countries according to each factor and dividing them into deciles, thereby capturing within-dimension inequalities. Comparisons across dimensions were then conducted to assess the relative contributions of different structural domains, and temporal changes from 2013 to 2018 were analyzed to characterize the dynamic evolution of disparities. The relative rank (ridit score) was used as the independent variable, and vaccination coverage was specified as the dependent variable. Weighted linear regression models (weighted by national population) were fitted, and the regression coefficient was interpreted as the SII, representing the absolute disparity (percentage points) between the most disadvantaged and most advantaged groups.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Data processing and visualization\u003c/h2\u003e\u003cp\u003eAll data cleaning, statistical analyses, and figure preparation were conducted using standard software packages. SPSS 26.0 (IBM Corp., Armonk, NY, USA) was used to compute descriptive statistics, Pearson correlation coefficients, and significance tests, and to fit regression models; inequality metrics, including the Slope Index of Inequality (SII), were also derived in SPSS. Origin 2021 (Origin Lab Corp., Northampton, MA, USA) was used to fit trend lines, render correlation scatter plots, and display fitted linear regressions. Figures and final layouts were prepared in Adobe Illustrator 2022 (Adobe Inc., San Jose, CA, USA) to ensure publication-quality output and visual clarity. All graphical outputs, including time-series plots, correlation scatter plots with fitted lines, stratified bar charts of structural factors, and inequality index visualizations, were generated directly from the underlying statistical analyses to ensure scientific rigor and consistent visual presentation.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 The role of institutions and policies in vaccination equity\u003c/h2\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e3.1.1 Structural impacts of income level and national immunization program inclusion on HPV vaccination coverage\u003c/h2\u003e\u003cp\u003eGlobal disparities in HPV vaccination coverage are shaped not only by absolute economic differences but also by the broader influence of social determinants of health (SDH) on the effectiveness of public health interventions. Income level affects vaccination both directly, by determining affordability and supply chain capacity, and indirectly, through pathways such as educational attainment, information dissemination, healthcare resource distribution, and governance capacity (Maness \u0026amp; Thompson, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, high-income countries (HICs), primarily located in Europe, the Americas, and the Western Pacific, generally possess strong fiscal investment, robust cold-chain infrastructure, and mature primary healthcare networks, which together enable vaccination coverage to reach the vast majority of target populations. These countries typically exhibit high health literacy and low vaccine hesitancy, fostering a positive feedback loop in which policy initiatives and public acceptance reinforce each other (Dube et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).As a result, vaccination coverage has remained among the highest worldwide, exceeding 80% in some years. In contrast, low-income countries (LICs) and lower-middle-income countries (LMICs), concentrated in Africa and the Eastern Mediterranean, face constrained budgets, shortages of healthcare personnel, and underdeveloped transport and storage infrastructure (Gallagher et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These limitations undermine vaccine accessibility, timeliness, and affordability, resulting in persistently low coverage rates, often under 30%. Moreover, constrained economic conditions reduce institutional capacity and workforce effectiveness, limiting the reach and execution of immunization programs even when such frameworks are formally established (Bruni et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAgainst this backdrop, the inclusion of HPV vaccination in National Immunization Programs (NIPs) exerts a significant institutional effect. Theoretically, NIP inclusion reduces economic and informational barriers through government subsidies, centralized procurement, and standardized vaccination strategies, thereby increasing coverage (Bruni et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, countries incorporating HPV vaccination into NIPs consistently exhibit higher coverage rates than those without, with disparities reaching up to 40% in some regions. However, this institutional advantage is weaker in LMICs, where limited fiscal allocations, supply chain disruptions, weak primary healthcare implementation, and cultural or religious resistance to vaccination may in some cases offset the intended benefits of policy design. This observation is consistent with the Health System Building Blocks framework, which posits that policy effectiveness depends on coordinated functioning across multiple system components (Malik et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Taken together, these findings suggest that the combined effects of income level and NIP inclusion vary substantially across WHO regions. This trend is consistent with prior cross-national research, underscoring that the interplay between economic and institutional factors is a key driver of HPV vaccination coverage (Ozawa et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMultidimensional analysis revealed a significant interaction between income level and NIP inclusion in shaping HPV vaccination coverage. High-income countries with NIP integration achieved high coverage through a dual resource and institutional advantage, whereas low-income countries without NIP support fell into a low-coverage trap characterized by simultaneous deficits in funding and institutional capacity (Gallagher et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This cumulative effect underscores the need for a multidimensional strategy to reduce global HPV vaccination disparities: reinforcing financial and infrastructural capacity from the socioeconomic dimension, enhancing health education and public awareness from the sociocultural dimension, and strengthening immunization planning and implementation from the policy dimension (Wigle et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In low-income countries, breaking the cycle of low income, weak institutional support, and low vaccination coverage requires integrating international financial and technical assistance with education campaigns and culturally tailored interventions (Binagwaho et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e3.1.2 Structural relationship between women\u0026rsquo;s political representation and HPV vaccination coverage (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWomen\u0026rsquo;s representation in national parliaments reflects the broader gender-institutional environment of a country and is widely recognized as a critical political determinant of women\u0026rsquo;s health priorities (Quamruzzaman \u0026amp; Lange, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Using macro-level data from six WHO regions (2013\u0026ndash;2018), this study identified a significant structural gradient linking women\u0026rsquo;s parliamentary representation to HPV vaccination coverage, most pronounced in vaccination completion rates. As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;F, women\u0026rsquo;s parliamentary representation was consistently and positively associated with first-dose HPV vaccination coverage across all years. Marked regional disparities were observed. In Europe and the Americas, women\u0026rsquo;s parliamentary representation typically exceeded 25%, with first-dose HPV coverage generally ranging from 50% to 80%. By contrast, in Africa and the Eastern Mediterranean, women\u0026rsquo;s parliamentary representation was often below 20%, corresponding to vaccination rates typically under 30%, with some countries reporting persistently negligible coverage (near zero). Figures\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eG\u0026ndash;L further demonstrate the robustness and amplified effect of this relationship when examining full-course vaccination completion (final-dose coverage). Compared with first-dose coverage, final-dose completion is a more sensitive indicator of the sustained implementation capacity of health systems and the degree of public trust. In countries with stronger institutional representation of women, vaccination completion rates consistently remained at moderate to high levels. Conversely, in regions with limited female political representation, HPV vaccination completion rates remained substantially lower, even when included in NIPs, due to weak implementation capacity and fragile grassroots mobilization structures, resulting in a pronounced policy\u0026ndash;coverage gap (Macmillan et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMechanistically, women\u0026rsquo;s parliamentary representation, an institutional marker of gender empowerment, exerts system-level influence on vaccination uptake through multiple pathways. At the institutional level, female legislators are more likely to champion women\u0026rsquo;s and children\u0026rsquo;s health agendas, including cervical cancer prevention, sexual health education, and budgetary commitments for vaccination programs (Wigle et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). From an economic\u0026ndash;institutional perspective, they tend to steer budget allocations and resource priorities toward women\u0026rsquo;s health, thereby improving vaccine accessibility and affordability. At the sociocultural level, women legislators can reshape public discourse, reduce cultural resistance and stigma surrounding HPV vaccination, and enhance public acceptance (Araujo \u0026amp; Tejedo-Romero, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNotably, institutional gender empowerment plays a significant moderating role in shaping the effects of economic and sociocultural factors. High levels of women\u0026rsquo;s institutional participation amplify the positive effects of financial investment and cultural support on vaccination coverage, whereas low participation constrains coverage even under favorable economic conditions or high cultural acceptance. This moderating mechanism forms an institution\u0026ndash;economic\u0026ndash;sociocultural triadic loop, elucidating the institutional roots of vaccination disparities among countries with otherwise comparable economic conditions. Moreover, as a structural marker of gender empowerment, women\u0026rsquo;s parliamentary representation advances cervical cancer prevention, sexual health education, and vaccine financing, and supports budget allocations, legislative priorities, and accountability mechanisms that favor women\u0026rsquo;s health, thereby improving the accessibility, acceptability, and cultural alignment of HPV vaccination (Mackenbach, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These structural associations are consistent with the Health Opportunity Structure framework, which posits that institutional gender empowerment shapes which health issues are prioritized on policy agendas, how they are implemented, and whether health services are effectively absorbed and utilized by society (Ozawa et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The stable positive associations identified in this study indicate that gender\u0026ndash;institutional environments shape not only the design of vaccination policies but also the micro-level mechanisms through which these policies are socially enacted.\u003c/p\u003e\u003cp\u003eTime-series analysis revealed no significant convergence of this structural gradient over the six-year period, indicating strong path dependence in gender\u0026ndash;institutional inequalities and suggesting that short-term policy interventions are unlikely to reverse these patterns (Ali et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In several lower-middle-income countries, despite the inclusion of HPV vaccination in NIPs, the persistent lack of women\u0026rsquo;s political representation has deprived programs of institutional backing and social consensus, thereby constraining improvements in coverage. Notably, several outliers were identified; for example, in some Western Pacific countries, relatively high women\u0026rsquo;s parliamentary representation coincided with persistently low vaccination rates, highlighting that although gender empowerment is a critical antecedent, it is not the sole determinant of vaccine equity. Other factors, including cultural beliefs, community mobilization, health system capacity, and educational attainment, function as critical synergistic mechanisms influencing vaccination coverage and should be incorporated into comprehensive analytical models (Westen et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn summary, institutional gender empowerment emerges as a pivotal factor shaping HPV vaccine equity, with a significant moderating influence on economic and sociocultural determinants. Future public health strategies should systematically integrate this indicator into the design of multidimensional, structurally oriented vaccination policies, thereby advancing the dual goals of gender justice and health equity.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Economic resource allocation and healthcare accessibility\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1 Potential impact of physician density on HPV vaccination Coverage\u003c/h2\u003e\u003cp\u003ePhysician density, a critical structural marker of health system capacity, is widely recognized as a key mediating factor linking vaccination coverage potential to health equity. Using WHO regional data from 2013 to 2018, we analyzed temporal trends in physician density (per 1,000 population) and examined its association with first-dose HPV vaccination coverage.\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, global physician density exhibited pronounced geographic disparities. Since 2013, Europe and the Americas have maintained relatively high levels (\u0026gt;\u0026thinsp;3.5 and \u0026gt;\u0026thinsp;2.0 per 1,000, respectively), whereas Africa and Southeast Asia have remained below 1.0 per 1,000, with negligible growth. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, presented as a physician-to-population heatmap, further demonstrates the persistence and structural rigidity of these regional disparities. In Africa and the Eastern Mediterranean, physician density improved only marginally despite increased global health investments from 2013 to 2018, underscoring the fragility and persistent lag of primary healthcare infrastructure. In line with World Bank and WHO minimum thresholds for essential healthcare workforce density (1.0\u0026ndash;1.5 per 1,000), Africa and Southeast Asia have persistently remained at levels of severe medical resource scarcity, marking them as prototypical zones of systemic healthcare disadvantage. From the perspective of HPV vaccination, such structural disparities critically constrain both initiation and completion of vaccination. Within the framework of healthcare accessibility, physician workforce determines the physical feasibility of supply-side provision and indirectly shapes public willingness and trust in vaccination by influencing health education, program organization, cold-chain logistics, and adverse event management. Physician shortages compromise not only service availability but also critical dimensions such as acceptability and appropriateness of care (Pozo-Martin et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study identified a stable social gradient between physician density and HPV vaccination coverage. High-density regions (e.g., Europe and the Americas) maintained consistently higher HPV coverage with steady annual gains, whereas resource-limited regions (e.g., Africa and the Eastern Mediterranean) exhibited a vaccine deprivation phenomenon, where NIP inclusion failed to translate into operational coverage due to inadequate medical staffing (Habib et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lindstrom, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This structural shortfall is consistent with Kawachi\u0026rsquo;s opportunity structure theory, underscoring that healthcare workforce is a foundational prerequisite, rather than a peripheral factor, for achieving vaccination equity. Although derived from ecological, region-level data and subject to potential confounding, our findings provide structural evidence that strengthening physician supply can enhance vaccination equity. Prior research has also shown that physician density is positively associated with childhood vaccination rates (e.g., DTP, MMR) across diverse national models, with effects particularly pronounced in LMICs (Kruk et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn summary, physician density reflects disparities in healthcare investment and resource allocation, shapes health literacy and vaccine acceptance, and indicates the strength of primary healthcare networks and immunization program implementation. The significant structural inequality linking physician density to HPV vaccination coverage underscores that global cervical cancer control strategies must go beyond vaccine supply and policy frameworks. Strengthening and optimizing the healthcare workforce is essential to ensure the efficient and equitable translation of vaccination policies into actual uptake.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.2.2 Structural gaps between health expenditure and HPV vaccination coverage\u003c/h2\u003e\u003cp\u003eNational fiscal capacity and patterns of health expenditure are critical structural determinants of vaccination equity in the advancement of global HPV vaccine coverage (Machingaidze et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e7\u003c/span\u003eA\u0026ndash;F, HPV vaccination rates (first and final doses) show clear stratification according to the share of government health expenditure in GDP. In high-income regions such as Europe and the Americas, health spending typically exceeded 8% of GDP, with vaccination coverage maintained at 60\u0026ndash;80%. By contrast, Africa and the Eastern Mediterranean allocated less than 5% of GDP to health, with vaccination coverage typically below 30% and in some cases near zero. This trend underscores a positive association between fiscal capacity and vaccination performance (Lupu \u0026amp; Tiganasu, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As further shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e7\u003c/span\u003eG\u0026ndash;L, per capita health expenditure exceeded USD 500 in the Americas and Europe, where vaccination coverage was sustained at relatively high levels. In contrast, regions with per capita spending below USD 200 exhibited markedly low vaccination coverage, reflecting a structural disconnect between limited fiscal support and weak immunization capacity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e8\u003c/span\u003e presents a cross-sectional view of 2020 fiscal structures, with dual axes illustrating the alignment between government health expenditure (% of GDP) and per capita spending. Results indicate that European and American countries clustered in the upper-right quadrant, characterized by high-intensity investment and high resource density, representing an ideal fiscal structure of high spending and high coverage. Conversely, African and Eastern Mediterranean countries clustered in the lower-left quadrant, where fragile fiscal foundations limited institutional conditions for vaccine accessibility. This structural disconnect between fiscal capacity and vaccination uptake may underlie persistent barriers to improving coverage.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eImportantly, absolute fiscal expenditure alone does not fully explain variation in vaccination rates. Several upper-middle-income countries had adequate fiscal resources but still exhibited low vaccination rates, suggesting that the effective translation of spending depends on institutional efficiency, governance capacity, and social mobilization (Kruk et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rughinis et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the context of widespread vaccine hesitancy, fiscal investment alone cannot achieve substantial improvements in coverage; instead, the interplay of fiscal capacity, institutional performance, and public trust must be jointly addressed (Lupu \u0026amp; Tiganasu, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Taken together, these results indicate that fiscal capacity, institutional effectiveness, and sociocultural trust form an interdependent mechanism shaping HPV vaccination coverage, with institutional effectiveness serving as the critical mediator linking economic foundations to social acceptance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.2.3 Fiscal\u0026ndash;Behavioral mismatch: structural gaps between government health expenditure and HPV vaccination coverage\u003c/h2\u003e\u003cp\u003eIn analyzing the structural drivers of HPV vaccination inequities, the conversion efficiency between fiscal expenditure and vaccination uptake is a critical measure of public health system performance. Figures\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e9\u003c/span\u003e and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e10\u003c/span\u003e illustrate the structural gaps observed from 2013 to 2018 between government health expenditure, expressed both as a share of GDP and as per capita spending, and first-dose HPV vaccination coverage, underscoring the pronounced disconnect between fiscal capacity and vaccination performance.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAs shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e9\u003c/span\u003eA\u0026ndash;F, discrepancies between first-dose coverage and health expenditure as a share of GDP reveal imbalances in fiscal allocation and behavioral response across regions. Europe and the Americas maintained high fiscal shares but lagging vaccination performance, whereas Africa and the Eastern Mediterranean faced a double disadvantage of limited resources and weak institutional execution, reflecting compounded structural constraints (Wang et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Notably, in the Americas (e.g., 2015\u0026ndash;2016), a high-spending but moderate-coverage pattern was observed, underscoring the limited translation of fiscal input into vaccination uptake. Figures\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e9\u003c/span\u003eG\u0026ndash;L further illustrate structural deviations between per capita government spending and first-dose coverage. In regions such as the Eastern Mediterranean and Africa, per capita spending rose but coverage remained low, reflecting a mismatch of increasing spending without corresponding uptake. By contrast, Europe exhibited a favorable fiscal-vaccination alignment, indicative of strong institutional efficiency and social mobilization (Larsson et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e10\u003c/span\u003e presents fiscal\u0026ndash;behavioral decoupling risk in a bivariate plot, with first-dose coverage on the x-axis, expenditure intensity (GDP share or per capita) on the y-axis, and point size representing structural disparities. Distributional patterns show Europe and parts of the Western Pacific clustered in the high-spending\u0026ndash;high-coverage quadrant, reflecting positive fiscal\u0026ndash;behavioral alignment, while the Eastern Mediterranean and Africa remained concentrated in the low-spending\u0026ndash;low-coverage quadrant, entrenched in compounded structural disadvantage. Several upper-middle-income countries, despite strong fiscal capacity, lagged in vaccination uptake, suggesting that sociocultural barriers such as limited cultural acceptance and trust deficits in institutional implementation, policy transmission, or social mobilization may play a role (Nova et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOverall, vaccination uptake is not a linear outcome of fiscal investment but the result of complex interactions among economic capacity, institutional effectiveness, and sociocultural context, with institutions serving as the key mediator linking resources to behavioral outcomes. While fiscal spending provides the material foundation for vaccine delivery, its effectiveness depends on operational feasibility, policy implementation, and public trust. In the absence of cultural adaptation and effective health communication, even abundant resources may result in a high-investment but low-uptake mismatch. Achieving structural health equity therefore requires a tripartite framework of fiscal investment, institutional safeguards, and social mobilization. Within this framework, institutions regulate both economic allocation and cultural alignment to enhance policy translation, ensure sustainability, and reduce vaccination disparities across regions and populations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.2.4 Temporal trends in regional HPV vaccination coverage\u003c/h2\u003e\u003cp\u003eHPV vaccination coverage has exhibited substantial regional variation and uneven progress over time. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates temporal trends in HPV vaccination coverage across the six WHO regions, with four indicators: overall first-dose coverage (A), overall final-dose coverage (B), first-dose coverage before age 15 (C), and final-dose coverage before age 15 (D). The results indicate pronounced regional disparities and persistent structural inequalities.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor overall first-dose coverage (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), the Americas maintained the highest levels, rising from 38.2% in 2013 to 65.9% in 2018, an increase of about 28% over six years. By contrast, Africa and Southeast Asia showed limited improvement, reaching 18.0% and 7.3% in 2018, respectively. The Eastern Mediterranean remained below 5% throughout the study period, indicating persistently low coverage. The Western Pacific and Europe showed intermediate levels, with 2018 rates of 7.2% and 30.1%, respectively, but growth remained relatively slow. Trends in overall final-dose coverage (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) were similar but exhibited even greater regional contrasts. In 2018, the Americas reached 53.9%, representing an increase of 25 percentage points from 28.9% in 2013. Final-dose coverage in Africa and Southeast Asia remained below 10% in 2018, underscoring greater barriers to completing the vaccination schedule. In the Eastern Mediterranean, coverage remained below 3% for six consecutive years, indicating an absence of systematic vaccine rollout and highlighting the need for targeted public health interventions (Bruni et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Regional disparities were more pronounced for vaccination before age 15 \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u0026ndash;D). By 2018, the Americas achieved 70% for the first dose and 56% for the final dose, indicating strong prioritization of children and adolescents. In contrast, final-dose coverage before age 15 remained below 30% in all other regions, with the Eastern Mediterranean and Southeast Asia remaining below 5%, well below the WHO target of full vaccination before age 15 (Dorji et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBetween 2013 and 2018, HPV vaccination patterns across the six WHO regions remained highly divergent, with no evidence of convergence, indicating the persistence of global structural vaccine inequality. Disparities extended beyond baseline coverage to completion rates and early-age vaccination. From a socioeconomic perspective, the Americas, with higher GDP per capita and health expenditure, maintained stable support for vaccine procurement and delivery, whereas SII results indicated that economic disparities in low-income regions amplified inequities. In the sociocultural dimension, regions with higher female education and labor participation (e.g., the Americas and Europe) consistently achieved higher coverage, whereas areas with limited education showed deficits in awareness and vaccine uptake. Institutionally, comprehensive NIP inclusion and higher physician density facilitated improvements, whereas weak health systems in the Eastern Mediterranean and Africa imposed major constraints. Notably, vaccination rates in the Americas plateaued after 2014, indicating system maturity, whereas most low- and middle-income regions remained at early stages of system development, hindered by slow policy progress, resource shortages, and limited public awareness (Han et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Luthra et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese findings align with global health equity theory, which posits that under resource scarcity, preventive interventions such as vaccines concentrate in regions with stronger institutions and fiscal capacity, thereby widening initial disparities. Consistent with the framework of social determinants of health, uneven distribution of economic resources, education, and health system coverage entrenches inequities by shaping accessibility, affordability, and willingness to vaccinate (Onagoruwa \u0026amp; Wodon, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Thus, the observed temporal patterns highlight both disparities in coverage and the structural interplay between health governance and social stratification. Future strategies for vaccine equity should adopt stratified, targeted, and structurally informed approaches to reduce disparities and promote more equitable global coverage.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Cultural and social factors: cognition, gender, and collective behavior\u003c/h2\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 Association Between Vaccination Coverage and Cervical Cancer Mortality\u003c/h2\u003e\u003cp\u003eThis study systematically analyzed data from the six WHO regions to evaluate the impact of HPV vaccination on cervical cancer, focusing on the associations of first-dose coverage, final-dose coverage, and completion rates with cervical cancer mortality \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u0026ndash;c). The results indicated a consistent global pattern: vaccination coverage was inversely correlated with cervical cancer mortality, with the strongest association observed for full-course completion. These findings demonstrate that unequal vaccination coverage is a critical driver of global disparities in women\u0026rsquo;s health.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e2\u003c/span\u003ea shows the association between first-dose coverage and cervical cancer mortality across regions. In the Americas (AMR) and Europe (EUR), first-dose coverage reached 68.5% and 59.2%, with corresponding mortality rates of 6.8 and 5.1 per 100,000, substantially lower than in other regions. By contrast, Africa (AFR) and the Eastern Mediterranean (EMR) recorded substantially lower first-dose coverage (13.2% and 18.7%) and the highest mortality rates (22.4 and 17.1 per 100,000). Southeast Asia (SEAR) showed moderate coverage (32.5%), but mortality remained high at 15.2 per 100,000. These results suggest that first-dose uptake alone is insufficient to provide effective immune protection. This aligns with the herd immunity threshold mechanism, which requires coverage above approximately 70% to establish a protective barrier against persistent HPV transmission and reinfection. Regions falling short of this threshold, even with vaccination programs in place, experience limited reductions in mortality (Arbyn et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bruni et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e2\u003c/span\u003eb demonstrates an even stronger negative correlation between final-dose coverage and mortality. The Americas reported the highest completion rate (62.4%) with mortality reduced to 6.5 per 100,000, whereas Europe achieved 54.7% completion with mortality at 5.3 per 100,000. Africa had the lowest completion rate (8.7%) and the highest mortality (23.2 per 100,000). The Pearson correlation between completion rate and mortality was \u0026minus;\u0026thinsp;0.72 \u003cem\u003e(P\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e), the strongest among all vaccination indicators. This finding underscores the critical importance of full-course vaccination, as first-dose initiation alone cannot substantially reduce cervical cancer mortality. The findings reflect the \u0026ldquo;full immunization protection mechanism,\u0026rdquo; whereby multiple doses are required to elicit durable and high-titer neutralizing antibody responses. Only through full completion can maximal individual protection be achieved, translating into substantial reductions in cervical cancer incidence and mortality at the population level (Kjaer et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e2\u003c/span\u003ec presents a comprehensive analysis of completion rates in relation to cervical cancer mortality. Cross-sectional regression indicated that each 10-percentage-point increase in completion was associated with an average decline of 2.1 per 100,000 in mortality. Regions with higher baseline mortality, such as EMR and SEAR, derived greater reductions from increased vaccine coverage, indicating higher marginal health benefits in high-burden settings. This structural disparity reflects how uneven resource allocation and health system capacity amplify the effects of vaccination gaps. The findings align with the \u0026ldquo;marginal health benefit mechanism,\u0026rdquo; whereby additional coverage in high-burden regions prevents disproportionately more cases and deaths and yields greater health returns per unit of vaccine investment, such as larger reductions in DALYs and life-years gained, compared with low-burden settings (Garland, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jit et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFrom a socioeconomic perspective, high-income regions with substantial health investment are better positioned to achieve broad and sustained vaccination coverage, whereas low-income regions experience persistent delays due to limited financial capacity. Sociocultural factors also play a critical role: populations with higher levels of education and stronger health awareness demonstrate greater acceptance of vaccination, while insufficient awareness in some cultural contexts continues to hinder uptake. At the institutional level, countries with comprehensive immunization programs, financial subsidies, and well-established primary health systems show faster progress in improving coverage, whereas weak policy frameworks limit the ability to ensure full completion (Van Minh et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn summary, HPV vaccination coverage is strongly and inversely associated with cervical cancer mortality, with completion rate emerging as the most reliable predictor of mortality reduction. Together, these findings underscore the central role of HPV vaccination in public health interventions and provide robust evidence to guide global vaccination strategies. In low- and middle-income countries, policies should shift their focus from initiation to completion, ensuring continuity across the vaccination pathway. Such a shift is essential to maximize the vaccine\u0026rsquo;s impact on reducing cervical cancer mortality and to advance the broader goal of global health equity for women.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 Potential impact of Female Labor Force Participation on HPV Vaccination Coverage\u003c/h2\u003e\u003cp\u003eThis study examined the relationship between female labor force participation rate (FLFP) and HPV vaccination coverage (first- and final-dose) across the six WHO regions from 2013 to 2018, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003e. FLFP demonstrated a positive correlation with vaccination coverage, particularly in Europe (EUR), the Americas (AMR), and the Western Pacific Region (WPR).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn EUR and AMR, most countries maintained FLFP levels between 55% and 65%. During the same period, HPV vaccination rates were consistently high, with both first- and final-dose coverage exceeding 70%. This suggests that higher women\u0026rsquo;s social participation is associated with more effective vaccine uptake. In several low-income countries within Africa (AFR) and the Eastern Mediterranean Region (EMR), FLFP generally fell below 40%, and vaccination coverage was markedly lower, in some cases below 20%. These disparities reflect both economic inequality and differences in women\u0026rsquo;s social status and cultural roles. Importantly, women\u0026rsquo;s labor force participation is not only an economic indicator but also reflects agency and decision-making power in family health matters, including vaccination (Alarc\u0026atilde;o \u0026amp; Zdravkova, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Brotherton et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA longitudinal analysis from 2013\u0026ndash;2018 showed that countries with higher FLFP had more stable vaccination coverage, characterized by minimal annual fluctuations and more consistent program implementation. In countries with lower FLFP, vaccination rates fluctuated more widely, and program continuity was more vulnerable to external shocks, including economic downturns, limited health resources, and sociopolitical instability. These differences are often linked to cultural contexts where health decisions are dominated by men, limiting women\u0026rsquo;s influence in vaccination choices (Mengistie et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Moreover, the association between FLFP and vaccination interacts with other structural determinants, including education, economic empowerment, women\u0026rsquo;s parliamentary representation, and gender norms, which together shape women\u0026rsquo;s access to health services. Existing evidence suggests that higher female labor force participation improves access to healthcare, enhances community awareness, and increases acceptance of vaccination programs, thereby facilitating HPV vaccine uptake (Gallagher et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mensch et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results indicate that FLFP is positively correlated with HPV vaccination coverage and shows regional differences in stability and fluctuation, highlighting its mediating role in vaccination equity. This effect cannot be attributed to a single economic variable but instead reflects a composite mechanism shaped by education, economic empowerment, and prevailing gender norms. FLFP reflects women\u0026rsquo;s status in employment and income generation, directly influencing their ability to pay for and access healthcare services. Higher levels of labor participation are also associated with stronger gender equality awareness and greater decision-making power in family health matters, which facilitate vaccine acceptance and implementation. FLFP further reflects governmental commitment to promoting women\u0026rsquo;s employment, safeguarding opportunities for social participation, and advancing gender equality (Fledderjohann \u0026amp; Channon, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Limbu \u0026amp; Gautam, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn summary, promoting women\u0026rsquo;s economic and social participation should be considered a long-term strategic goal for advancing global HPV vaccination equity. Indicators such as FLFP should be incorporated into monitoring and evaluation frameworks to sustainably increase vaccination coverage and reduce interregional disparities.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3 Structural association between female education level and HPV vaccination coverage\u003c/h2\u003e\u003cp\u003eEducation level, a critical social determinant of public health interventions, has been extensively documented in infectious disease studies as strongly associated with vaccination coverage. Using global multi-regional data from 2013 to 2018, this study analyzed the structural association between female literacy rates and HPV vaccination coverage. Regression trends and regional differences were examined to highlight the role of education in promoting both vaccine initiation and full-course completion. Figures\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eA\u0026ndash;F show that despite year-to-year fluctuations, literacy rates were positively associated with vaccine completion, with the strongest correlations in 2014, 2015, and 2018 \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eB, C, \u003cb\u003eand E\u003c/b\u003e). In the Americas and Europe, where female literacy rates were near 100%, HPV full-course vaccination rates remained stable at 60\u0026ndash;80%. By comparison, in sub-Saharan Africa and the Eastern Mediterranean, where literacy rates were below 75%, completion rates were generally below 30% and in some countries approached zero. Figures\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eG\u0026ndash;L illustrate the impact of literacy rates on first-dose initiation. Between 2014 and 2017 (Figs.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eH\u0026ndash;K), regression slopes were steeper and associations stronger, suggesting that education plays an especially important role in driving vaccine initiation. For every 10-percentage-point increase in literacy rate, initiation coverage increased markedly, indicating that education is a key determinant of vaccination willingness and acceptance (Cutts et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Ekwunife \u0026amp; Lhachimi, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese findings align with the \u0026ldquo;health literacy\u0026rdquo; theory, which holds that better-educated populations are more capable of understanding vaccine-related information, recognizing its benefits and risks, and therefore show greater willingness to initiate vaccination. However, this study revealed that the impact of education varies across economic and institutional contexts. In high-income countries, strong health systems and stable investment reinforce the positive effects of education on vaccination. In contrast, in low-income countries, even improvements in literacy do not translate into higher coverage when vaccine supply chains and policy implementation are weak (Restrepo-Mendez et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA \u0026ldquo;literacy\u0026ndash;vaccination mismatch\u0026rdquo; was also observed in certain regions, such as parts of the Western Pacific, where female literacy rates are relatively high but vaccination coverage remains low. This suggests that although education is necessary, its effect is constrained by religious and cultural norms, policy implementation, and healthcare resources (Cata-Preta et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Denny, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). At the sociocultural level, education enhances women\u0026rsquo;s autonomy in health decision-making and promotes social participation. However, this effect is fully realized only when supported by institutions such as national immunization programs, financial subsidies, and community mobilization. Institutions not only directly determine vaccine accessibility but also mediate the combined influence of education and economic conditions, forming an interaction among economic, institutional, and sociocultural factors. According to social capital theory, better-educated women are more likely to act as health disseminators within families and communities, spreading vaccine-related knowledge and strengthening social mobilization. Therefore, improving female literacy should not be seen solely as an educational responsibility but must be integrated into public health strategies, supported by financial investment, institutional implementation, and community mobilization.\u003c/p\u003e\u003cp\u003eIn summary, female education is positively associated with HPV vaccination rates, with the strongest effect observed at the initiation stage. However, completion rates depend more heavily on institutional and social support. Future strategies for vaccine equity should integrate the \u0026ldquo;education\u0026ndash;mobilization\u0026ndash;implementation\u0026rdquo; chain into intervention pathways. In regions with low literacy rates, strengthening both basic education and health literacy will be essential to build the structural foundation for vaccination. Female literacy should also be incorporated as a key policy indicator to advance education-driven health equity.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Interactive effects of the composite structural inequality index on HPV vaccination and cervical cancer mortality\u003c/h2\u003e\u003cp\u003eTo explore socioeconomic inequality in HPV vaccination and cervical cancer mortality, this study applied the Slope Index of Inequality (SII) to data from six WHO regions (2013\u0026ndash;2018) and used the Ridit regression model to estimate SES gradients for first- and final-dose coverage (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). The SII is a measure of absolute health inequality, with higher values indicating wider gaps between high- and low-SES groups. Higher values reflect wider gaps between high- and low-SES groups. SII was applied across socioeconomic, sociocultural, and policy dimensions to provide a comprehensive depiction of multilevel structural inequalities. Results showed a steady rise in inequality: the SII for first-dose vaccination increased from approximately 0.35 in 2013 to 0.71 in 2018, while the SII for final-dose vaccination rose from 0.37 to 0.59. These trends reflect widening gaps across economic, institutional, and sociocultural dimensions, highlighting persistent divergence in vaccine accessibility and intensifying structural inequalities. Notably, SII values were consistently higher for first-dose coverage than for full completion, highlighting dropout and discontinuity in vaccination pathways, which are disproportionately concentrated among low-SES populations. Socioculturally, SII revealed disparities in cultural trust, health literacy, and vaccination behavior, with high-SES groups benefiting disproportionately from mainstream health communication, whereas low-SES groups remained hindered by information gaps and distorted risk perceptions (Rivillas et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe SII for cervical cancer mortality remained stable between \u0026minus;\u0026thinsp;0.19 and \u0026minus;\u0026thinsp;0.20, indicating a persistent excess disease burden among low-SES groups with no meaningful improvement over time. The regional hierarchy followed the pattern \u0026lsquo;Americas\u0026thinsp;\u0026gt;\u0026thinsp;Europe\u0026thinsp;\u0026gt;\u0026thinsp;Western Pacific\u0026thinsp;\u0026gt;\u0026thinsp;Eastern Mediterranean\u0026thinsp;\u0026gt;\u0026thinsp;Southeast Asia\u0026thinsp;\u0026gt;\u0026thinsp;Africa,\u0026rsquo; underscoring the structural disadvantage of LMICs in achieving equitable vaccine coverage. At the policy-institutional level, SII illuminated disparities in NIP coverage, fiscal capacity, and frontline implementation. Although most LMICs have formally integrated HPV vaccination into NIPs, limited financial resources and fragile service delivery have hindered the translation of institutional accessibility into effective behavioral uptake (Rivillas et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wiseman et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFrom a theoretical public health perspective, these findings corroborate the mechanistic pathways proposed by the Social Determinants of Health framework and the theory of Institutional Embeddedness of Inequality. Specifically, economic, institutional, and sociocultural factors interact within an institutionally mediated system, which can either amplify disparities or mitigate them through well-designed and effectively implemented policies (Gill \u0026amp; Benatar, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Mulaga et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The SII not only quantifies the socioeconomic gradients of vaccination and mortality but also explains how interactions among fiscal resources, institutional arrangements, and cultural factors generate a fractured fiscal\u0026ndash;institution\u0026ndash;behavior chain. Although most LMICs have integrated HPV vaccination into national immunization programs, constraints in fiscal capacity, service infrastructure, and community mobilization render vaccines institutionally accessible but practically unattainable at the implementation level. Information asymmetry, cultural barriers, and deficits in trust further exacerbate dropout and response obstacles among low-SES groups, reinforcing a fractured \u0026ldquo;fiscal-institution-behavior\u0026rdquo; chain (Bray et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Guillaume et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMore critically, even where vaccination coverage has improved, disparities in cervical cancer mortality have persisted, indicating that current programs have not yet achieved high-quality coverage among vulnerable populations. This gap undermines population-level protection and may exacerbate existing inequalities through uneven intervention diffusion, leading to a structural amplification effect. The application of SII highlights both the socioeconomic gradients underlying vaccination behavior and health risks, and the deeper structural challenges constraining global HPV vaccine promotion. Future strategies for vaccine equity must proceed along three parallel tracks: sustained and stable financial support, precise and effective institutional pathways, and the systematic development of culturally sensitive and trust-building mechanisms. Such efforts are essential to move beyond \u0026ldquo;institutional equity\u0026rdquo; toward \u0026ldquo;substantive equity,\u0026rdquo; thereby advancing structural health justice on a global scale.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThis study used longitudinal data from six WHO regions (2013\u0026ndash;2018) to establish a multidimensional framework linking vaccination coverage, health outcomes, and structural social determinants. Based on this framework, a \u0026lsquo;vaccination-health outcome-structural inequality\u0026rsquo; three-pathway model was proposed. The results showed that although global HPV vaccination coverage increased, substantial gaps between first- and final-dose completion persisted in Africa, the Eastern Mediterranean, and South-East Asia, reflecting disparities in accessibility, continuity, and institutional capacity. Vaccination coverage was inversely associated with cervical cancer mortality, particularly in Europe and the Americas, indicating that public health benefits depend not only on overall coverage but also on equitable distribution and completion of vaccination schedules.\u003c/p\u003e\u003cp\u003eGovernment health expenditure was consistently associated with higher vaccination rates, supporting the conclusion that fiscal investment is a key driver of equity. The structural inequality index developed in this study, which incorporated income stratification, NIP coverage, physician density, female parliamentary representation, and labor force participation, effectively explained regional disparities in both vaccination and cervical cancer mortality. Gender equality indicators were positively associated with vaccine uptake, providing further evidence that female empowerment improves access to and utilization of health resources.\u003c/p\u003e\u003cp\u003eIn summary, structural inequalities remain a major barrier to HPV vaccine scale-up and cervical cancer control. Addressing these disparities requires not only expanding resources but also implementing structural interventions, including targeted fiscal investment, institutional strengthening, and gender equity promotion. In addition, advancing cross-regional governance is essential to ensure sustainable and scalable responses. Future research should quantify the relative contributions of structural factors and assess multilevel strategies across diverse income settings to inform evidence-based and context-specific vaccination policies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eClinical Trial Number\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by the 2024 Beijing Routine Health Expenditure Accounting Based on SHA2011 (Grant No. BUCM-2025-KYJS-KYC-011) and the Scientific Research Project from Jiangsu Commission of Health (No. F202151).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSiyan Liu: Investigation, writing \u0026ndash; original draft. Xiaowei Man: Conceptualization, investigation, writing \u0026ndash; original draft, writing \u0026ndash; review and editing, supervision, project administration. Xingli Cao: Writing \u0026ndash; review and editing.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcharya K, Dharel D, Subedi RK, Bhattarai A, Paudel YR. Inequalities in full vaccination coverage based on maternal education and wealth quintiles among children aged 12\u0026ndash;23 months: further analysis of national cross-sectional surveys of six South Asian countries. BMJ Open. 2022;12(2):e046971. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2020-046971\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2020-046971\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlarc\u0026atilde;o V, Zdravkova B. Attitudes and Practices towards HPV Vaccination and Its Social Processes in Europe: An Equity-Focused Scoping Review. Societies. 2022;12(5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/soc12050131\u003c/span\u003e\u003cspan address=\"10.3390/soc12050131\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAli HA, Hartner A-M, Echeverria-Londono S, Roth J, Li XM, Abbas K, Portnoy A, Vynnycky E, Woodruff K, Ferguson NM, Toor J, Gaythorpe KA. Vaccine equity in low and middle income countries: a systematic review and meta-analysis. Int J Equity Health. 2022;21(1):82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12939-022-01678-5\u003c/span\u003e\u003cspan address=\"10.1186/s12939-022-01678-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAraujo JFFE, Tejedo-Romero F. Women\u0026rsquo;s political representation and transparency in local governance. Local Government Stud. 2016;42(6):885\u0026ndash;906. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/03003930.2016.1194266\u003c/span\u003e\u003cspan address=\"10.1080/03003930.2016.1194266\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArbyn M, Weiderpass E, Bruni E, de Sanjose S, Saraiya M, Ferlay J, Bray F. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. Lancet Global Health. 2020;8(2):e191\u0026ndash;203. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2214-109X(19)30482-6\u003c/span\u003e\u003cspan address=\"10.1016/S2214-109X(19)30482-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBinagwaho A, Wagner CM, Gatera M, Karema C, Nutt CT, Ngabo F. Achieving high coverage in Rwanda's national human papillomavirus vaccination programme. Bull World Health Organ. 2012;90(8):623\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2471/BLT.11.097253\u003c/span\u003e\u003cspan address=\"10.2471/BLT.11.097253\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBranda F, Pavia G, Ciccozzi A, Quirino A, Marascio N, Gigliotti S, Matera G, Romano C, Locci C, Azzena I, Pascale N, Sanna D, Casu M, Ceccarelli G, Ciccozzi M, Scarpa F. Human Papillomavirus (HPV) Vaccination: Progress, Challenges, and Future Directions in Global Immunization Strategies. Vaccines. 2024;12(11). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/vaccines12111293\u003c/span\u003e\u003cspan address=\"10.3390/vaccines12111293\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2018;68(6):394\u0026ndash;424. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3322/caac.21492\u003c/span\u003e\u003cspan address=\"10.3322/caac.21492\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrotherton J, Hendry A, Dey A, Hull BP, Beard F. HPV vaccination coverage: slightly improved two-dose schedule completion estimates and historical estimates lower on AIR than HPV Register. Aust N Z J Public Health. 2022;46(3):394\u0026ndash;400. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1753-6405.13233\u003c/span\u003e\u003cspan address=\"10.1111/1753-6405.13233\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBruni L, Diaz M, Barrionuevo-Rosas L, Herrero R, Bray F, Bosch FX, de Sanjose S, Castellsague X. Global estimates of human papillomavirus vaccination coverage by region and income level: a pooled analysis. Lancet Global Health. 2016;4(7):e453\u0026ndash;463. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2214-109X(16)30099-7\u003c/span\u003e\u003cspan address=\"10.1016/S2214-109X(16)30099-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBruni L, Saura-Lazaro A, Montoliu A, Brotons M, Alemany L, Diallo MS, Afsar OZ, LaMontagne DS, Mosina L, Contreras M, Velandia-Gonzalez M, Pastore R, Gacic-Dobo M, Bloem P. HPV vaccination introduction worldwide and WHO and UNICEF estimates of national HPV immunization coverage 2010\u0026ndash;2019. Prev Med. 2021;144:106399. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ypmed.2020.106399\u003c/span\u003e\u003cspan address=\"10.1016/j.ypmed.2020.106399\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBudu E, Opoku Ahinkorah B, Okyere J, Seidu A-A, Ofori Duah H. Inequalities in the prevalence of full immunization coverage among one-year-olds in Ghana, 1993\u0026ndash;2014. Vaccine. 2022;40(26):3614\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.vaccine.2022.04.081\u003c/span\u003e\u003cspan address=\"10.1016/j.vaccine.2022.04.081\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCata-Preta BdO, Wehrmeister FC, Santos TM, Barros AJD, Victora CG. Patterns in Wealth-related Inequalities in 86 Low- and Middle-Income Countries: Global Evidence on the Emergence of Vaccine Hesitancy. Am J Prev Med. 2021;60(1 Suppl 1):S24\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.amepre.2020.07.028\u003c/span\u003e\u003cspan address=\"10.1016/j.amepre.2020.07.028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCutts FT, Claquin P, Danovaro-Holliday MC, Rhoda DA. Monitoring vaccination coverage: Defining the role of surveys. Vaccine. 2016;34(35):4103\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.vaccine.2016.06.053\u003c/span\u003e\u003cspan address=\"10.1016/j.vaccine.2016.06.053\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDenny L. (2022). HPV vaccine introduction and implementation in Low- and Middle-Income Countries. \u003cem\u003eVaccine\u003c/em\u003e, \u003cem\u003e40 Suppl 1\u003c/em\u003e, A1. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.vaccine.2022.02.074\u003c/span\u003e\u003cspan address=\"10.1016/j.vaccine.2022.02.074\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDorji T, Nopsopon T, Tamang ST, Pongpirul K. (2021). Human papillomavirus vaccination uptake in low-and middle-income countries: a meta-analysis. \u003cem\u003eEClinicalMedicine\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e, 100836. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.eclinm.2021.100836\u003c/span\u003e\u003cspan address=\"10.1016/j.eclinm.2021.100836\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDube E, Laberge C, Guay M, Bramadat P, Roy RR, Bettinger JA. Vaccine hesitancy: an overview. Hum Vaccines Immunotherapeutics. 2013;9(8):1763\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4161/hv.24657\u003c/span\u003e\u003cspan address=\"10.4161/hv.24657\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEkwunife OI, Lhachimi SK. Cost-effectiveness of Human Papilloma Virus (HPV) vaccination in Nigeria: a decision analysis using pragmatic parameter estimates for cost and programme coverage. BMC Health Serv Res. 2017;17(1):815. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12913-017-2758-2\u003c/span\u003e\u003cspan address=\"10.1186/s12913-017-2758-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFledderjohann J, Channon M. Gender, nutritional disparities, and child survival in Nepal. BMC Nutr. 2022;8(1):50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s40795-022-00543-6\u003c/span\u003e\u003cspan address=\"10.1186/s40795-022-00543-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGallagher KE, LaMontagne DS, Watson-Jones D. (2018). Status of HPV vaccine introduction and barriers to country uptake. \u003cem\u003eVaccine\u003c/em\u003e, \u003cem\u003e36\u003c/em\u003e(32 Pt A), 4761\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.vaccine.2018.02.003\u003c/span\u003e\u003cspan address=\"10.1016/j.vaccine.2018.02.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarland SM. Population-level impact and herd effects following HPV vaccination programs: a global view. Pathology 51. 2019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pathol.2018.12.147\u003c/span\u003e\u003cspan address=\"10.1016/j.pathol.2018.12.147\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGill S, Benatar SR. History, Structure and Agency in Global Health Governance Comment on Global Health Governance Challenges 2016 - Are We Ready? Int J Health Policy Manage. 2017;6(4):237\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.15171/ijhpm.2016.119\u003c/span\u003e\u003cspan address=\"10.15171/ijhpm.2016.119\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuillaume D, Waheed D-e-N, Schleiff M, Muralidharan KK, Vorsters A, Limaye RJ. Global perspectives of determinants influencing HPV vaccine introduction and scale-up in low- and middle-income countries. PLoS ONE. 2024;19(1):e0291990. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0291990\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0291990\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHabib RR, El-Harakeh A, Ziadee M, Abi Younes E, Asmar E, K. Social capital, social cohesion, and health of Syrian refugee working children living in informal tented settlements in Lebanon: A cross-sectional study. PLoS Med. 2020;17(9):e1003283. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pmed.1003283\u003c/span\u003e\u003cspan address=\"10.1371/journal.pmed.1003283\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHan J, Zhang L, Chen Y, Zhang Y, Wang L, Cai R, Li M, Dai Y, Dang L, Chen H, Zhu L. (2025). Global HPV vaccination programs and coverage rates: a systematic review. \u003cem\u003eEClinicalMedicine\u003c/em\u003e, \u003cem\u003e84\u003c/em\u003e, 103290. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.eclinm.2025.103290\u003c/span\u003e\u003cspan address=\"10.1016/j.eclinm.2025.103290\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJit M, Brisson M, Portnoy A, Hutubessy R. Cost-effectiveness of female human papillomavirus vaccination in 179 countries: a PRIME modelling study. Lancet Global Health. 2014;2(7):e406\u0026ndash;414. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2214-109X(14)70237-2\u003c/span\u003e\u003cspan address=\"10.1016/S2214-109X(14)70237-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKjaer SK, Dehlendorff C, Belmonte F, Baandrup L. Real-World Effectiveness of Human Papillomavirus Vaccination Against Cervical Cancer. J Natl Cancer Inst. 2021;113(10):1329\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jnci/djab080\u003c/span\u003e\u003cspan address=\"10.1093/jnci/djab080\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKruk ME, Gage AD, Arsenault C, Jordan K, Leslie HH, Roder-DeWan S, Adeyi O, Barker P, Daelmans B, Doubova SV, English M, Garcia-Elorrio E, Guanais F, Gureje O, Hirschhorn LR, Jiang L, Kelley E, Lemango ET, Liljestrand J, Pate M. High-quality health systems in the Sustainable Development Goals era: time for a revolution. Lancet Global Health Comm. 2018;6(11):e1196\u0026ndash;252. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2214-109X(18)30386-3\u003c/span\u003e\u003cspan address=\"10.1016/S2214-109X(18)30386-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLarsson EC, Wittberg E, Lundasen SW. Variations in vaccination uptake: COVID-19 vaccination rates in Swedish municipalities. PLOS Global Public Health. 2022;2(10):e0001204. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pgph.0001204\u003c/span\u003e\u003cspan address=\"10.1371/journal.pgph.0001204\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLimbu YB, Gautam RK. The determinants of COVID-19 vaccination intention: a meta-review. Front Public Health. 2023;11:1162861. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpubh.2023.1162861\u003c/span\u003e\u003cspan address=\"10.3389/fpubh.2023.1162861\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLindstrom M. Psychosocial stress and social capital pathways and health: Perspectives from Lund University, Malmo. Scand J Public Health. 2022;50(7):864\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/14034948221075015\u003c/span\u003e\u003cspan address=\"10.1177/14034948221075015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLupu D, Tiganasu R. COVID-19 vaccination and governance in the case of low, middle and high-income countries. BMC Public Health. 2023;23(1):1073. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12889-023-15975-3\u003c/span\u003e\u003cspan address=\"10.1186/s12889-023-15975-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuthra K, Zimmermann Jin A, Vasudevan P, Kirk K, Marzetta C, Privor-Dumm L. Assessing vaccine introduction and uptake timelines in Gavi-supported countries: are introduction timelines accelerating across vaccine delivery platforms? BMJ Global Health. 2021;6(5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjgh-2021-005032\u003c/span\u003e\u003cspan address=\"10.1136/bmjgh-2021-005032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMachingaidze S, Wiysonge CS, Hussey GD. Strengthening the expanded programme on immunization in Africa: looking beyond 2015. PLoS Med. 2013;10(3):e1001405. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pmed.1001405\u003c/span\u003e\u003cspan address=\"10.1371/journal.pmed.1001405\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMackenbach JP. The persistence of health inequalities in modern welfare states: the explanation of a paradox. Soc Sci Med. 2012;75(4):761\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.socscimed.2012.02.031\u003c/span\u003e\u003cspan address=\"10.1016/j.socscimed.2012.02.031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMacmillan R, Shofia N, Sigle W. Gender and the Politics of Death: Female Representation, Political and Developmental Context, and Population Health in a Cross-National Panel. Demography. 2018;55(5):1905\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s13524-018-0697-0\u003c/span\u003e\u003cspan address=\"10.1007/s13524-018-0697-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMalik S, Mock KO, Martillotti R, Caravella G, Zhou X, Mbamelu M, Scarbrough KH. HPV Vaccines Among University Students: Understanding Barriers and Facilitators of Vaccine Uptake. Vaccines. 2024;12(12). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/vaccines12121385\u003c/span\u003e\u003cspan address=\"10.3390/vaccines12121385\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eManess SB, Thompson EL. Social Determinants of Human Papillomavirus Vaccine Uptake: An Assessment of Publicly Available Data. Public Health Rep. 2019;134(3):264\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0033354919838219\u003c/span\u003e\u003cspan address=\"10.1177/0033354919838219\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMengistie BA, Yirsaw AN, Lakew G, Mekonnen GB, Shibabaw AA, Chereka AA, Kitil GW, Wondie WT, Abuhay AE, Getachew E. Human papillomavirus vaccine uptake and its determinants among women in Africa: an umbrella review. Front Public Health. 2025;13:1537250. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpubh.2025.1537250\u003c/span\u003e\u003cspan address=\"10.3389/fpubh.2025.1537250\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMensch BS, Chuang EK, Melnikas AJ, Psaki SR. Evidence for causal links between education and maternal and child health: systematic review. Trop Med Int Health. 2019;24(5):504\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/tmi.13218\u003c/span\u003e\u003cspan address=\"10.1111/tmi.13218\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMulaga AN, Kamndaya MS, Masangwi SJ. Decomposing socio-economic inequality in catastrophic out-of-pocket health expenditures in Malawi. PLOS Global Public Health. 2022;2(2):e0000182. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pgph.0000182\u003c/span\u003e\u003cspan address=\"10.1371/journal.pgph.0000182\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNguyen PT, Nakamura R, Shimadzu H, Abubakar AK, Le PM, Nguyen HV, Nguyen HL, Sato M, Honda A, Gilmour S. Progress and inequality in child immunization in 38 African countries, 2000\u0026ndash;2030: A spatio-temporal Bayesian analysis at national and sub-national levels. PLoS Med. 2025;22(7):e1004664. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pmed.1004664\u003c/span\u003e\u003cspan address=\"10.1371/journal.pmed.1004664\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNova A, Fazia T, Bernardinelli L. Investigating mortality trends in Italy during the COVID-19 pandemic: life expectancy changes within provinces and vaccination campaign impact up to December 2022. Public Health. 2023;225:168\u0026ndash;75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.puhe.2023.09.031\u003c/span\u003e\u003cspan address=\"10.1016/j.puhe.2023.09.031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOnagoruwa A, Wodon Q. Child marriage, educational attainment, and comprehensive knowledge of HIV/AIDS: a multi-country analysis. J Biosoc Sci. 2025;57(1):96\u0026ndash;111. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0021932024000397\u003c/span\u003e\u003cspan address=\"10.1017/S0021932024000397\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOzawa S, Clark S, Portnoy A, Grewal S, Brenzel L, Walker DG. Return On Investment From Childhood Immunization In Low- And Middle-Income Countries, 2011-20. Health Aff. 2016;35(2):199\u0026ndash;207. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1377/hlthaff.2015.1086\u003c/span\u003e\u003cspan address=\"10.1377/hlthaff.2015.1086\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePozo-Martin F, Nove A, Lopes SC, Campbell J, Buchan J, Dussault G, Kunjumen T, Cometto G, Siyam A. Health workforce metrics pre- and post-2015: a stimulus to public policy and planning. Hum Resoures Health. 2017;15(1):14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12960-017-0190-7\u003c/span\u003e\u003cspan address=\"10.1186/s12960-017-0190-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuamruzzaman A, Lange M. Female political representation and child health: Evidence from a multilevel analysis. Soc Sci Med. 2016. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.socscimed.2016.10.025\u003c/span\u003e\u003cspan address=\"10.1016/j.socscimed.2016.10.025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRestrepo-Mendez MC, Barros AJ, Wong KL, Johnson HL, Pariyo G, Franca GV, Wehrmeiste FC, Victora CG. Inequalities in full immunization coverage: trends in low- and middle-income countries. Bull World Health Organ. 2016;94(11):794\u0026ndash;B805. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2471/BLT.15.162172\u003c/span\u003e\u003cspan address=\"10.2471/BLT.15.162172\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRivillas JC, Devia-Rodriguez R, Ingabire M-G. Measuring socioeconomic and health financing inequality in maternal mortality in Colombia: a mixed methods approach. Intertional J Equity Health. 2020;19(1):98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12939-020-01219-y\u003c/span\u003e\u003cspan address=\"10.1186/s12939-020-01219-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRughinis C, Vulpe SN, Flaherty MG, Vasile S. Vaccination, life expectancy, and trust: patterns of COVID-19 and measles vaccination rates around the world. Public Health. 2022;210:114\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.puhe.2022.06.027\u003c/span\u003e\u003cspan address=\"10.1016/j.puhe.2022.06.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShato T, Humble S, Anandarajah A, Barnette A, Brandt HM, Garbutt J, Klesges L, Thompson VS, Silver MI. Influences of sociodemographic characteristics and parental HPV vaccination hesitancy on HPV vaccination coverage in five US states. Vaccine. 2023;41(25):3772\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.vaccine.2023.04.082\u003c/span\u003e\u003cspan address=\"10.1016/j.vaccine.2023.04.082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. Cancer J Clin. 2021;71(3):209\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3322/caac.21660\u003c/span\u003e\u003cspan address=\"10.3322/caac.21660\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Minh H, My NTT, Jit M. Cervical cancer treatment costs and cost-effectiveness analysis of human papillomavirus vaccination in Vietnam: a PRIME modeling study. BMC Health Serv Res. 2017;17(1):353. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12913-017-2297-x\u003c/span\u003e\u003cspan address=\"10.1186/s12913-017-2297-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Q, Leung K, Jit M, Wu JT, Lin L. Global socioeconomic inequalities in vaccination coverage, supply, and confidence. NPJ Vaccines. 2025;10(1):91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41541-025-01143-8\u003c/span\u003e\u003cspan address=\"10.1038/s41541-025-01143-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWesten EA, Bard E, Li D, Dye T, Whaley N, Seligman N. 746: Women\u0026rsquo;s representation in government as a predictor of women\u0026rsquo;s health outcomes. Am J Obstet Gynecol. 2019;220(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ajog.2018.11.769\u003c/span\u003e\u003cspan address=\"10.1016/j.ajog.2018.11.769\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWigle J, Fontenot HB, Zimet GD. Global Delivery of Human Papillomavirus Vaccines. Pediatr Clin North Am. 2016;63(1):81\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pcl.2015.08.004\u003c/span\u003e\u003cspan address=\"10.1016/j.pcl.2015.08.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWiseman V, Lagarde M, Batura N, Lin S, Irava W, Roberts G. Measuring inequalities in the distribution of the Fiji Health Workforce. Int J Equity Health. 2017;16(1):115. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12939-017-0575-1\u003c/span\u003e\u003cspan address=\"10.1186/s12939-017-0575-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiong S, Humble S, Barnette A, Brandt H, Thompson V, Klesges LM, Silver MI. Associations of geographic-based socioeconomic factors and HPV vaccination among male and female children in five US states. BMC Public Health. 2024;24(1):702. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12889-024-18206-5\u003c/span\u003e\u003cspan address=\"10.1186/s12889-024-18206-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou L, Li Y, Wang H, Qin R, Han Z, Li R. Global cervical cancer elimination: quantifying the status, progress, and gaps. BMC Med. 2025;23(1):67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12916-025-03897-3\u003c/span\u003e\u003cspan address=\"10.1186/s12916-025-03897-3\" 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":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"HPV Vaccination Coverage, Cervical Cancer, Structural Health Inequality, Socioeconomic Factor, National Immunization Program (NIP), Global Health Policy","lastPublishedDoi":"10.21203/rs.3.rs-7654138/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7654138/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCervical cancer remains one of the most prevalent malignancies affecting women globally, and HPV vaccination is widely recognized as the cornerstone of primary prevention. Drawing on global macro-level data from 2013 to 2018, this study systematically evaluated the spatiotemporal patterns of HPV vaccination coverage and its associations with multiple structural determinants. By integrating indicators including first- and final-dose vaccine coverage, cervical cancer mortality, per capita GDP, physician density, government health expenditure, women\u0026rsquo;s educational attainment, female social participation, labor force involvement, and the inclusion of HPV vaccines in national immunization programs (NIPs), and applying visualization, correlation analysis, and Slope Index of Inequality (SII) modeling, we revealed pronounced inequities in HPV vaccination across the globe. Through the integration of visualization, correlation analyses, and Slope Index of Inequality (SII) modeling, we uncovered marked inequities in HPV vaccination coverage across the globe. The findings demonstrate that structural health inequalities constitute a fundamental barrier to achieving equitable HPV vaccine uptake. Future strategies should emphasize multidimensional policy interventions, including prioritized fiscal investment, institutional design optimization, and gender equity promotion, to enhance resource allocation efficiency and improve access to women\u0026rsquo;s health services. These measures will provide robust scientific evidence and policy guidance for advancing the global cervical cancer elimination agenda.\u003c/p\u003e","manuscriptTitle":"Structural Determinants of HPV Vaccination Inequalities: A Multiregional Analysis across Six WHO Regions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 19:05:10","doi":"10.21203/rs.3.rs-7654138/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d8bf912d-445a-4895-b894-5f97553fc9d5","owner":[],"postedDate":"October 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-04T10:26:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-16 19:05:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7654138","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7654138","identity":"rs-7654138","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}