Skip to main content

Measuring school level attributable risk to support school-based HPV vaccination programs

Abstract

Background

In Australia in 2017, 89% of 15-year-old females and 86% of 15-year-old males had received at least one dose of the HPV vaccine. However, considerable variation in HPV vaccination initiation (dose one) across schools remains. It is important to understand the school-level characteristics most strongly associated with low initiation and their contribution to the overall between-school variation.

Methods

A population-based ecological analysis was conducted using school-level data for 2016 on all adolescent students eligible for HPV vaccination in three Australian jurisdictions. We conducted logistic regression to determine school-level factors associated with lower HPV vaccination initiation (< 75% dose 1 uptake) and estimated the population attributable risk (PAR) and the proportion of schools with the factor (school-level prevalence).

Results

The factors most strongly associated with lower initiation, and their prevalence were; small schools (OR = 9.3, 95%CI = 6.1–14.1; 33% of schools), special education schools (OR = 5.6,95%CI = 3.7–8.5; 8% of schools), higher Indigenous enrolments (OR = 2.7,95% CI:1.9–3.7; 31% of schools), lower attendance rates (OR = 2.6,95%CI = 1.7–3.7; 35% of schools), remote location (OR = 2.6,95%CI = 1.6–4.3; 6% of schools,) and lower socioeconomic area (OR = 1.8,95% CI = 1.3–2.5; 33% of schools). The highest PARs were small schools (PAR = 79%, 95%CI:76–82), higher Indigenous enrolments (PAR = 38%, 95%CI: 31–44) and lower attendance rate (PAR = 37%, 95%CI: 29–46).

Conclusion

This analysis suggests that initiatives to support schools that are smaller, with a higher proportion of Indigenous adolescents and lower attendance rates may contribute most to reducing the variation of HPV vaccination uptake observed at a school-level in these jurisdictions. Estimating population-level coverage at the school-level is useful to guide policy and prioritise resourcing to support school-based vaccination programs.

Peer Review reports

Introduction

Human papillomavirus (HPV) infection causes nearly all cervical cancers, with cervical cancer the fourth most common cause of cancer incidence and mortality in women worldwide [1]. HPV is also responsible for 90% of anal, 60% of penile and 30% of oropharyngeal cancers globally [2, 3]. Since the 1970s the incidence of oropharyngeal cancer has substantially increased among younger age groups in the United States, Canada, parts of Europe and Australia [2, 4, 5]. In addition, HPV causes 90% of genital warts, which prior to vaccine introduction was the most commonly managed sexual health condition in Australia [2]. HPV-related cancers and genital warts have significant adverse impacts on reproductive health and quality of life and are costly to manage [6, 7].

The first HPV vaccine providing protection against oncogenic types of HPV and, in turn, invasive cervical cancer, other cancers and genital warts was registered in Australia in 2006 [8, 9]. Numerous studies since have demonstrated the population effectiveness of the vaccine in reducing genital warts [10, 11], high-grade precancerous cervical lesions [12,13,14] and, more recently, invasive cervical cancer [15]. As of late 2019, over 124 countries had implemented a national HPV vaccination program [16]. HPV vaccination programs are targeted at young adolescents, as the vaccine is most effective prior to initiation of sexual activity and exposure to the virus [17, 18]. In November 2020, the World Health Organisation (WHO) launched the ‘Global Strategy to accelerate the elimination of cervical cancer as a public health problem’, which is underpinned by the three pillars of HPV vaccination, cervical screening using HPV testing (or equivalent), and treatment [19]. The strategy calls for the achievement of HPV vaccination coverage of 90% of girls by age 15 years (based on the coverage necessary in countries with a single-sex vaccination program) [19]. This goal was set based on the effectiveness of HPV vaccines [13, 14, 20], and cervical screening using HPV testing.

Voluntary on-site school-based HPV vaccination programs have been successful in achieving high rates of vaccination coverage in adolescents in Australia, Canada, several European countries and several low- and middle-income countries [21,22,23]. Australia was the first country to implement a fully funded, national, school-based HPV vaccination program, and since its introduction has achieved high coverage, reaching just over 80% of eligible students in 2017 for the 3-dose course [24], before switching to a 2-dose course in 2018. The school-based HPV vaccination program operates at the beginning of secondary school, either in Year 7 or Year 8 (11 to 14 years of age), for boys and girls. Public Health units or local councils are responsible for administering the vaccines, in partnership with schools. In Australia, adolescents access the HPV vaccine primarily through their schools, however students who miss doses through the school-based program are eligible to receive the vaccine through primary care up until the age of 19 years.

Despite the high HPV vaccination coverage achieved in Australia, programmatic reports have indicated there is variation in coverage between jurisdictions and also between smaller geographical areas within jurisdictions [25, 26]. Recently, we examined variation at the schoollevel, and identified school-level factors associated with lower initiation of HPV vaccination across 3 Australian states [27]. Further investigation of these data at a school level demonstrated 25% of schools had low initiation coverage (< 75% dose 1 uptake) and there were multiple school-level factors associated with lower initiation coverage [27]. Here we extend this analysis to calculate the population-attributable risk (PAR) [28], which accounts for both the strength of the association and the prevalence of the risk factor in the population. While PAR is traditionally used to calculate risk for individuals in a population, our unit of measure is at the school level and, thus, hereafter we will refer to the PAR as school-level attributable risk. Measuring school-level attributable risk may determine where to focus interventions to address variations in HPV vaccination coverage at the school level, and, in turn, ensure all adolescents have equal opportunity to be offered HPV vaccination initiation, irrespective of which school they attend. Coverage is used in this context to describe the percentage of the community who received a vaccine (population level), while uptake is used in the context of a person accepting the vaccine (individual level). Although we are examining school- level factors related to uptake, there are a variety of factors that influence vaccination uptake including sociodemographic characteristics such as income, geographic location, education and occupation; access to health care and other organisational factors; social environmental factors including media influence and social norms; individual child characteristics; individual parental factors including educational level, ethnicity, religious beliefs, and knowledge regarding HPV and cervical cancer; and trust in the pharmaceutical industry and government [23, 29,30,31,32,33,34,35,36,37,38,39]. This method therefore does not assess risk factors at the individual level, but rather provides an indication of school-level factors that can inform interventions and future research.

To our knowledge, the PAR method has not been used previously to understand the contribution of factors associated with vaccine uptake at the school level, with the few studies using this method focused on vaccination uptake in the United States health care setting [40,41,42], no studies have calculated school-level attributable risk. Here we aim to determine the school-level attributable risk of school-level factors associated with lower HPV vaccination initiation and estimate the school-level attributable risk using the odds ratio and school-level factor prevalence.

Methods

Study design and context

We conducted an ecological analysis of HPV vaccine initiation coverage across three Australian states – New South Wales (NSW), Tasmania and Western Australia (WA) – with the school as the unit of analysis.

Study population

We included all secondary schools, which provide education to adolescents (approximately 12–18 years of age), in the three states for which year-specific student enrolment numbers and number of delivered HPV vaccination doses were available for 2016. We restricted our analysis to schools with vaccine-eligible enrolment numbers of at least 10 students.

Study outcome

The primary outcome was the proportion of adolescents in each school who initiated the HPV vaccination course (1 or more doses of the quadrivalent HPV vaccine). As the focus of the analysis was school-level coverage (rather than population-level coverage), only doses recorded by the National HPV Vaccination Program Register (NHPVR) as having been delivered in school and which could be attributed to a school and year level were included in the analysis. Initiation coverage for a school was calculated as the number of dose 1 vaccinations reported to the NHPVR divided by the student enrolments for the year level of program delivery. Low initiation coverage was defined as < 75% dose 1 uptake of the first dose.

Data sources

We obtained data from the following four statutory bodies to calculate the study outcomes and covariates. All datasets were at the school or postcode level of the school in 2016.

1. National HPV Vaccination Program Register (NHPVR): the national HPV vaccination registry (closed at the end of 2018), which collected details about HPV vaccinations given in Australia [43]. We obtained vaccination doses given by cohort year and school name.

2. Jurisdictional health departments: responsible for immunisation programs, and collection of individual-level data on HPV doses delivered in schools and enrolment data. We obtained school enrolment data for each school grade in which the vaccine program was delivered (Year 7 in two jurisdictions, Year 8 in one jurisdiction). Enrolment data collected from New South Wales (NSW), Western Australia (WA) and Tasmania included graded schools (which denoted school year) for mainstream schools and special education schools. WA also included ungraded ‘special education’ schools (schools that do not place students in a specific year level).

3. The Australian Curriculum, Assessment and Reporting Authority (ACARA): an independent statutory authority responsible for the development of a national curriculum, which collects and reports characteristics of schools and their students [44]. We obtained total enrolments for the entire school (school size); student attendance rate (defined as student days attended as a proportion of total possible student days); co-educational status (i.e. whether the school enrols both boys and girls); special education status (i.e. schools catering for students with special educational needs, or mainstream schools); the percentage of students identified as Indigenous students; and the percentage of students with a language background other than English at home.

4. Australian Bureau of Statistics: a national statutory body which collects demographic data from Australian residents by a census every 5 years. We obtained data on the Socio-Economic Indexes for Areas Index of Relative Socio-Economic Disadvantage (a standard area-level measure of disadvantage summarising a range of information about economic and social conditions of households within an area) at the postcode level [45], and for remoteness (five classes of remoteness based on a measure of relative access to services: major city, inner regional, outer regional, remote, and very remote) at the postcode level [45].

Statistical analysis

We merged the datasets above using the school name and postcode. For unmatched schools, we then utilised probabilistic matching using the STATA ‘reclink’ command. Remaining records were reviewed manually, with only plausible matches included.

We conducted univariate logistic regression analysis to identify sociodemographic and school-related factors associated with the primary outcome of low HPV initiation. Sociodemographic variables included the percentage of enrolled students who identified as Indigenous, the percentage of enrolled students with a language background other than English (LBOTE), and the SEIFA IRSD defined by postcode of the school [45]. School-related variables included co-educational status (both boys and girls vs single sex), special education status (catering for special educational needs vs mainstream), geographical location of the school (major city, inner regional, outer regional, remote, or very remote), size of the school (based on total enrolments), attendance (percentage of all possible school days attended), and school affiliation (independent, Catholic, government). We categorised the continuous measurements (school size, Indigenous enrolment, language background other than English, socioeconomic disadvantage score and attendance) using data-driven tertiles. We did not conduct a multivariate analysis due to previously known high levels of collinearity/multicollinearity between the school-level characteristics [27], but instead accounted for the collinearity when calculating the combined school-level attributable risk.

School-level attributable risk

We estimated school-level impacts of each school-level characteristic on low-coverage schools in the dataset by combining the odds ratios and the prevalence of the school-level characteristics distributed across the schools as described in Table 1. Briefly, we calculated the school-level attributable risk percentage for each characteristic and 95% confidence intervals (CI) individually, as well as their combined impact in a multifactorial setting accounting for their correlation structure [46]. We adjusted for school affiliation, rather than including it as a covariate, to maintain anonymity as requested by stakeholders in the education sector. Analyses were conducted using STATA IC v14.2 (StataCorp, College Station, TX); school-level attributable risk percentages were calculated using SAS version 9 (SAS Inc., Cary, NC). Appendix 1 illustrates the calculation of the school-level attributable risk and the 95% CI for school size as an example variable using the fully documented, publicly available macro (https://www.hsph.harvard.edu/donna-spiegelman/software/par/).

Ethical approval

Ethical approval was provided by the Human Research Ethics Committees of the University of New South Wales (HC17632), the Australian National University (2017/516), the University of Tasmania (1320/17), the Aboriginal Health and Medical Research Council of New South Wales (1320/17), the Aboriginal Health Council of Western Australia (818), and the Department of Health of Western Australia (RGS0000000456).

Results

Characteristics of schools

Of 1325 schools, we excluded 39 schools for which we had enrolment data but no matching school vaccination data, leaving 1286 schools. Of the 1286 schools included, 86% were co-educational, 58% were in major cities, 35% had low attendance rates (< 87% of all possible school days attended), 33% were small (enrolments of 11–383 total students in the school), 33% were located in areas in the most socioeconomically disadvantaged tertile, 31% had a high proportion of Indigenous enrolments, and 8% were special education schools. There were 327 schools considered as low coverage.

Factors associated with lower initiation

The median school-level HPV vaccination initiation (i.e. dose 1) coverage was 84.7% (IQR 75.0–90.4%), with 327 (25%) schools classified as having low initiation at ≤ 75% coverage. The school-level factors most strongly associated with lower initiation in the univariate analyses and their prevalence were: small size (OR 9.3, 95%CI = 6.1–14.1, 33% of schools, n = 419), serving adolescents with special education needs (OR 5.6, 95%CI = 3.7–8.5, 8%, n = 8), a higher proportion of Indigenous adolescents (OR 2.7, 95%CI = 1.9–3.7, 31%, n = 394), lower attendance rates (OR 2.6, 95%CI = 1.7–3.7, 35%, n = 451), location in remote areas (OR 2.6, 95%CI = 1.6–4.3, 6%, n = 73) and location in lower socioeconomic areas (OR 1.8, 95% = 1.3–2.5, 33%, n = 428) (Table 1). There were strong correlations between these characteristics (Table 2).

Table 1 Associations between school characteristics and low in-school HPV vaccine initiation, 2016
Table 2 Correlations between continuous and ordinal categorical covariates (Spearman's rank correlation coefficients), schools in 2016 HPV vaccination program year

School-level attributable risk

The school-level attributable risk was based on the 327 low coverage schools. Characteristics which accounted for the largest proportion of low initiation coverage among the low coverage schools were: smaller size (small and medium), with a school-level attributable risk of 79% (95%CI = 76–82), higher Indigenous enrolments (38%, 95%CI = 31–44), lower attendance rates (37%, 95%CI = 29–46), location in postcodes with higher rates of disadvantage (34%, 95%CI = 28–41), serving adolescents with special education needs (27%, 95%CI = 23–31) and location in remote postcodes (24%, 95%CI = 19–29) (Table 3). Including all these school-level factors in the combined model, the school-level attributable risk was 90%, indicating that these factors account for 90% of schools with low HPV vaccination initiation coverage.

Table 3 Ranked individual impact of each school characteristic and school-level attributable risk %

Discussion

In our multi-state school-level analysis of HPV vaccination initiation coverage, we found the school-level factors most strongly associated with lower dose 1 uptake were: smaller numbers of enrolled students, a student population comprising adolescents with a disability, a higher proportion of Indigenous adolescents, lower attendance rates, a location in remote areas and a location in lower socioeconomic areas. Taking both the odds ratios and the school factor prevalence into account, the school-level attributable risk analysis shows that the characteristics that accounted for the largest proportion of low coverage schools were small size, higher Indigenous enrolments and lower attendance rates.

Based on the highest odds ratio only, small schools were most strongly associated with lower school-level HPV vaccination initiation. As smaller schools (small and medium schools combined) were common, they also had the highest school-level attributable risk at 79%. We are only aware of one other study in the UK which has examined HPV vaccination coverage correlated at a school level, which found that smaller schools achieved lower coverage compared to other schools in the sample [47]. The UK study did not differentiate initiation coverage from completion though, but hypothesised that lower coverage may be due to less resource prioritisation as it may be more efficient to focus on increasing vaccination in larger schools rather than smaller ones [47].

Schools with a higher proportion of Indigenous adolescent enrolment also had a high odds ratio; as such schools were more common, the school-level attributable risk was 38%. Another population-based study in four Australian states and territories demonstrated that, in 2015–2016, first dose coverage exceeded 80% for Indigenous adolescents and was similar to non-Indigenous adolescents; however, this study only included one of the three jurisdictions in our study, highlighting the variation across jurisdictions in Australia [48]. These findings are important as, in Australia, there are important disparities in the burden of disease from cervical cancer, with higher incidence and mortality documented in Indigenous women [49]. These associations are likely to be due to both underscreening and a higher prevalence of risk factors such as smoking and high parity [50], and emphasise the need to achieve equitable vaccination coverage across all geographical areas and population groups.

Schools with low attendance rates had similar odds ratios and school-level attributable risk percentage to schools with higher Indigenous enrolments. Two other Australian studies in recent years have also shown absenteeism to influence HPV vaccination coverage rates, specifically HPV vaccination completion coverage [30, 51]. High absenteeism rates reduce collective opportunities to initiate and complete the HPV vaccination course in school, and novel means of reaching and vaccinating adolescents with lower school attendance in other settings they engage with may be needed.

Special education schools were 5.6 times more likely to have low initiation coverage, with a median vaccination initiation coverage of only 53%; however, these schools only accounted for 8% of all schools in the three states, and thus had a school-level attributable risk of 27%. A recent review of vaccination in people with disability found 14 of 18 included studies reported that people with disabilities have lower rates of vaccination uptake across a range of different vaccines [52]. There have been only two Australian studies that have examined immunisation uptake in adolescents: one study on HPV vaccination [53], and one study on dTpa and HPV vaccination [54]. Both studies indicated that many young people with disabilities in Australia are missing out on adolescent vaccinations, with cited barriers including absenteeism, lack of consent and inability to immunise due to behaviour challenges [53, 54].

In this study, we calculated the school-level attributable risk to determine the school characteristics that contributed most to lower HPV vaccination initiation coverage. These outputs are consistent with a utilitarian ethical framework, where decisions are based on the greatest amount of benefit expected for the greatest number of individuals [55], in this case to reduce school-level variation in vaccination coverage and aim for the global target of 90% HPV vaccination coverage [56]. An alternative approach that could be utilised is the deontological ethical framework, which in this analysis would focus on the odds ratio only. A deontological ethical framework views ethics as a duty where the morality of an action, in this case providing vaccination to those in marginalised groups (even if it is a smaller group), is an obligation, and to not do so would be unacceptable, even if that meant limiting resources more broadly [55]. For example, this would mean we may focus on adolescents with disabilities in special education schools or Indigenous adolescents due to their well-known social and health disadvantages and the higher odds ratios. For Indigenous adolescents, addressing these variations in HPV vaccination uptake is important due to the disparities in the burden of disease from cervical cancer in Indigenous women [57]. For adolescents with disabilities, despite evidence that their sexual health needs are often similar to or greater than those of their typically developing peers, access to and utilisation of other forms of prevention including cervical screening is less common [52, 58]. A combination of the utilitarian and deontological ethical frameworks would be ideal to maximise coverage broadly and ensure equity for all populations.

Our study has a few limitations to consider when interpreting the findings. First, we used an ecological approach to identify schools and specific characteristics associated with lower HPV initiation; therefore, our approach does not assess risk factors at the individual level, but rather provides an indication of school-level factors that can inform interventions and future research. The covariates were based on those routinely available in a range of datasets, and some may have been markers of other risk factors. Many of the variables describing school characteristics were highly correlated, which may have led to an inability to resolve confounding and distinguish causally related factors. Second, due to the strong collinearity/multicollinearity between the school-level characteristics, we were unable to develop multivariable models without introducing bias of unpredictable direction and magnitude due to multicollinearity. Third, we were unable to include all special education schools, with the limited inclusion of ungraded special schools in our study; therefore, the estimated odds ratios may be much higher or lower than reported here. Finally, our analysis focused on the ability of the school-based vaccination programs to vaccinate students in the school setting and therefore did not include vaccinations that may have been administered later through GP clinics, which means HPV vaccine initiation coverage may be higher than reported in our study. Overall, HPV vaccination coverage in Australia is high and coverage trends from 2017–2020 were consistent with the findings of the study with coverage relatively resilient in the face of the COVID pandemic [16]. As our study results were based on data from 2016/2017, there may have since been some fluctuations in the prevalence of risk factors and how they contribute to lower HPV vaccination initiation coverage at the school-level. Additionally, as only three states in Australia participated in the study, the results may not be generalizable to all Australian states and territories although there are strong similarities in the way that schools operate and in how the vaccination program is delivered in schools across the country. Many of the factors identified as associated with lower school level coverage here have been noted previously to be individual student or school level risk factors in other jurisdictions of Australia e.g. students in special schools in Victoria [51] and school absenteeism in South Australia.

In conclusion, we determined that smaller schools, schools with a higher proportion of Indigenous enrolments and schools with lower attendance rates had lower odds than special education schools of having low HPV vaccine initiation coverage. These schools made up 33–79% of schools overall with lower vaccination initiation coverage, thus focusing initiatives in schools with these characteristics would reduce the greatest amount of school-level variation in these three jurisdictions. There is also a need to ensure equitable access to adolescent vaccination across low coverage schools, which, based on the odds ratio, would mean focusing on special education schools. Although school-based HPV vaccination programs have been successful in achieving high rates of vaccination coverage in adolescents in many countries, each country varies in its approach to delivery and prioritisation [59, 60], and coverage achieved is highly variable. The findings of this study may be particularly beneficial for countries with the lowest HPV vaccination uptake. Tailored strategies are critical to improving vaccination uptake in under immunized groups. A recent study in the UK found that new consent procedures can improve uptake of HPV vaccination [59]. Other studies have utilized enhanced reminders, educational and communication activities, and multicomponent strategies [60]. Other interventions that have been shown to improve HPV vaccination coverage included financial incentives and reminders, motivational behavioural interventions, training including assessment and feedback, and consultations [61]. Strategies need to be adaptable to specific contexts to maximize vaccination uptake and understanding school factors can help guide the application of these strategies. The findings from this study may help inform immunisation program planning and prioritisation of resource allocation to support school-based vaccination programs. Further qualitative research is also needed in these settings to understand barriers to vaccination and guide specific strategies to improve uptake in schools with these characteristics.

Availability of data and materials

The data that support the findings of this study are available from the four statutory bodies [participating jurisdictional departments, ABS, ACARA and NHPVR] but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission from the statutory bodies.

References

  1. Arbyn M, Weiderpass E, Bruni L, de Sanjosé S, Saraiya M, Ferlay J, et al. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. Lancet Glob Health. 2020;8(2):e191–203.

    PubMed  Article  Google Scholar 

  2. Bruni L, Diaz M, Barrionuevo-Rosas L, Herrero R, Bray F, Bosch FX, et al. Global estimates of human papillomavirus vaccination coverage by region and income level: a pooled analysis. Lancet Glob Health. 2016;4(7):e453–63.

    PubMed  Article  Google Scholar 

  3. de Martel C, Plummer M, Vignat J, Franceschi S. Worldwide burden of cancer attributable to HPV by site, country and HPV type. Int J Cancer. 2017;141(4):664–70.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  4. de Martel C, Ferlay J, Franceschi S, Vignat J, Bray F, Forman D, et al. Global burden of cancers attributable to infections in 2008: a review and synthetic analysis. Lancet Oncol. 2012;13(6):607–15.

    PubMed  Article  Google Scholar 

  5. Hussein AA, Helder MN, de Visscher JG, Leemans CR, Braakhuis BJ, de Vet HCW, et al. Global incidence of oral and oropharynx cancer in patients younger than 45 years versus older patients: A systematic review. Eur J Cancer. 2017;82:115–27.

    PubMed  Article  Google Scholar 

  6. Préaud E, Largeron N. Economic burden of non-cervical cancers attributable to human papillomavirus: a European scoping review. J Med Econ. 2013;16(6):763–76.

    PubMed  Article  Google Scholar 

  7. Pirotta M, Stein AN, Conway EL, Harrison C, Britt H, Garland S. Genital warts incidence and healthcare resource utilisation in Australia. Sex Trans Infect. 2010;86(3):181–6.

    Article  Google Scholar 

  8. Walboomers JM, Jacobs MV, Manos MM, Bosch FX, Kummer JA, Shah KV, et al. Human papillomavirus is a necessary cause of invasive cervical cancer worldwide. J Pathol. 1999;189(1):12–9.

    CAS  PubMed  Article  Google Scholar 

  9. Arrossi S, Temin S, Garland S, Eckert LON, Bhatla N, Castellsagué X, et al. Primary Prevention of Cervical Cancer: American Society of Clinical Oncology Resource-Stratified Guideline. J Glob Oncol. 2017;3(5):611–34.

    PubMed  PubMed Central  Article  Google Scholar 

  10. Ali H, Donovan B, Wand H, Read TRH, Regan DG, Grulich AE, et al. Genital warts in young Australians five years into national human papillomavirus vaccination programme: national surveillance data. Brit Med J. 2013;346:f2032.

    PubMed  Article  Google Scholar 

  11. Ali H, McManus H, O’Connor CC, Callander D, Kong M, Graham S, et al. Human papillomavirus vaccination and genital warts in young Indigenous Australians: national sentinel surveillance data. Med J Aust. 2017;206(5):204–9.

    PubMed  Article  Google Scholar 

  12. Arbyn M, Xu L, Simoens C, Martin-Hirsch PP. Prophylactic vaccination against human papillomaviruses to prevent cervical cancer and its precursors. Cochrane Database Syst Rev. 2018;5(5):Cd009069.

    PubMed  Google Scholar 

  13. Drolet M, Benard E, Perez N, Brisson M. Population-level impact and herd effects following the introduction of human papillomavirus vaccination programmes: updated systematic review and meta-analysis. Lancet (London, England). 2019;394(10197):497–509.

    Article  Google Scholar 

  14. Gertig DM, Brotherton JM, Budd AC, Drennan K, Chappell G, Saville AM. Impact of a population-based HPV vaccination program on cervical abnormalities: a data linkage study. BMC Med. 2013;11:227.

    PubMed  PubMed Central  Article  Google Scholar 

  15. Lei J, Ploner A, Elfström KM, Wang J, Roth A, Fang F, et al. HPV Vaccination and the Risk of Invasive Cervical Cancer. N Engl J Med. 2020;383(14):1340–8.

    CAS  PubMed  Article  Google Scholar 

  16. Global HPV vaccine introduction overview: projected and current national introductions, demonstration/pilot projects, gender-neutral vaccination programs, and global HPV vaccine introduction maps (2006–2022) 2019. Available from: https://path.azureedge.net/media/documents/GlobalHPVVaccineIntroOverview_Nov2019.pdf.

  17. Gottvall M, Larsson M, Hoglund AT, Tyden T. High HPV vaccine acceptance despite low awareness among Swedish upper secondary school students. Eur J Contracept Reprod Health Care. 2009;14(6):399–405.

    PubMed  Article  Google Scholar 

  18. Arbyn M, Xu L. Efficacy and safety of prophylactic HPV vaccines. A Cochrane review of randomized trials. Expert Rev Vaccines. 2018;17(12):1085–91.

    CAS  PubMed  Article  Google Scholar 

  19. Organization WH. Global strategy to accelerate the elimination of cervical cancer as a public health problem 2020. [Available from: https://www.who.int/publications/i/item/9789240014107.

  20. Brisson M, Bénard É, Drolet M, Bogaards JA, Baussano I, Vänskä S, et al. Population-level impact, herd immunity, and elimination after human papillomavirus vaccination: a systematic review and meta-analysis of predictions from transmission-dynamic models. Lancet Public Health. 2016;1(1):e8–17.

    PubMed  PubMed Central  Article  Google Scholar 

  21. Brotherton JM, Fridman M, May CL, Chappell G, Saville AM, Gertig DM. Early effect of the HPV vaccination programme on cervical abnormalities in Victoria, Australia: an ecological study. Lancet (London, England). 2011;377(9783):2085–92.

    Article  Google Scholar 

  22. Brabin L, Roberts SA, Stretch R, Baxter D, Chambers G, Kitchener H, et al. Uptake of first two doses of human papillomavirus vaccine by adolescent schoolgirls in Manchester: prospective cohort study. BMJ (Clinical research ed). 2008;336(7652):1056–8.

    Article  Google Scholar 

  23. Ogilvie G, Anderson M, Marra F, McNeil S, Pielak K, Dawar M, et al. A population-based evaluation of a publicly funded, school-based HPV vaccine program in British Columbia, Canada: parental factors associated with HPV vaccine receipt. PLoS Med  2010;7(5):e1000270.

    PubMed  PubMed Central  Article  Google Scholar 

  24. National HPV Program Register. HPV vaccination coverage 2012–2017. Melbourne: NHPVR; 2018.

  25. National HPV Program Register. National (Australia) HPV 3 dose vaccination coverage for males turning 15 years of age in 2017. 2017. Available from: http://www.hpvregister.org.au/research/coverage-data/HPV-Vaccination-Coverage-2017---Male.

  26. National HPV Program Register. National (Australia) HPV 3 dose vaccination coverage for all females turning 15 years of age, 2017. 2017. Available from: http://www.hpvregister.org.au/research/coverage-data/hpv-vaccination-coverage-2017only.

  27. Sisnowski J, Vujovich-Dunn C, Gidding H, Brotherton J, Wand H, Lorch R, Veitch M, Sheppeard V, Effler P, Skinner SR, Venn A, Davies C, Hocking J, Whop L, Leask J, Canfell K, Sanci L, Smith M, Kang M, Temple-Smith M, Kidd M, Burns S, Selvey L, Meijer D, Ennis S, Thomson C, Lane N, Kaldor J, Guy R. Differences in school factors associated with adolescent HPV vaccination initiation and completion coverage in three Australian states. Vaccine. 2021;39(41):6117–26. https://doi.org/10.1016/j.vaccine.2021.08.076. Epub 2021 Sep 4. PMID: 34493408.

  28. Population Attributable Risk (PAR). In: Kirch W, editor. Encyclopedia of Public Health. Dordrecht: Springer Netherlands; 2008. p. 1117–8.

  29. Mak DB, Bulsara MK, Wrate MJ, Carcione D, Chantry M, Efller PV. Factors determining vaccine uptake in Western Australian adolescents. J Paediatr Child Health. 2013;49(11):895–900.

    PubMed  Article  Google Scholar 

  30. Barbaro B, Brotherton JM. Assessing HPV vaccine coverage in Australia by geography and socioeconomic status: are we protecting those most at risk? Aust N Z J Public Health. 2014;38(5):419–23.

    PubMed  Article  Google Scholar 

  31. Barbaro B, Brotherton JM, Gertig DM. Human papillomavirus vaccination and cervical cancer screening by socioeconomic status, Victoria. Med J Aust. 2012;196(7):445.

    PubMed  Article  Google Scholar 

  32. Roberts SA, Brabin L, Stretch R, Baxter D, Elton P, Kitchener H, et al. Human papillomavirus vaccination and social inequality: results from a prospective cohort study. Epidemiol Infect. 2011;139(3):400–5.

    CAS  PubMed  Article  Google Scholar 

  33. Fisher H, Audrey S, Mytton JA, Hickman M, Trotter C. Examining inequalities in the uptake of the school-based HPV vaccination programme in England: a retrospective cohort study. J Public Health (Oxf). 2014;36(1):36–45.

    Article  Google Scholar 

  34. Spencer AM, Roberts SA, Brabin L, Patnick J, Verma A. Sociodemographic factors predicting mother’s cervical screening and daughter’s HPV vaccination uptake. J Epidemiol Community Health. 2014;68(6):571–7.

    PubMed  Article  Google Scholar 

  35. Sinka K, Kavanagh K, Gordon R, Love J, Potts A, Donaghy M, et al. Achieving high and equitable coverage of adolescent HPV vaccine in Scotland. J Epidemiol Commun Health. 2014;68(1):57–63.

    Article  Google Scholar 

  36. Feiring B, Laake I, Molden T, Cappelen I, Håberg SE, Magnus P, et al. Do parental education and income matter? A nationwide register-based study on HPV vaccine uptake in the school-based immunisation programme in Norway. BMJ Open. 2015;5(5):e006422.

    PubMed  PubMed Central  Article  Google Scholar 

  37. Agius PA, Pitts MK, Smith AM, Mitchell A. Human papillomavirus and cervical cancer: Gardasil vaccination status and knowledge amongst a nationally representative sample of Australian secondary school students. Vaccine. 2010;28(27):4416–22.

    PubMed  Article  Google Scholar 

  38. Larson HJ, Jarrett C, Eckersberger E, Smith DM, Paterson P. Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: a systematic review of published literature, 2007–2012. Vaccine. 2014;32(19):2150–9.

    PubMed  Article  Google Scholar 

  39. Robbins SC, Bernard D, McCaffery K, Skinner SR. 'It's a logistical nightmare!' Recommendations for optimising human papillomavirus school-based vaccination experience. Sex Health. 2010;7(3):271–8. https://doi.org/10.1071/SH09140. PMID: 20719214.

  40. Ross A, Kennedy AB, Holt E, Guyer B, Hou W, Hughart N. Initiating the first DTP vaccination age-appropriately: a model for understanding vaccination coverage. Pediatrics. 1998;101(6):970–4.

    CAS  PubMed  Article  Google Scholar 

  41. Yawn BPXZ, Edmonson L, Jacobson RM, Jacobsen SJ. Barriers to immunization in a relatively affluent community. J Am Board Fam Pract. 2000;13(5):325–32.

    CAS  PubMed  Google Scholar 

  42. Smith PJ, Stokley S, Bednarczyk RA, Orenstein WA, Omer SB. HPV vaccination coverage of teen girls: the influence of health care providers. Vaccine. 2016;34(13):1604–10.

    PubMed  PubMed Central  Article  Google Scholar 

  43. National HPV Program Register. Coverage data: Victorian Cytology Service. 2018 [cited 2019 December 21]. Available from: http://www.hpvregister.org.au/research/coverage-data.

  44. Australian Curriculum Assessment and Reporting Authority. ACARA Data Access Program. 2019. Available from: http://www.acara.edu.au/contact-us/acara-data-access.

  45. Australian Bureau of Statistics. 2033.0.55.001 – Census of population and housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2016. Canberra: ABS; 2016.

  46. Wand H, Ward J, Bryant J, Delaney-Thiele D, Worth H, Pitts M, et al. Individual and population level impacts of illicit drug use, sexual risk behaviours on sexually transmitted infections among young Aboriginal and Torres Strait Islander people: results from the GOANNA survey. BMC Public Health. 2016;16:600.

    PubMed  PubMed Central  Article  Google Scholar 

  47. Tiley K, White J, Andrews N, Tessier E, Ramsay M, Edelstein M. What school-level and area-level factors influenced HPV and MenACWY vaccine coverage in England in 2016/2017? An ecological study. BMJ Open. 2019;9(7):e029087.

    PubMed  PubMed Central  Article  Google Scholar 

  48. Brotherton JM, Winch KL, Chappell G, Banks C, Meijer D, Ennis S, et al. HPV vaccination coverage and course completion rates for Indigenous Australian adolescents, 2015. Med J Aust. 2019;211(1):31–6.

    PubMed  Article  Google Scholar 

  49. O’Brien ED, Bailie RS, Jelfs PL. Cervical cancer mortality in Australia: contrasting risk by Aboriginality, age and rurality. Int J Epidemiol. 2000;29(5):813–6.

    CAS  PubMed  Article  Google Scholar 

  50. Whop LJ, Garvey G, Baade P, Cunningham J, Lokuge K, Brotherton JM, et al. The first comprehensive report on Indigenous Australian women’s inequalities in cervical screening: A retrospective registry cohort study in Queensland, Australia (2000–2011). Cancer. 2016;122(10):1560–9.

    PubMed  Article  Google Scholar 

  51. Watson M, Lynch J, D’Onise K, Brotherton J. Barriers to better three-dose coverage with HPV vaccination in school-based programs. Aust N Z J Public Health. 2014;38(1):91–2.

    PubMed  Article  Google Scholar 

  52. O’Neill J, Newall F, Antolovich G, Lima S, Danchin M. Vaccination in people with disability: a review. Hum Vaccin Immunother. 2020;16(1):7–15.

    PubMed  Article  Google Scholar 

  53. O’Neill J, Elia S, Perrett KP. Human papillomavirus vaccine uptake in adolescents with developmental disabilities. J Intellect Dev Disabil. 2019;44(1):98–102.

    Article  Google Scholar 

  54. O’Neill J, Newall F, Antolovich G, Lima S, Danchin M. The uptake of adolescent vaccinations through the School Immunisation Program in specialist schools in Victoria. Australia Vaccine. 2019;37(2):272–9.

    PubMed  Article  Google Scholar 

  55. Mandal J, Ponnambath DK, Parija SC. Utilitarian and deontological ethics in medicine. Trop Parasitol. 2016;6(1):5–7.

    PubMed  PubMed Central  Article  Google Scholar 

  56. Brisson M, Kim JJ, Canfell K, Drolet M, Gingras G, Burger EA, et al. Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries. Lancet. 2020;395(10224):575–90.

    PubMed  PubMed Central  Article  Google Scholar 

  57. Australian Institute of Health and Welfare. Australian cancer incidence and mortality (ACIM). Canberra: AIHW; 2017.

  58. Rowe MP, Audra L, Stratton AJ, Yoost  JL. HPV vaccination among females with mental and physical limitation. Marshall J Med. 2017;3(2):8.

  59. Fisher H, Hickman M, Ferrie J, Evans K, Bell M, Yates J, Roderick M, Reynolds R, MacLeod J, Audrey S. Impact of new consent procedures on uptake of the schools-based human papillomavirus (HPV) vaccination programme. J Public Health (Oxf). 2022;44(1):199–206. https://doi.org/10.1093/pubmed/fdaa164. PMID: 32978614; PMCID: PMC8904199.

  60. Acampora A, Grossi A, Barbara A, Colamesta V, Causio FA, Calabrò GE, et al. Increasing HPV Vaccination Uptake among Adolescents: A Systematic Review. Int J Environ Res Public Health. 2020;17(21):7997.

    CAS  PubMed Central  Article  Google Scholar 

  61. Mavundza EJ, Iwu-Jaja CJ, Wiyeh AB, Gausi B, Abdullahi LH, Halle-Ekane G, et al. A Systematic Review of Interventions to Improve HPV Vaccination Coverage. Vaccines (Basel). 2021;9(7):687.

    Article  Google Scholar 

Download references

Acknowledgements

The study was conducted as part of the HPV Partnership Project (NHMRC grant number APP1132344), which was formed between researchers, the National HPV Vaccination Program Register, and the health departments of three states, New South Wales, Tasmania, and Western Australia to understand why gaps persist in the HPV vaccination school-based program.

Funding

The study was funded by NHMRC grant number APP1132344.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, C.V.D., H.W., J.S., R.L., S.R.S., J.B., M.V., V.S., P.E., H.G., A.V., C.D., J.H., L.W., J.L., K.C., L.S., M.S., M.K., M.T.S., M.K., S.B., L.S., D.M., S.E., C.T., N.L., J.K., and R.G.; methodology, H.W., J.B., H.G., and R.G.; formal analysis, C.V.D., H.W., H.G. and R.G.; data curation, J.S., R.L., D.M., S.E., C.T., N.L. and J.B.; writing—original draft preparation, C.V.D.; writing—review and editing, C.V.D., H.W., J.S., R.L., S.R.S., J.B., M.V., A.V., C.D., J.H., L.W., J.L., K.C., L.S., M.S., M.K., M.T.S., M.K., S.B., L.S., D.M., S.E., J.K. and R.G.; supervision, R.G., S.R.S., H.W. and J.K.; project administration, C.V.D. All authors read and approved the final manuscript.

Corresponding author

Correspondence to C. Vujovich-Dunn.

Ethics declarations

Ethics approval and consent to participate

All methods were performed in accordance with the Declaration of Helsinki and approved by the following ethical committees. Ethical approval was provided by the Human Research Ethics Committees of the University of New South Wales (HC17632), the Australian National University (2017/516), the University of Tasmania (1320/17), the Aboriginal Health and Medical Research Council of New South Wales (1320/17), the Aboriginal Health Council of Western Australia (818), and the Department of Health of Western Australia (RGS0000000456). The project performed secondary analyses of existing administrative datasets that are held by states and national statutory bodies. Individual consent was not required based on Sect. 2.3.10 of the NHMRC’s National Statement on Ethical Conduct in Human Research (2007).

Consent for publication

Not applicable.

Competing interests

JS was funded by an Australian Government Research Training Program Scholarship, LW was funded by the NHMRC Early Career Fellowship (#1142035), and MS was funded by NHRMC grant (APP1159491) Cancer Institute NSW. RG was funded by an NHMRC fellowship (GNT1124647) and is a co-investigator on a project which received funding from Seqirus [unrelated to this project]. KC reports she is co-PI of an investigator-initiated trial of cervical screening, "Compass", run by the VCS Foundation Australia, which is a government-funded not-for-profit charity. The VCS Foundation has received equipment and a funding contribution from Roche Molecular Diagnostics. She is also co-PI on a major implementation program "Elimination of Cervical Cancer in the Western Pacific" which will receive support from the Minderoo Foundation and the Frazer Family Foundation and equipment donations from Cepheid Inc. However, neither KC nor her institution has received direct funding from industry for these or any other research project. All other authors have no competing interest to declare.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

 Sample SAS code for calculating the population attributable risk, using school size as example variable.  

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Vujovich-Dunn, C., Wand, H., Brotherton, J.M.L. et al. Measuring school level attributable risk to support school-based HPV vaccination programs. BMC Public Health 22, 822 (2022). https://doi.org/10.1186/s12889-022-13088-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-022-13088-x

Keywords

  • HPV vaccines
  • Primary prevention
  • Cervical cancer
  • Immunisation programs
  • School-based
  • Health equity