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. 2021 Jun 7;18(6):e1003588. doi: 10.1371/journal.pmed.1003588

Human papillomavirus seroprevalence in pregnant women following gender-neutral and girls-only vaccination programs in Finland: A cross-sectional cohort analysis following a cluster randomized trial

Penelope Gray 1,*, Hanna Kann 2, Ville N Pimenoff 2,3,4, Tiina Eriksson 5, Tapio Luostarinen 6, Simopekka Vänskä 7, Heljä-Marja Surcel 8,9, Helena Faust 2, Joakim Dillner 2, Matti Lehtinen 2,4,7,10
Editor: Nicola Low11
PMCID: PMC8216524  PMID: 34097688

Abstract

Background

Cervical cancer elimination through human papillomavirus (HPV) vaccination programs requires the attainment of herd effect. Due to its uniquely high basic reproduction number, the vaccination coverage required to achieve herd effect against HPV type 16 exceeds what is attainable in most populations. We have compared how gender-neutral and girls-only vaccination strategies create herd effect against HPV16 under moderate vaccination coverage achieved in a population-based, community-randomized trial.

Methods and findings

In 2007–2010, the 1992–1995 birth cohorts of 33 Finnish communities were randomized to receive gender-neutral HPV vaccination (Arm A), girls-only HPV vaccination (Arm B), or no HPV vaccination (Arm C) (11 communities per trial arm). HPV16/18/31/33/35/45 seroprevalence differences between the pre-vaccination era (2005–2010) and post-vaccination era (2011–2016) were compared between all 8,022 unvaccinated women <23 years old and resident in the 33 communities during 2005–2016 (2,657, 2,691, and 2,674 in Arms A, B, and C, respectively). Post- versus pre-vaccination-era HPV seroprevalence ratios (PRs) were compared by arm. Possible outcome misclassification was quantified via probabilistic bias analysis. An HPV16 and HPV18 seroprevalence reduction was observed post-vaccination in the gender-neutral vaccination arm in the entire study population (PR16 = 0.64, 95% CI 0.10–0.85; PR18 = 0.72, 95% CI 0.22–0.96) and for HPV16 also in the herpes simplex virus type 2 seropositive core group (PR16 = 0.64, 95% CI 0.50–0.81). Observed reductions in HPV31/33/35/45 seroprevalence (PR31/33/35/45 = 0.88, 95% CI 0.81–0.97) were replicated in Arm C (PR31/33/35/45 = 0.79, 95% CI 0.69–0.90).

Conclusions

In this study we only observed herd effect against HPV16/18 after gender-neutral vaccination with moderate vaccination coverage. With only moderate vaccination coverage, a gender-neutral vaccination strategy can facilitate the control of even HPV16. Our findings may have limited transportability to other vaccination coverage levels.

Trial registration

ClinicalTrials.gov number NCT00534638, https://clinicaltrials.gov/ct2/show/NCT00534638.

Author summary

Why was this study done?

  • High-risk human papillomavirus (HPV) infection is a necessary cause of cervical cancer in females.

  • HPV vaccination targeting high-risk HPV types 16 and 18 has been implemented internationally.

  • Achieving herd protection for HPV16 may require greater than 80% girls-only vaccination coverage, a level that has not been achievable in many countries.

  • We evaluate whether gender-neutral or girls-only HPV vaccination results in HPV16 and HPV18 herd protection when the vaccination coverage is only moderate (40%–50%).

What did the researchers do and find?

  • We implemented a community-randomized trial of gender-neutral versus girls-only versus no HPV vaccination of young adolescents in 2007–2010, with 11 communities in each arm. Vaccination coverage was implemented with moderate coverage (40%–50%) at the community level.

  • We evaluated the herd effect created by the different vaccination strategies by measuring the cumulative incidence of vaccine-protected HPV types in 8,022 young unvaccinated pregnant females (under 23 years old), comparing the time periods 2005–2010 (pre-vaccination) and 2011–2016 (post-vaccination).

  • An HPV16 herd effect, that is, a reduction in cumulative incidence among the unvaccinated females, was only observed in communities where gender-neutral vaccination had been implemented.

What do these findings mean?

  • Achieving a vaccination coverage of above 80%, which is required to achieve herd effect against HPV16, may be unrealistic in some populations. Implementing gender-neutral HPV vaccination provides a solution to this problem as the vaccination coverage threshold required to provide herd effect to unvaccinated females is lower.

  • Our study finds that gender-neutral vaccination provides stronger herd effect than girls-only vaccination in the setting of moderate vaccination coverage. However, these findings are limited to this setting and are not readily generalizable to settings with high (>80%) vaccination coverage.

Introduction

The World Health Organization has called for the elimination of cervical cancer as a public health problem [1]. To this end, the WHO has developed a global strategy requiring every country globally to achieve 90% human papillomavirus (HPV) vaccination of girls by the age of 15 years by the year 2030 [2]. However, although some countries such as Scotland have achieved 90% coverage, achieving this globally may be a near impossible challenge [3,4]. Present vaccination coverage levels [5] are notably below the 80% vaccination coverage that is required for the eradication of vaccine-targeted HPV types [6], and herd effect among unvaccinated individuals is needed.

HPV vaccines provide not only strong direct protection but also herd effect/herd protection, also known as herd immunity (i.e., indirect protection to unvaccinated individuals) due to assortative transmission of the HPVs [710]. Modeling studies have suggested that already low to moderate vaccination coverage inclusion of boys provides incremental herd effect to unvaccinated girls [6,9,11,12]. In our unique community-randomized HPV16/18 vaccination trial, the herd effect/herd immunity created has been measured as the degree of decrease in HPV incidence/prevalence in unvaccinated women [7,13,14]. We found the predicted herd effect against vaccine-targeted HPV18, and cross-protection against HPV types 31, 33, 35, and 45, when vaccination coverage was approximately 50% [7,13,14]. In populations implementing girls-only vaccination, notable herd effect against HPV16 (the most oncogenic and most common HPV type) has only been observed when the vaccination coverage was high [1517]. This is probably due to the high basic reproduction number (R0) of HPV16 compared to other HPV types [17], and may depend also on the method of identifying HPV occurrence (one-time PCR positivity or seropositivity, i.e., prevalence or cumulative incidence).

We performed population-based HPV analysis to evaluate the herd effect created by gender-neutral or girls-only vaccination following our community-randomized trial in the instance of low to moderate vaccination coverage. In the previous reports of this trial, the herd effect was evaluated using transitory HPV PCR positivity in study participants when they were aged 18 and/or 22 years; although notable HPV18 herd effect was observed, no HPV16 herd effect was found [12,13,18]. To provide assurance that the lack of HPV16 herd effect was not due to the methodological approach, we then nested a cross-sectional cohort within the community-randomized trial. We then estimated HPV16 seroprevalence (cumulative HPV16 incidence) over time using pre-and post-vaccination-era sera from unvaccinated women under the age of 23 years and resident in the communities with gender-neutral or girls-only vaccination strategies. Possible clearance of an ecological niche by HPV16/18 vaccination is also now described as the natural counterpart to the serology-based type-replacement study concerning non-vaccine HPV types [18].

Methods

Study design

A population-based, community-randomized HPV vaccination trial was conducted among female and male 1992–1995 birth cohorts between 2007 and 2010 [19]. The trial was originally designed to guide evidence-based decision-making regarding national HPV vaccination policy [20,21], by testing the primary hypothesis of difference in the creation of herd effect by gender-neutral versus girls-only HPV vaccination strategies. Thirty-three geographically distinct Finnish communities located a minimum of 50 km from the next nearest community (or 35 km in the case of the 5 communities from the Helsinki metropolitan area) were included in the trial. To increase study power, the coefficient of variation, Ks (Ks = 0.13), between communities was minimized by first stratifying the communities by previously ascertained HPV16/18 seroprevalence [22] into those with low, moderate, and high seroprevalence. From these 3 strata, the communities were then randomized using a random number generator to 3 trial arms: In Arm A communities, 90% of girls and boys received HPV vaccination, and 10% of girls and boys received hepatitis B virus (HBV) vaccination; in Arm B communities, 90% of girls received HPV vaccination, and 10% of girls and all boys received HBV vaccination; in Arm C communities, all girls and boys received HBV vaccination.

In total, 80,272 Finnish- or Swedish-speaking girls and boys in the 1992–1995 birth cohorts were identified via the Finnish Population Register Centre as being resident in the 33 trial communities. Out of this group, 20,513 girls and 11,662 boys participated in the trial with parental/guardian informed consent. The study was partially blinded to all Arm A study participants and all female Arm B participants. Vaccination took place from 2007 to 2010, when the participants were aged 12–15 years, with 99.4% of participants receiving all 3 doses of the allocated vaccine (the bivalent HPV vaccine Cervarix or the HBV vaccine Engerix-B). The mean community-level vaccination coverage acquired via this vaccination was 47.1% in Arm A communities and 45.8% in Arm B communities among girls from the 1992–1995 birth cohorts (standard deviation [SD] = 9.4% and 6.6%, respectively). In Arm A communities the vaccination coverage acquired among boys from the 1992–1995 birth cohorts was 19.5% (SD = 7.1%) [19,20].

The creation of herd effect by different HPV16/18 vaccination strategies over time was estimated via a nested cross-sectional cohort study [23] of all pregnant women under the age of 23 years who were resident in the 33 trial communities from 2005 until the end of 2016. Their serum samples were extracted from a population-representative biobank, the Finnish Maternity Cohort (FMC) [18,21]. The FMC biobank houses 2 million serum samples obtained from approximately all 1 million pregnant Finnish women between 1983 and 2016 for screening of congenital infections. The participating women provided informed consent at the maternity clinic to have their samples stored for research purposes by the FMC biobank; 96% of women consented.

FMC participants eligible for this study were under the age of 23 years at the time of sample donation, first-time donators to the FMC, resident in 1 of the 33 trial communities, and HPV unvaccinated [18]. In Finland, every citizen (or person resident for greater than 3 months) is given a unique personal identification number at birth (or shortly after arrival into the country). HPV vaccination status was confirmed by linkage via the participants personal identification number with the national HPV vaccination trial registry both prior to and after sample extraction. For the birth cohorts eligible to receive HPV vaccination via the Finnish national vaccination program (1998 and younger birth cohorts), HPV vaccination status was ascertained by manually scrutinizing participants’ HPV antibody levels for titers indicative of HPV vaccination (i.e., multiple-fold those acquired via natural infection for HPV16 and HPV18).

The eligible participants for the serosurvey came from the 1982 and younger birth cohorts. The 1992 to 1995 birth cohorts were exposed to community-level vaccination via the community-randomized trial intervention, and the 1998 and younger birth cohorts were exposed to community-level HPV vaccination via the Finnish national HPV vaccination program initiated in late 2013 (Fig 1 and S1 Fig). The sampling time frame was divided into the pre-vaccination period (2005–2010) and the post-vaccination period (2011–2016). All the pregnant females under the age of 23 years at the time of sample donation from each of the trial communities were included, totaling 8,022 females.

Fig 1. Lexis diagrams depicting the community-level exposure of the adolescent population to direct and indirect effects of the cluster-randomized human papillomavirus vaccination trial by birth cohort and study arm.

Fig 1

hite bars represent the birth cohorts with no vaccination, and the purple (trial vaccination) and orange (national vaccination) bars represent post-vaccination birth cohorts. The blue dashed lines indicate the sampling years and ages of this study. The colored fill of the symbols indicates the proportion of each type of vaccination that took place at that time point and age per birth cohort.

Data regarding self-reported maternal smoking among women under the age of 23 years and resident in the 33 communities between 2005 and 2016 were collected from the Finnish Medical Birth Register, and used as a surrogate of community-level risk-taking behaviors. To define the core group with high contact rate, we identified herpes simplex virus type 2 (HSV-2) seropositive women [18]. Data on community-specific vaccination coverage over each calendar year were collected from the HPV trial registry for the birth cohorts exposed to the community-randomized trial and from the Finnish vaccination register for the birth cohorts exposed to the Finnish national HPV vaccination program.

This study is reported in accordance to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist).

Ethics

The community-randomized HPV-040 study obtained permissions from the Ethical Review Board of Pirkanmaa Hospital District (R07113M 14.6.2007). The FMC steering committee granted permission for the linkage and use of the serum samples. No harm was caused to the cohorts.

Laboratory analyses

The serum samples were analyzed for the presence of IgG antibodies to HPV types 6, 11, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, and 73 and HSV-2 using multiplexed heparin-bound pseudovirion (and HSV-2 glycoprotein gG2) Luminex assay [24]. Seropositivity cutoff levels were established with a negative control panel of serum samples from 191 children ≤12 years old (mean age = 4.7 years) (S1 Text).

Statistical analyses

The primary hypothesis of this study was that HPV16/18 vaccination created a herd effect (in the HPV-040 and type-replacement study protocols, this was called “indirect effect” or “ecological niche formation”) over time. In this study, herd effect is defined and measured as the degree of decrease in HPV cumulative incidence (unattributable to random or systematic error) among unvaccinated individuals in the post-vaccination era. To investigate the herd effect (indirect effect) of increasing community-level HPV16/18 vaccination during the study period (via a gender-neutral or girls-only vaccination strategy), we calculated the absolute seroprevalence of vaccine-targeted HPV types 16, 18, and 16/18 (combined), and vaccine-cross-protected HPV types 31, 33, 35, 45, and 31/33/35/45 (combined). This was calculated for the pre- and post-vaccination eras, 2005–2010 and 2011–2016, respectively. In the case of the former, the participants who had donated the sera were likely to have been unexposed to the indirect effects of HPV vaccination, whereas in the case of the latter, the participants may have been under herd effect [14,19,20].

The degree of clustering of HPV16/18 and HPV16/18/31/33/35/45 seropositivity was assessed by calculation of the intracluster correlation coefficient from the pre-vaccination-era data (from 2005 to 2010) using Fleiss and Cuzick’s estimator in combination with Zou and Donner’s modified Wald test to compute the 95% confidence intervals [25,26].

The exposure in this study is defined as exposure to the herd effects (indirect effects) of HPV16/18 vaccination due to residing at the time of sample donation in one of the communities of the community-randomized trial. Thus, to evaluate the extent of exposure in the study population of pregnant females under the age of 23 years, the birth-cohort-, community-, and year-specific vaccination coverage was calculated. From this, the community-specific vaccination coverage by year among the study population was then calculated as the birth-cohort-weighted vaccination coverage by gender, weighted by the proportion of participants from each birth cohort found in each year of the study among the study population of pregnant females. We also calculated HSV-2 seroprevalence to assess changes in the occurrence of sexually transmitted infections between the pre- and post-vaccination eras. Calendar-time-specific absolute seroprevalence was calculated stratified by Arms A, B, and C of the community-randomized trial. The accompanying 95% confidence intervals were calculated using the Agresti–Coull method [27].

To further assess the indirect effect of community-level vaccination in the post-vaccination era, we estimated within-arm seroprevalence ratios (PRs) comparing the post- to pre-vaccination HPV-type-specific seroprevalence (for HPV types 16, 18, 31, 33, 35, 45, and 16/18 combined) using a log binomial generalized estimating equation (GEE) model to take account of within-arm clustering. HPV-type-specific seroprevalence was not directly compared between the arms as stated in the pre-analysis plan (S2 Text), as statistically significant differences were found between the arms at baseline prior to any HPV vaccination. To take account of possible confounding, all estimates were adjusted for community-level self-reported maternal smoking, as a surrogate of community-level risk-taking behaviors. To investigate the effect of core group membership (a possible effect modifier) on the indirect effect, the secondary outcome of the study, we stratified the estimates by HSV-2 seropositivity.

To estimate the overall herd effect (the indirect effect) of gender-neutral and girls-only HPV vaccination compared to the counterfactual scenario, we further calculated the between-arm ratio of PRs, comparing the within-arm PR (adjusted for community-level maternal smoking) of Arm A or B (the intervention arms) to the PR of the control Arm C. The accompanying 95% confidence intervals were calculated according to the methodology of Altman and Bland [28].

Systematic outcome misclassification of the serological assay was quantified and corrected for assuming non-differential bias of the within- and between-arm estimates via probabilistic bias analysis [29]. Previously obtained estimates of test sensitivity and specificity were used at the outset (S1 Table) [30], assuming a constant probability distribution. If these prior estimates proved incompatible with the observed data, then a uniform probability density ranging from 0 to 1 was specified, to obtain all plausible values of the sensitivity or specificity compatible with the observed data. The resultant range of plausible values for the given HPV-type-specific sensitivity or specificity was then assumed, with a uniform probability density ranging from the given minimum to maximum value. The results from this sensitivity analysis were then used to quantify misclassification in the primary analysis.

All statistical analyses were conducted using the R statistical software package (version 3.6.0.).

Results

Baseline characteristics of the study population

In total, all 8,022 HPV-unvaccinated pregnant females under the age of 23 years who were resident in one of the 33 trial communities and had been invited to donate a blood sample to the FMC between the years 2005 and 2016 were identified. An additional 3,498 females were initially found to be ineligible due to being HPV vaccinated. In total, 4,007 participants were from the era preceding completion of vaccination (2005–2010), and 4,015 were from the post-vaccination era (2011–2016). Participants were excluded from the statistical analyses owing to HPV vaccination (N = 49) or being aged >22 years at sample donation (N = 436). In total, 7,531 women were included: 1,322, 1,289, and 1,304 from the pre-vaccination-era Arm A, B, and C communities, respectively, and 1,247, 1,158, and 1,211 from the same post-vaccination-era communities (Fig 2). The intracluster correlation coefficient was consistently low, at 0.007 for HPV16/18 seropositivity and 0.005 for HPV16/18/31/33/35/45 seropositivity (S2 Table).

Fig 2. Flow chart of the cross-sectional cohort study nested in the Finnish community randomized human papillomavirus (HPV) vaccination trial with stepwise subsequent exclusions.

Fig 2

1The arms are the trial arms from the cluster (community) randomized trial of HPV vaccination strategy, conducted in 2007–2010.2Includes all females aged 3–22 years who were resident in the communities specified as of the 31 December 2005 (data extracted from Statistics Finland).

The participants’ age distributions in the pre-vaccination and post-vaccination eras were comparable, with the majority being 18 to 22 years old (S3 Table). The HSV-2 seroprevalence was materially similar between the arms, but somewhat higher in the pre-vaccination era as compared to the post-vaccination era (17.8% and 15.0%, respectively) (Fig 3). Community-level self-reported smoking was consistently higher in the control Arm C communities than in the gender-neutral vaccination Arm A and girls-only vaccination Arm B communities (S3 Table). The community-specific vaccination coverage among the eligible female birth cohorts for this study was negligible in the pre-vaccination era, from 2005 until 2010, and increased in the post-vaccination era in the intervention arm communities (from 5.6% to 52.5% in Arm A, and from 6.3% to 46.7% in Arm B) (Fig 4).

Fig 3. Type-specific human papillomavirus (HPV) and herpes simplex virus type 2 (HSV-2) seroprevalence (%) among unvaccinated females under the age of 23 years by intervention strategy: Gender-neutral vaccination (Arm A), girls-only vaccination (Arm B), and control vaccination (Arm C).

Fig 3

Type-specific seroprevalence is stratified by time period of sample donation (pre-vaccination era, 2005–2010; post-vaccination era, 2011–2016).

Fig 4. Evaluation of human papillomavirus (HPV) vaccination coverage in the study population: Community-specific birth-cohort-weighted vaccination coverage of the consecutive community-randomized trial and national girls-only vaccination program.

Fig 4

Exposure to the indirect effects of HPV16/18 vaccination is defined as residing at the time of sample donation in one of the community-randomized HPV vaccination trial communities. Each row represents a trial community, and each column a year of the follow-up period. The community-specific vaccination coverage is calculated for pregnant females under the age of 23 years and includes vaccination of 12- to 15-year-old males and females in 2007–2010, and the national girls-only vaccination program launched in late 2013.

HPV seroprevalence by vaccination era

In the pre-vaccination era, HPV16/18 seroprevalence was high: 29.7%, 29.6%, and 26.8%, respectively, in the Arm A, B, and C communities. In the post-vaccination era, HPV16/18 seroprevalence was somewhat decreased (23.6%) in the gender-neutral vaccination Arm A communities (Fig 3; S4 Table). Notably, the HPV16 seroprevalence was decreased in the Arm A communities in the post-vaccination era compared to the pre-vaccination era (17.4% versus 22.1%). No decrease in HPV16 seroprevalence was noted in the girls-only vaccination Arm B or control C communities (Fig 3; S4 Table).

Within-arm post- versus pre-vaccination-era HPV PRs

The within-arm HPV16/18 PR comparing the post- to the pre-vaccination era was notably decreased in Arm A. The HPV16/18 estimate was significantly somewhat decreased in the gender-neutral vaccination Arm A (PR16/18 = 0.80, 95% CI 0.74–0.87), whereas in the girls-only vaccination Arm B and control Arm C, no significant reductions were noted (PR16/18 = 0.98, 95% CI 0.85–1.12, in Arm B; PR16/18 = 0.91, 95% CI 0.81–1.03, in Arm C) (Table 1). The HPV16 PR specifically was decreased in Arm A (PR16 = 0.79, 95% CI 0.72–0.87). No corresponding decrease was observed in Arms B or C (PR16 = 1.09, 95% CI 0.91–1.32, in Arm B; PR16 = 1.01, 95% CI 0.86–1.20, in Arm C) (Table 1). After applying probabilistic bias analysis to correct for outcome misclassification, the within-arm HPV16/18 and HPV16 PR estimates in Arm A were found to be further decreased (PR16/18 = 0.66, 95% CI 0.10–0.85, and PR16 = 0.64, 95% CI 0.09–0.86, respectively). Also, the within-arm PR estimate for HPV18 was significantly decreased in the gender-neutral vaccination Arm A after accounting for the error due to outcome misclassification (PR18 = 0.72, 95% CI 0.21–0.96) (Table 1).

Table 1. Post- versus pre-vaccination HPV-type-specific adjusted seroprevalence ratio (PR) among unvaccinated Finnish females aged under 23 years.

HPV type Post- versus pre-vaccination-era PR (95% CI)
Arm A (N = 1,247 versus 1,322) Arm B (N = 1,158 versus 1,289) Arm C (N = 1,211 versus 1,304)
Accounting for random error
16 0.79 (0.72–0.87) 1.09 (0.91–1.32) 1.01 (0.86–1.20)
18 0.86 (0.70–1.06) 0.96 (0.74–1.24) 0.89 (0.70–1.13)
16/18 0.80 (0.74–0.87) 0.98 (0.85–1.12) 0.91 (0.81–1.03)
31 0.90 (0.79–1.01) 0.86 (0.73–1.02) 0.72 (0.57–0.91)
33 1.05 (0.88–1.26) 0.94 (0.77–1.14) 0.81 (0.63–1.03)
35 0.70 (0.52–0.94) 0.98 (0.64–1.51) 0.77 (0.58–1.01)
45 0.89 (0.69–1.14) 1.01 (0.76–1.36) 0.90 (0.64–1.26)
Accounting for random error and systematic error
16 0.64 (0.09–0.86) 1.19 (0.98–3.70) 1.07 (0.89–1.85)
18 0.72 (0.21–0.96) 0.89 (0.39–1.12) 0.79 (0.21–1.03)
16/18 0.66 (0.10–0.85) 0.92 (0.44–1.07) 0.84 (0.24–1.01)
31 0.79 (0.20–1.00) 0.75 (0.15–0.97) 0.55 (0.07–0.78)
33 1.14 (0.86–2.73) 0.85 (0.31–1.13) 0.66 (0.15–0.94)
35 0.52 (0.07–0.83) 0.90 (0.44–1.25) 0.59 (0.10–0.91)
45 0.73 (0.19–1.06) 1.01 (0.78–1.33) 0.79 (0.25–1.13)

Comparisons are between 2 time periods of sample donation (2011–2016, post-vaccination era, versus 2005–2010, pre-vaccination era), stratified by intervention Arm A (gender-neutral HPV vaccination), Arm B (girls-only HPV vaccination), and Arm C (control vaccination), accounting for random error and accounting for random error and systematic error due to outcome misclassification. The estimates corrected for random error only are adjusted for community-level smoking. Corresponding unadjusted estimates are displayed in S5 Table.

The HPV35 PR estimate was significantly decreased in the gender-neutral vaccination Arm A (PR35 = 0.70, 95% CI 0.52–0.94; Table 1). However, this finding appeared to be essentially replicated in the control Arm C (PR35 = 0.77, 95% CI 0.58–1.01; Table 1). No decrease in HPV35 seroprevalence was observed in the girls-only vaccination Arm B (PR35 = 0.98, 95% CI 0.64–1.51). HPV31 was non-significantly slightly decreased in both the gender-neutral vaccination Arm A and the girls-only vaccination Arm B (PR31 = 0.90, 95% CI 0.79–1.01, in Arm A; PR31 = 0.86, 95% CI 0.73–1.02, in Arm B), but was further decreased in the control Arm C with no HPV vaccination (PR31 = 0.72, 95% CI 0.57–0.91). HPV33 was not decreased in Arm A (PR33 = 1.05, 95% CI 0.88–1.26), while it approximately stayed the same in Arm B (PR33 = 0.94, 95% CI 0.77–1.14) and non-significantly decreased slightly in Arm C (PR33 = 0.81, 95% CI 0.63–1.03). On the other hand, HPV45 was non-significantly marginally decreased in Arm A (PR45 = 0.89, 95% CI 0.69–1.14), approximated the null in Arm B (PR45 = 1.01, 95% CI 0.76–1.36), and in Arm C was decreased in a similar manner as in Arm A (PR45 = 0.90, 95% CI 0.64–1.26) (Table 1).

The HPV16 PR estimate was also noticeably decreased among the HSV-2 seropositive individuals in the gender-neutral vaccination Arm A (PR16 = 0.64, 95% CI 0.50–0.81). Most estimates for vaccine-protected HPV types were also decreased among the HSV-2 seropositive individuals, especially in Arm A (PR31 = 0.74, 95% CI 0.53–1.02; PR35 = 0.57, 95% CI 0.37–0.88; PR45 = 0.64, 95% CI 0.37–1.08), albeit sometimes with borderline statistical significance. The findings for HPV31 and HPV45 were, however, replicated in the control Arm C (PR31 = 0.64, 95% CI 0.42–0.98; PR45 = 0.69, 95% CI 0.37–1.30) (S6 Table).

Between-arm comparison of the post- versus pre-vaccination-era PRs

To account for possible secular trends, between-arm comparisons of the within-arm post- versus pre-vaccination-era PRs were made, comparing the ratios from HPV vaccination arms to the ratios from the control Arm C. The HPV16 ratio of PRs (RPR), remained decreased when comparing the gender-neutral vaccination Arm A to the control Arm C (RPR16 = 0.78, 95% CI 0.64–0.95) (Fig 5).

Fig 5. Ratio of human papillomavirus (HPV) seroprevalence ratios (PRs) comparing Arm A/B to Arm C.

Fig 5

Arm-specific PRs comprise post-vaccination to pre-vaccination-era HPV PRs among pregnant unvaccinated Finnish females, aged under 23 years, and adjusted for community-level maternal smoking. RPR, ratio of seroprevalence ratios.

Discussion

We nested a cross-sectional cohort within a population-based, community-randomized HPV16/18 vaccination trial to estimate changes over time in HPV16/18 seroprevalence created by gender-neutral or girls-only vaccination strategies, using pre- and post-vaccination-era sera from unvaccinated women resident in the trial communities. The HPV16 and HPV18 seroprevalence was somewhat decreased in young unvaccinated women after gender-neutral vaccination. This was observed although the vaccination coverage was only moderate to low. Most importantly, a degree of partial herd effect against HPV16 was observed over time within the gender-neutral vaccination arm, when compared to the counterfactual control arm, and within the HSV-2 seropositive core group, representing those with high contact rate. Girls-only HPV vaccination with moderate vaccination coverage did not result in any notable HPV16 herd effect.

The level of vaccination coverage required for herd effect is a function of a given HPV type’s basic reproduction number. This in turn is a function of the effective transmission rate and the mean duration of infection, which for HPV16 is especially long. Thus, the vaccination coverage required to achieve herd effect against HPV16 is expected to be high, higher than for other HPV types [14], and for girls-only vaccination this indeed seems to be the case [16]. Furthermore, the predicted herd effect is 25% to 50% greater for a gender-neutral than for a girls-only vaccination scenario [23]. Our study provides empirical evidence that when vaccination coverage is suboptimal, a gender-neutral vaccination strategy optimizes HPV16 herd effect and thus effectiveness of vaccination.

This observation is of major importance, if the call for action to eliminate cervical cancer is realistically going to be achieved. The gender-neutral vaccination strategy, with its sturdier impact on both HPV16 and HPV18, may assist in overcoming the obstacle of suboptimal girls-only vaccination coverage.

Apart from HPV16 being the most oncogenic HPV type, both dynamic transmission models and randomized trials have suggested that HPV16 is the most difficult to achieve herd protection against [14,17]. The vaccination coverage required to achieve herd protection against a given vaccine-protected type in addition to being strategy-dependent is also population-dependent [17]. The observation of a degree of partial HPV16 herd effect also in the core group following gender-neutral vaccination is reassuring, since modeling studies have suggested that the existence of the core group defies creation of herd effect [17]. When using PCR for the determination of current HPV infections, and concomitant Chlamydia trachomatis infection as a proxy of sexual risk-taking behavior, only HPV18 herd effect has been observed among the core group [31]. Whereas the seroprevalence comparisons documented a HPV16 herd effect in those with ‘ever’ core group membership, with HSV-2 seropositivity as the proxy. Thus, implementing a gender-neutral vaccination strategy is likely to deliver also on targets of equity in eliminating cervical cancer.

Previously, when following up the 1992–1995 birth cohorts of our community-randomized trial, no evidence of HPV16 herd effect among unvaccinated females was observed with PCR-defined endpoints [13]. DNA positivity as identified by one-time PCR-positivity is not a measure of cumulative infection and is also subject to outcome misclassification owing to its inability to distinguish persistent infections from transient depositions [32]. The resulting suboptimal specificity probably biased the previous estimates of HPV16/18 herd effect [13], and likely resulted in an underestimation of the true effects.

Sensitivity analyses assuming that serology has imperfect sensitivity to identify cumulative HPV exposure found that the degree of misclassification was HPV type specific. Furthermore, the previous validation methods [30] may have underestimated the true specificity. The remaining misclassification biased the estimates towards the null point. The previously reported sensitivity estimates were particularly low for HPV18. After quantifying and correcting for this bias, the HPV18 PR estimates were in line with earlier PCR-based observations of HPV18 herd effect after gender-neutral vaccination [13].

This study is limited by the imperfect ability of HPV serology to identify all cumulative HPV infection. However, HPV antibodies are a measure of persistent infection, thus by identifying cumulative infection by seroconversion, we identify women with true persistent HPV infection and exclude the apparent issue of the absence of HPV seroconversion in a proportion of women who have had only an HPV deposition.

Earlier studies were restricted to the birth cohorts that participated in the community-randomized trial [13]. We now also included females from the unvaccinated birth cohorts, 1996–1997, subsequent to the trial cohorts. Because HPV is a sexually transmitted virus, HPV transmission moves in the direction of the older to younger birth cohorts. Thus, the herd effect was expected to be stronger in the younger vaccinated cohorts [14]. Probably the older vaccinated male and female 1992–1995 birth cohorts have conferred indirect protection to the subsequent birth cohorts in the gender-neutral vaccination arm, due to the disruption in HPV transmission [33].

This is to our knowledge the only serosurvey among unvaccinated females following a community-randomized trial of different vaccination strategies. A previous serosurvey conducted in Australia among unvaccinated males to evaluate the first-order herd effect of girls-only vaccination found somewhat decreased HPV16/18 seropositivity in its post-vaccination era [34]. However, males seroconvert following HPV infections at lower rates than females, thus resulting in a possible underestimation of the true reduction in infection prevalence [35].

This study is strengthened by its utilization of the Finnish infrastructure of population-based intervention cohorts, biobanks, and registries, linkable via unique personal identification numbers. Our extraction of serum samples from all eligible participants in the population-based FMC [21] provided a sufficient population-representative sample size to evaluate vaccination-strategy-specific differences in HPV seroprevalence and account for random error. Further to this, our sampling of only pregnant females under 23 years at the time of sample donation captures the age distribution at which the HPV incidence curve peaks and the demographic most at risk.

This study may be limited in its generalizability, as the average age of mothers at first live birth in Finland is approximately 29 years [36]. It is possible that our study population of pregnant females under 23 years have above-average sexual risk-taking behaviors and lifetime risk of acquiring HPV. Our results may have incomplete transportability to populations that have differing baseline risk and sexual network structures This study is also limited to the setting of moderate vaccination coverage; therefore, the findings are not generalizable to scenarios with greater vaccination coverage. Furthermore, the findings may also have incomplete generalizability to a scenario with more consecutively vaccinated birth cohorts and a longer period of time between vaccination initiation and follow-up. Given our inclusion criteria in this study, it is also possible that participants may have moved between communities between the commencement of sexual activity and sample donation, which may introduce some bias in our estimates. However, given that the participants were all pregnant females under the age of 23 years, it is possible that they are the portion of source population that are least likely to move to a new community.

It may also be possible that changes over time in the sexual network or risk-taking behavior have altered HPV seroprevalence even in the absence of vaccination. The observed changes in HSV-2 seroprevalence could conceivably be interpreted as evidence of this. However, HSV-2 epidemiology has globally been undergoing complex changes in recent decades, with HSV-1 increasing and HSV-2 decreasing as the main cause of genital herpes infections [37]. Therefore, the observed decrease in HSV-2 seropositivity over time is not entirely unexpected and may be independent of any changes in HPV incidence over the time frame. However, with respect to this, our study is strengthened by its design, as the within-arm seroprevalence comparisons in Arm C, where no HPV vaccination was applied, provided us with a counterfactual estimate to tackle such possible secular trends.

Our results suggest that when HPV vaccination coverage is moderate, only gender-neutral vaccination establishes herd effect against HPV16 and HPV18 among unvaccinated females. This finding supports the implementation of a gender-neutral HPV vaccination policy to achieve optimal vaccine effectiveness when obtaining a girls-only vaccination coverage of 90% is impossible.

Supporting information

S1 Checklist. STROBE checklist.

(DOCX)

S1 Fig. Lexis diagrams depicting the vaccinated cohorts and vaccination coverage among the eligible birth cohorts of the study population, by arm and gender.

(a) Among females; (b) among males.

(DOCX)

S2 Fig. Type-specific human papillomavirus (HPV) seroprevalence (%) among unvaccinated females under the age of 23 years by vaccination strategy—gender-neutral vaccination (Arm A), girls-only vaccination (Arm B), and control vaccination (Arm C)—and time period of sample donation (pre-vaccination era, 2005–2010, and post-vaccination era, 2011–2016).

(DOCX)

S3 Fig. Ratio of HPV seroprevalence ratios (RPR) comparing Arm A/B to Arm C.

Arm-specific PRs comprise post-vaccination to pre-vaccination-era HPV seroprevalence ratios among pregnant unvaccinated Finnish females aged under 23 years old, and are adjusted for community-level maternal smoking.

(DOCX)

S1 Table. Sensitivity and specificity parameters of pseudovirion-based serology in measuring cumulative HPV exposure used in the probabilistic bias analysis.

(DOCX)

S2 Table. Intracluster correlation coefficient (ICC) of any human papillomavirus (HPV) type seropositivity among pregnant females donating sera during the pre-vaccination era, 2005–2010.

HSV-2, herpes simplex virus type 2.

(DOCX)

S3 Table. Characteristics of the study population after exclusions owing to ineligibility.

(DOCX)

S4 Table. Absolute HPV-type-specific seroprevalence among unvaccinated pregnant Finnish women stratified by trial arm and vaccination era (2005–2010 is defined as the “pre-vaccination era” and 2011–2016 as the “post-vaccination era”), and additionally by HSV-2 seropositivity.

(DOCX)

S5 Table. Unadjusted HPV-type-specific seroprevalence ratio (PR) among unvaccinated Finnish females comparing the post-vaccination era to the pre-vaccination era.

Comparisons are between 2 time periods of sample donation (2011–2016, post-vaccination era, versus 2005–2010, pre-vaccination era), stratified by intervention Arm A (gender-neutral HPV vaccination), Arm B (girls-only HPV vaccination), and Arm C (control vaccination).

(DOCX)

S6 Table. Adjusted seroprevalence ratio (PR) of HPV seropositivity by HPV type among pregnant, unvaccinated Finnish females under the age of 23 years by study arm (gender-neutral vaccination Arm A, girls-only vaccination Arm B, or control Arm C), comparing time period of sample donation (post-vaccination era, 2011–2016, compared to the pre-vaccination era, 2005–2010), and stratified by herpes simplex virus type 2 serostatus.

All estimates are adjusted for smoking. na, not available.

(DOCX)

S1 Text. Supplementary methods (laboratory analysis and statistical analysis).

(DOCX)

S2 Text. Prospective pre-analysis plan.

(PDF)

S3 Text. Trial protocol and report analysis plan (HPV-040 trial).

(PDF)

Acknowledgments

The authors wish to thank the steering committee of the HPV-040 trial—Allan Donner, Eduardo Franco, Pauli Leinikki, Achim Schneider, and Margaret Stanley—for all their scientific advice and support throughout the study. In addition, they would like to thank Kat French for generating the random allocation sequence of the original community-randomized trial. The authors also wish to thank Sara Kuusiniemi and Indira Adhikari for their part in the collection and handling of the serum samples used in this study from the larger FMC biobank, and Mika Gissler for providing data on self-reported maternal smoking, collected as part of the Finnish Medical Birth Register.

Abbreviations

FMC

Finnish Maternity Cohort

HBV

hepatitis B virus

HPV

human papillomavirus

HSV-2

herpes simplex virus type 2

PR

seroprevalence ratio

RPR

ratio of seroprevalence ratios

Data Availability

All the pertinent summary-level data are contained within the manuscript and supplementary files. All other relevant underlying individual-level data will be returned to Northern Finland Biobank Borealis in accordance with the signed Material Transfer Agreement. Biobank Borealis will subsequently make this individual-level data available researchers in accordance with their data access policies (contact via: biopankkiborealis@ppshp.fi).

Funding Statement

The study was also supported by grants from the Swedish Cancer Society (CAN 2015/399 and CAN 2017/459, https://www.cancerfonden.se/), from the Swedish Foundation for Strategic Research (grant number RB13-0011, https://strategiska.se/en/) and from Karolinska Institutet (Dnr. 2019-01523, https://ki.se/). ML received funding from KI for his Professorship (Dnr. 2-3698/2017, https://ki.se/). PG received personal working grants from the Cancer Society of Finland (pink ribbon fund, https://www.cancersociety.fi/) and the City of Tampere Science Fund (https://www.tampere.fi/). GlaxoSmithKline Biologicals SA funded the community-randomized HPV-040 trial (NCT00534638, https://www.gsk.com/) however was not in any way involved in the conduct of this study. The authors are solely responsible for the final content and interpretation.

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Decision Letter 0

Adya Misra

15 Jan 2020

Dear Dr Gray,

Thank you for submitting your manuscript entitled "Gender-neutral vaccination is the key to HPV16 herd effect when vaccination coverage is limited: a community-randomised trial of vaccination strategy" for consideration by PLOS Medicine.

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Decision Letter 1

Emma Veitch

13 May 2020

Dear Dr. Gray,

Thank you very much for submitting your manuscript "Gender-neutral vaccination is the key to HPV16 herd effect when vaccination coverage is limited: a community-randomised trial of vaccination strategy" (PMEDICINE-D-20-00112R1) for consideration at PLOS Medicine.

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[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

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-----------------------------------------------------------

Requests from the editors:

*In the title and throughout the paper, the term "community RCT" is used, do the authors mean "cluster RCT" which might be the more commonly recognised term? (in that randomization is of groups of individuals, not individuals themselves). The authors could consider using cluster RCT instead, this might be more generally understood and recognised.

*Although the authors use CONSORT to aid reporting of the trial, it would be good to explicitly mention this in the methods (and call out there the supporting file which basically constitutes the CONSORT checklist), and also to consider using the specialised CONSORT extension for cluster RCTs (http://www.consort-statement.org/extensions?ContentWidgetId=554) as this contains specific advice for particular elements of design and analysis that should be elaborated in more detail for a cluster RCT.

*In the abstract, it would be good to state how many clusters were in each randomized arm in the trial.

*In the last sentence of the Abstract Methods and Findings section, it would be good to include a brief description of any key limitation(s) of the study's design/methods.

*At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

*If possible, please tweak the in-text referencing style to match the PLOS Medicine format (numerals in square brackets, ie [1, 2]) - if using referencing software this should be fairly straight forward.

*Per the reviewers' comments, it would be good to explain in more detail in the manuscript and acknowledge the degree of novelty over and above prior studies also examining this question.

*In the Methods, it would be good to spell out the randomization procedures more clearly, per the CONSORT statement (either standard or cluster CONSORT should explain what needs to be detailed), but specifically an explanation of how allocation to arms was concealed and so on.

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Comments from the reviewers:

Reviewer #1: "Gender-neutral vaccination is the key to HPV16 herd effect when vaccination coverage is limited: a community-randomised trial of vaccination strategy" investigates the effects of moderate gender-neutral vs. girls-only vs. control (none) human papillomavirus (HPV), through a community-randomized trial in Finland, on herd immunity. The main analysis involving post- vs. pre-vaccination HPV prevalence/correlation was performed on 8,022 qualifying unvaccinated pregnent women whom were 23 years old or under and resident in the 33 involved communities, between 2005 and 2016. It was concluded that only gender-neutral vaccination results in herd protection against HPV16/18 (and not girls-only or no vaccination), when vaccination coverage is moderate.

The major strengths of this study lie in the original large-scale community-randomized design, and the statistical analysis attempting to take linked attributes (e.g. maternal smoking, HSV-2 seropositivity) into account. The general findings are also in accordance with expectations and modelling attempts (e.g. [12]), given the primary spread of HPV through intercourse. However, there are a number of key concerns:

1. Firstly, relatively similar analyses (comparing gender-neutral versus girls-only impact on HPV prevalence) on the same data have been published by some of the same authors (i.e. citations [16],[8]). In fact, some of the details available in these prior work (e.g. on the nature of the 33 communities, with each community having at least 35,000 inhabitants, and being at least 35km from each other) would probably be appropriately included as supplementary material here. In any case, the same broad conclusions had been reached in [16]: "In conclusion, while gender-neutral strategy enhanced the effectiveness of HPV vaccination for cross-protected HPV types with low to moderate coverage, high coverage in males appears to be key to providing a substantial public health benefit also to unvaccinated females".

The immediate reaction would then be on the additional contributions of this manuscript, on top of and over these previous works ([16],[8]). From what could be understood, the main distinction was that cervicovaginal samples taken at 18.5 years from all (vaccinated/unvaccinated) female participants were used for PCR analysis in [16], as opposed to seroprevalance amongst unvaccinated pregnant females at or under 23 years only - but also from non-participating cohorts - for this study. In general, the authors might consider stressing the presence of their directly-relevant previous work, and describe more precisely the relative strengths/weaknesses of this paper in comparison to those previous works.

2. While the authors do mention that "one-time PCR positivity is not a measure of cumulative infection", the discussion then goes on to admit the imperfect sensitivity of serology (as a measure of persistent infection), and seemingly uses PCR-based observations as the comparison standard after correcting for serology bias. It seems clear that the sensitivity of HPV detection (from serology) can have an appreciable effect on the outcome of the analyses. As such, the authors might consider quantifying the degree of this imperfect sensitivity (e.g. against some [PCR?] gold standard?), and how exactly the serology analyses were "quantified and corrected" (perhaps as an addition to the supplementary Laboratory Analysis).

3. A major focus of the paper is on "herd protection", given its emphasis in the abstract's motivation and conclusions, in particular the statement that "...when vaccination coverage is moderate, only gender-neutral vaccination results in herd protection against both HPV types 16 and 18". The directly relevant results shown in Figure 4 do seem to suggest a statistically-significant reduction in seroprevalence of HPV (from ~30% to ~23%) for gender-neutral (Arm A) vaccination, compared to only a marginal reduction for girls-only (Arm B) vaccination. However, the question is whether such a reduction would qualify as "herd protection". The authors might consider discussing the criteria for herd protection to be validated (i.e. if the seroprevalence reduction were to say 27% instead of 23%, would there still be herd protection?)

Moreover, the results from Figure 4 appear to imply that the declaration in the Discussion section that "...the gender-neutral vaccination strategy with its superb impact on both HPV16 and 18 overcomes the obstacle of suboptimal girls-only vaccination coverage", might be slightly exaggerated.

4. Given the recommendation on aggregate population-level herd protection, it might be appropriate to have an idea of the movement dynamics of the study participants, if possible. In particular, did they tend to stay within their original communities (which determined the Arm they belonged to), or was movement between communities common? This is especially since it is stated that "...exposure to the indirect effects of HPV16/18 vaccination is defined as residing at the time of sample donation in one of the community-randomized HPV vaccination trial communities", which appears to implicitly allow for such movement. A brief discussion of how such movement (if prevalent) could inform the recommendations would be appreciated.

5. While the analyses were adjusted for maternal smoking, which is mentioned to be consistently higher in the control Arm C communities, this gives rise to the question of whether smoking is expected to have any direct effect on HPV/cervocal cancer prevalence. Moreover, how exactly were these statistical adjustments (including random/systematic error introduced in Table 1) implemented?

Also, since it is stated that "...all estimates were adjusted for community-wise self-reported smoking", the authors might comment whether omitting the adjustments produces similar conclusions in any case. This is especially since Figure 5 suggests that adjusting for smoking has caused Arm B (girls-only vaccination) to demonstrate higher HPV seroprevalence ratios compared to Arm C (the control)

6. The population numbers in Figure 2 may be a little off. In particular, pre-vaccination total N=4006 is stated at the beginning, but the sum of the three Arms in the next step, 1326+1347+1334 is 4007. Similarly, post-vaccination total N=4016, but the sum 1331+1344+1340 is 4015.

Additional minor comments follow:

7. It is stated in the Introduction that "Furthermore, in our community-randomized trial, gender-neutral HPV vaccination has provided significantly stronger herd effect against HPV18/31/33/35...". It might be clarified that this is from analysis performed in previously-published studies.

8. The HBV abbreviation seems to appear without an initial definition (hepatitis B); it might also be relevant to mention that the HBV vaccine shows no clinically-relevant interference in antibody response to HPV antigens, if true.

9. This sentence under the Statistical Analyses subsection might be reworded: "To evaluate the extent of exposure among the study population of pregnant females, where The exposure is defined as the indirect exposure to HPV16/18 vaccination due residing at the time of sample donation in one of the communities of the community-randomized trial".

10. For the sentence "Particularly the HPV16 seroprevalence was significantly decreased in the Arm A communities in the post-vaccination era compared to the pre-vaccination era (22.1% versus 17.4%)", the percentage figures might appear in the same order as the eras they reference (i.e. 17.4% versus 22.1%)

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Reviewer #2: This is a carefully designed and appropriate study utilising HPV seroprevalence in young pregnant women ( plus some age matched males) from communities in Finland from pre and post HPV vaccination eras to deliver a randomised investigation to measure the potential impact of gender neutral vaccination to achieve better herd immunity The principle conclusion is that when HPV vaccination coverage is moderate, only gender-neutral vaccination establishes herd protection against HPV16 and HPV18, among unvaccinated females. This manuscript provides important support for the implementation of a gender-neutral HPV vaccination policy to achieve optimal vaccine effectiveness when obtaining a girls-only vaccination coverage of 90% is impossible. Previous studies have utilised HPV DNA PCR endpoints and have not seen such herd immunity impacts with lower coverage. This is discussed as likely due to this measure not reflecting cumulative infection and inability to distinguish persistent virus and transient infection.

Reviewer #3: In this study, Gray et al. use Finnish HPV serology data to examine whether gender-neutral HPV vaccination leads to more herd effects than girls-only vaccination in unvaccinated young women. The use of serology data presents a different and interesting way of assessing HPV exposure compared with most other herd effect studies which have used HPV DNA detection. Notable study strengths include the large sample size, high participant consent rate, the linkage of data with a large community-randomized HPV vaccination trial, and the inclusion of a sensitivity analysis to assess the likely impact of non-differential misclassification error. However, some notable limitations of the study include the low representativity of the sample (pregnant women <23) and limited ability to control for possible changes over time occurring in the background risk of HPV exposure (secular trends). While the topic is important and the study may offer some interesting insights, I have some major comments regarding the analysis and interpretations:

* The authors estimate that HPV vaccination coverage is approximately 47-53% in the eligible female birth cohorts in the post-vaccination era. However, very few women were excluded in the flowchart due to previous vaccination in the post-vaccination era (14/1331 in arm A, 23/1344 in arm B, and 12/1340 in arm C). This suggests that the women in the Finnish Maternity Cohort up to 2016 are a population of women where HPV vaccine coverage is at best 1-2% (likely they skew older and include women who may have been missed by the community trial). The authors should consider whether it is plausible that there would be herd effects when vaccination coverage appears to be so low in the study sample.

* The declines in HSV-2 seroprevalence over time suggest that there may be declines in HPV seroprevalence over time that may not be entirely attributable to vaccination programs, possibly due to differences in age distribution or in sexual behaviors. I would have liked to see this included somehow in the analyses, perhaps through the inclusion of a time trend in prevalence common to all HPV types. A time trend could have been included through the use of a difference in differences analysis, for example. Currently there is little mention of this in the discussion and of the possibility that observed changes could be due to other trends over time.

* The study sample is meant to be restricted to unvaccinated women. We need more information on how the authors identified "HPV-vaccinated" women based on their antibody levels, this is not very clear currently.

Other comments:

* I personally find it problematic and stigmatizing to label HSV-2 seropositives as a "sexual risk-taking core group" given how common HSV-2 is in the general population. Please consider rephrasing this in the paper as women who are likely to have had higher exposure to STIs, which is less judgmental.

* The authors claim there is little difference in age distribution pre- and post-vaccination. However, small differences in age could have a big impact on HPV seroprevalence given the large expected increase in HPV prevalence with age during the late teens. It would be helpful to give the mean age of women pre- and post-vaccination or include a table of the age distribution by era in the appendix. Is there any reason that age was not adjusted for in the log binomial model?

* The authors mention that pregnant women <23 are likely to be a more sexually active group, given that the average age at pregnancy is 29. The authors may want to mention that herd effects are expected to be lower and harder to detect in more sexually active groups, so their estimates are likely to underestimate herd effects in the general population.

* The serum samples were tested for more HPV types than were presented (39, 51, 52, 58, 59, 66, 68, 73). Why not present the results for these types, which are not expected to be affected by vaccine cross-protection? This would give further information as to whether there are time trends in HPV seroprevalence over time that are not attributable to vaccination.

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Reviewer #4: This manuscript addresses the important topic of who to vaccinate against HPV. It is clearly written and makes an important contribution to our understanding of herd immunity. Herd protection was estimated via a repeated cross-sectional cohort study of all pregnant women under the age of 23 within thirty-three communities participating in a community-randomized HPV vaccination trial. Cumulative infection in unvaccinated patients was estimated using L1 VLP serology. Communities were then randomized to one of three trial Arms: Arm A, gender-neutral HPV vaccination; Arm B, girls-only HPV vaccination; or Arm C, no HPV vaccination. This is a massive effort in a well followed nordic population.

The % of patients vaccinated within each cohort is hard to decipher as you read the manuscript. Please make this more clear in the text.

No estimate of the stability of the populations (i.e. how much intermingling) was provided, and should be.

In Figure 4, the drop in HSV2 seropositivity in Cohort B was as profound and significant as for the drop in HPV16/18 seropositivity in Cohort A. Please explain as this seems to call into question the main findings of the paper.

They show that the HPV16 and HPV18 seroprevalence was decreased in young unvaccinated women after gender neutral vaccination, but with single gender vaccination under these conditions of low vaccination rates. This provides a demonstration of herd immunity, but is perhaps not all that surprising given that twice as many people in the gender neutral vaccination cohort were vaccinated. Nevertheless it shows the important message that when only low vaccination rates can be achieved in girls that there is value in vaccinating boys to improve protection of girls through herd immunity. It is also highly likely that boys will also receive direct health benefits themselves through prevention of anogenital cancers and head and neck cancers, and should be strongly urged anyway for reasons of equity.

Do you expect the impact of herd immunity to grow as the population ages?

Is it reasonable to consider looking at the impact on CIN2/3 rates in the medical record as well as seropositivity?

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Any attachments provided with reviews can be seen via the following link:

[LINK]

Decision Letter 2

Thomas J McBride

6 Oct 2020

Dear Dr. Gray,

Thank you very much for submitting your revised manuscript "Gender-neutral vaccination is the key to HPV16 herd effect when vaccination coverage is limited: a cluster-randomized trial of vaccination strategy" (PMEDICINE-D-20-00112R2) for consideration at PLOS Medicine.

Your revision was evaluated by a senior editor and discussed among all the editors here. It was also discussed with the academic editor, and sent to two of the original reviewersr. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

I am afraid that we still will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a further revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

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Comments from the Academic Editor:

The study is based on excellent data sources and a well-known and important HPV vaccine trial, with record linkage to a national cohort of and serum databank for pregnant women. Herd effects of HPV vaccination are a valid and useful outcome to examine through further analyses of the parent trial. But the revised version of this manuscript does not give enough information to understand motivation, planning, analysis plan or results adequately. After reading detailed and thoughtful comments of the reviewers, the actual changes to the manuscript are very limited. As one reviewer says, you need to go back to all the previous studies to piece things together.

The paper is hard to follow for three main reasons. First, this report doesn’t explain well enough how this particular analysis fits in with the original trial, or the subsequently described plan to examine type replacement. Second, there are inconsistencies between this paper and the analysis plan that was provided. Third, it is not particularly easy to see how herd immunity is being defined and measured. I have a number of requests for clarification and suggestions.

General comments

1. Explanations and context: In the introduction, please explain the rationale for this study more fully, as it relates to the original objectives of the trial. The clinicaltrials.gov entry doesn’t mention type replacement or herd effects as primary or secondary outcomes, but the study design was reported as an RCT. The original RCT (as presented in ref 18) included modelling and provision to examine herd effects within the trial population, but did not specify additional analyses. Explain more clearly what the previous publications (esp refs 8 and 9) did and did not address about herd effects (e.g. lack of herd effects shown for HPV16 using HPV DNA positivity).

2. Without a protocol or statistical analysis plan written in advance for this particular analysis, it is hard to see whether the findings here showing support for a pre-defined hypothesis, or are exploratory and hypothesis-generating. In the introduction, please explain how the plan to assess herd effects of gender-neutral vaccination developed. The data from the Finnish Maternity Cohort (FMC) are mentioned in ref 18 for planning the trial, but not that they will be used in future. Explain how this study fits into the study analysis plan provided – that plan does not mention anything about measuring herd effects. The authors say they needed to find a herd effect before investigating type replacement. In this case, we would expect to see an analysis plan for investigating the herd effects before the analysis plan for type replacement. There is a new publication, which was not mentioned in the previous revisions, Gray P, et al. Int J Cancer 2020. Is this the manuscript that used the analysis plan? Please clarify, in the manuscript.

3. Given these limitations, I think that the title and conclusions (as stated in the Abstract and end of the main text) are somewhat overstated. The second bullet point of ‘What do these Findings Mean? in the Author summary is more appropriate as a conclusion.

4. Methods, study design could be clearer. The first two pages are confusing because they jump between the parent trial and the Finnish Maternity Cohort.

4a. Please state the hypothesis, if there was one, or if not that these are exploratory analyses.

4b. Please state the primary outcome. I couldn’t find definitions of which was the primary and which were secondary outcomes. Similarly, results were not reported according to primary or secondary outcomes.

4c. Fig 1, please add a first level to the flow chart to show how the cohort studied in this trial is related to the parent trial, including total numbers in the communities in each arm.

4d. Statistical analyses. The study is an analysis of a cohort nested in an RCT. Please describe how you measure follow-up and account for losses to follow-up. Please compare the characteristics of cohort participants to those of the female population of the same age in the trial communities.

4e. The analysis plan provided says that the pre-vaccination period is 2005-2007 and the post-vaccination period is 2008-2016. In the analyses here, the pre-vaccination period is 2005-2010. But vaccination was given in 2007-2010, so these years are part of the vaccination and post-vaccination period. Please explain.

5. Herd effects. These can be hard to conceptualise and understand.

5a. The authors now give a definition of herd protection. Could they give the full definition in the text that they gave in the response to reviewers? Could they also address Reviewer #1’s question about the relevant size of the difference? What size of difference was hypothesised?

5b. What was the vaccine coverage in the three arms? Is it possible that there is a greater effect in Arm A because overall coverage is higher? In Arm A, girls+boys coverage = 47.1% of girls + 19.5 of boys%. In Arm B, it’s 45.8% of girls.

5c. The authors report three different analyses, but these don’t seem to be comparable with respect to factors that are controlled for or stratified by. Please calrify these choices.

5c.i. Indirect effect of ‘community-wise’ vaccination over the study period – absolute seroprevalence in pre- and post-vaccination periods – why not controlled for smoking, or stratified by HSV-2 status?

5c.ii. Further assess indirect effect of ‘community-wise’ vaccination in the post-vaccination era – within-arm seroprevalence ratios, comparing post-vaccination and pre-vaccination (controlled for smoking – but we should see the crude ratios too)

5c.iii. Overall indirect effect of gender-neutral and girls-only, compared with counterfactual – between-arm ratio of seroprevalence – ratio of ratios - ? controlled for smoking?

6. Discussion, Interpretation according to gender-neutral strategy: Is there any information on sexual mixing between girls and boys who are vaccinated or not vaccinated? How would this affect the findings if there were assortativity according to vaccination status?

Specific queries (page and line numbers as in the marked up copy because there are none in the clean version of the pdf)

1. ‘Community-wise’ – doesn’t make sense – should it be community-wide (across all communities)? Or community-specific (for a specific community)?

2. Arms A, B and C. It’s hard to remember which arm is which. In some parts of the manuscript, it would be easier to refer to the gender-neutral arm of the trial (maybe with Arm A in brackets).

3. P8, line 193: why ‘1982 and younger birth cohorts’? Should this be 1992?

4. P10, line 226: ‘due residing’ doesn’t make sense.

5. P10, line 231-2: ‘weighted to the birth cohort distribution found in each year…’ ‘distribution’ of what? Age? Sex?

6. P12, line 282-3: HSV-2 seroprevalence – please refer to Fig 4.

7. P13, lines 306-8: Figures in Table 1a and text don’t match.

8. Fig 3. Why is there no shading in the years 2007-2010, when HPV vaccination was offered as part of the trial?

9. P15, line 346, ‘randomized trial evidence’ – please qualify this, given that the study population is a subset of the women in the communities.

10. P15: please explain why Chlamydia trachomatis as a marker of high sexual partner change (core group membership), would not be associated with a herd effect against HPV16 but HSV2 seroprevalence would?

Requests from the editors:

1- Thank you for updating the study design to cluster-randomized. However, following our email correspondence, it is now clear that this was a cohort study based on data from a cluster-randomized trial. Please update the Title and all other mentions of the study design throughout the manuscript to reflect this.

2- Please also include the prospective analysis plan (from our email correspondence) as a supplemental file, referenced from the Methods section. Any changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

3- Thank you for including the Cluster Trials CONSORT extension. However, as an observational study, it is more appropriate to report according to the STROBE Guideline, and include the completed STROBE checklist as Supporting Information. Please add the following statement, or similar, to the first section Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)." and remove the CONSORT checklist (and its mention in the Methods)

The STROBE guideline can be found here: http://www.equator-network.org/reporting-guidelines/strobe/

When completing the checklist, please use section and paragraph numbers, rather than page numbers.

4- Please describe briefly the ethical, legal, or contractual restriction that prevents you from sharing the deidentified dataset publicly. Please also note that a study author cannot be the contact person for the data. Please provide a different contact for data access, such as a member of your institute’s data or ethics committee.

5-Please revise your title according to PLOS Medicine's style. Your title must be nondeclarative and not a question. I recommend "Human papillomavirus seroprevalence in pregnant women following gender neutral and girls-only vaccination programs in Finland: a cohort analysis following a cluster randomized trial.”

6- Throughout the manuscript, please replace “subjects” with “participants”.

7- Abstract Background: Please be more specific about what you mean by “medically most important HPV type”, and cite the actual reproductive number instead of “high”.

8- In addition to stating the number of communities in each arm, please also include the number of participants in each arm when first describing the study in the Abstract.

9- In the Abstract and throughout the Results, please report all main outcomes (i.e., seroprevalence differences for all HPV types).

10- Thank you for mentioning a study limitation at the end of the Abstract Methods and Findings. Please make this a separate sentence(s), and include other relevant study limitations (e.g., generalizability outside Finland, potential effects of secular trends in sexual behaviors).

11- Abstract Conclusions: Please address the study implications without overreaching what can be concluded from the data; the phrase "In this study, we observed ..." may be useful.

12- Additionally, in the Abstract Conclusions, please interpret the study based on the results presented in the abstract, emphasizing what is new without overstating your conclusions. Perhaps, “These findings suggest that gender-neutral vaccination can facilitate the control of HPV16…”

13- Author summary point 3, please edit to: “Achieving herd protection for HPV16 requires greater than 80% girls-only vaccination coverage, a level that has not been achievable in many countries.”

14- Author Summary point 4 (“Evidence-based solutions to this problem are required...”) should be removed and replaced with the study question.

15- Author Summary point 7 (“Only among the unvaccinated females...”) is phrased a bit awkwardly, consider editing.

16- The last sentence of the Introduction could be split into two sentences to improve clarity.

17- For all observational studies, in the manuscript text, please indicate: (1) the specific hypotheses you intended to test, (2) the analytical methods by which you planned to test them, (3) the analyses you actually performed, and (4) when reported analyses differ from those that were planned, transparent explanations for differences that affect the reliability of the study's results. If a reported analysis was performed based on an interesting but unanticipated pattern in the data, please be clear that the analysis was data-driven.

18- Please remove trademark symbols (e.g., CervarixTM, Engerix®-B).

19- Thank you for including vaccination coverage. Please include the numerators and denominators that go along with each percentage. Additionally, this seems like it should be in the Results rather than Methods?

20- Please provide a table showing the baseline characteristics of the study population.

21- Regarding the point (made by reviewers 1 and 4) about the likelihood of intermingling among the study population, your response should be noted in the manuscript text, in case readers also have the same question. Also, is there a reference you could point to on this point?

22- Figure 5, the color legend is over top of the bottom ratio numbers.

23- Please integrate your response to Reviewer 4’s 4th point (about the HSV seroprevalence) into the main text, as readers may have the same question.

24- Please include a table of absolute numbers of seropositive cases, in addition to the information on adjusted seroprevalence ratio contained in the current table 1.

25- Please incorporate table S3 into the main paper.

26- Please begin the Discussion with a brief summary of what was done, before describing the results.

27- The phrase “sexual risk-taking core group” still appears, please replace with a less stigmatizing phrase.

28- Please rephrase the final paragraph of the Discussion to limit the conclusions to the current study. E.g., “Our results suggest that when HPV vaccination coverage is moderate…”

Comments from the reviewers:

Reviewer #1: We thank the authors for considering the points raised in our previous review. They have largely been addressed, and only a few suggestions remain:

1. The additional advantages of the new cumulative incidence methodology over the previous one-time PCR-positivity might be briefly mentioned at the end of the Introduction section, for readers to more quickly recognize the significance of the work. The relevant previous work might also be cited there.

2. The (low) possibility of movement between communities might also be briefly mentioned as a possible limitation.

3. The addition of Table S1 is much appreciated. If possible, it might be briefly explained as to how the sensitivity/specificity used in the analysis, were derived from the primary assumption.

Reviewer #3: Great work by the authors. Remaining comments:

* It is recommended in flow charts by CONSORT to include all those assessed for eligibility in the study and document reasons for exclusion from the study. Please include in the flowchart all women <23 in the Finnish Maternity Cohort in the communities, and indicate how many were excluded due to lack of consent and the 3498 excluded due to registry-linked HPV vaccination status by study period in Figure 2.

* Please indicate what cutoff was used when assessing HPV vaccination status through antibody titers.

* They repeat the definition of exposure twice in the methods, this sentence could be deleted: "Exposure to the indirect effects of HPV16/18 vaccination is defined as residing at the time of sample donation in one of the community-randomized HPV vaccination trial communities."

Any attachments provided with reviews can be seen via the following link:

[LINK]

Decision Letter 3

Raffaella Bosurgi

15 Mar 2021

Dear Dr Gray, 

On behalf of my colleagues and the Academic Editor, Nicola Low, I am pleased to inform you that we have agreed to publish your manuscript "Human papillomavirus seroprevalence in pregnant women following gender-neutral and girls-only vaccination programs in Finland: a cross-sectional cohort analysis following a cluster-randomized trial" (PMEDICINE-D-20-00112R3) in PLOS Medicine.

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Checklist. STROBE checklist.

    (DOCX)

    S1 Fig. Lexis diagrams depicting the vaccinated cohorts and vaccination coverage among the eligible birth cohorts of the study population, by arm and gender.

    (a) Among females; (b) among males.

    (DOCX)

    S2 Fig. Type-specific human papillomavirus (HPV) seroprevalence (%) among unvaccinated females under the age of 23 years by vaccination strategy—gender-neutral vaccination (Arm A), girls-only vaccination (Arm B), and control vaccination (Arm C)—and time period of sample donation (pre-vaccination era, 2005–2010, and post-vaccination era, 2011–2016).

    (DOCX)

    S3 Fig. Ratio of HPV seroprevalence ratios (RPR) comparing Arm A/B to Arm C.

    Arm-specific PRs comprise post-vaccination to pre-vaccination-era HPV seroprevalence ratios among pregnant unvaccinated Finnish females aged under 23 years old, and are adjusted for community-level maternal smoking.

    (DOCX)

    S1 Table. Sensitivity and specificity parameters of pseudovirion-based serology in measuring cumulative HPV exposure used in the probabilistic bias analysis.

    (DOCX)

    S2 Table. Intracluster correlation coefficient (ICC) of any human papillomavirus (HPV) type seropositivity among pregnant females donating sera during the pre-vaccination era, 2005–2010.

    HSV-2, herpes simplex virus type 2.

    (DOCX)

    S3 Table. Characteristics of the study population after exclusions owing to ineligibility.

    (DOCX)

    S4 Table. Absolute HPV-type-specific seroprevalence among unvaccinated pregnant Finnish women stratified by trial arm and vaccination era (2005–2010 is defined as the “pre-vaccination era” and 2011–2016 as the “post-vaccination era”), and additionally by HSV-2 seropositivity.

    (DOCX)

    S5 Table. Unadjusted HPV-type-specific seroprevalence ratio (PR) among unvaccinated Finnish females comparing the post-vaccination era to the pre-vaccination era.

    Comparisons are between 2 time periods of sample donation (2011–2016, post-vaccination era, versus 2005–2010, pre-vaccination era), stratified by intervention Arm A (gender-neutral HPV vaccination), Arm B (girls-only HPV vaccination), and Arm C (control vaccination).

    (DOCX)

    S6 Table. Adjusted seroprevalence ratio (PR) of HPV seropositivity by HPV type among pregnant, unvaccinated Finnish females under the age of 23 years by study arm (gender-neutral vaccination Arm A, girls-only vaccination Arm B, or control Arm C), comparing time period of sample donation (post-vaccination era, 2011–2016, compared to the pre-vaccination era, 2005–2010), and stratified by herpes simplex virus type 2 serostatus.

    All estimates are adjusted for smoking. na, not available.

    (DOCX)

    S1 Text. Supplementary methods (laboratory analysis and statistical analysis).

    (DOCX)

    S2 Text. Prospective pre-analysis plan.

    (PDF)

    S3 Text. Trial protocol and report analysis plan (HPV-040 trial).

    (PDF)

    Attachment

    Submitted filename: Response to the reviewers.docx

    Attachment

    Submitted filename: Response to Reviewers.docx

    Data Availability Statement

    All the pertinent summary-level data are contained within the manuscript and supplementary files. All other relevant underlying individual-level data will be returned to Northern Finland Biobank Borealis in accordance with the signed Material Transfer Agreement. Biobank Borealis will subsequently make this individual-level data available researchers in accordance with their data access policies (contact via: biopankkiborealis@ppshp.fi).


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