Association between female genital schistosomiasis and high-risk human papillomavirus among women of reproductive age in Zambia: the Schista study

Background: Female genital schistosomiasis (FGS) is a chronic gynaecological disease caused by the deposition of Schistosoma haematobium eggs in the female genital tract. It is highly prevalent in sub-Saharan Africa (SSA), the region with the highest cervical cancer incidence and mortality rates globally. Persistent infection with high risk (HR-) human papilloma virus (HPV) is necessary for cervical cancer development. We aimed to determine the cross-sectional association between FGS and HR-HPV genotypes in women across three communities in Zambia.

Women aged 15-50, sexually active, not menstruating or pregnant, were recruited at home by community health workers. Participants provided two cervicovaginal self-swabs, a urine sample, collected HIV and Trichomonas vaginalis self-tests and completed a questionnaire. At clinic follow-up, midwives collected two cervicovaginal swabs and cervical images with point-of-care colposcopy (EVA System, MobileODT /i1). Swabs were analysed for 14 HR-HPV types (GeneXpert /i1) and for Schistosoma DNA (ITS-2 qPCR). Urine samples were analysed for Schistosoma ova by microscopy and for circulating anodic antigen (CAA) to detect active infection. Visual FGS was defined as colposcopic identification of specific genital lesions. Molecular FGS was defined as Schistosoma qPCR positivecervicovaginal swabs.

A total of 2,532 women (median age 28 years [IQR:22-36]) were recruited at home and 67% (1,694/2,532) completed clinic follow-up. Prevalence of visual FGS, molecular FGS, and HR-HPV were 35.2% [595/1,691], 6.5% [165/2,532], and 28.7% [690/2,401], respectively. HIV seropositivity was 17.5% (443/2,530), with 91.2% (406/443) self-reporting the use of antiretroviral therapy (ART). Risk factors crudely associated with HR-HPV infection included younger age, marital status, higher number of pregnancies, molecular FGS positivity, and urinary S. haematobium positivity detected using microscopy. There was evidence of a weak association between molecular FGS and all HR-HPV (adjusted Odds Ratio [aOR]=1.3, 95% Confidence Intervals [CI] 0.9-1.9). Women with molecular FGS were significantly more likely to test positive for HR-HPV 16/18/45 (aOR=1.7, 95%CI 1.0-2.8). No significant association was observed between visual FGS and HR-HPV infection (crude [c] OR = 0.9, 95% CI 0.7-1.1). . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint Lamberti et al. FGS and HR-HPV 3

To our knowledge, this is the first study to jointly screen for FGS and HR-HPV in Zambia and to report an association between the most oncogenic HR-HPV types and molecular FGS. These findings call for the need for integrating FGS and HR-HPV screening strategies to address the dual burden in SSA.

High-risk human papillomavirus, female genital schistosomiasis, cervical cancer, Zambia, Neglected tropical diseases, sub-Saharan Africa, sexual and reproductive health . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 4

Female genital schistosomiasis (FGS) is a chronic and neglected gynaecological disease estimated to affect 30-56 million women globally, mostly in sub-Saharan Africa (SSA) (1,2). It is caused by the deposition of the eggs of Schistosoma (S.) haematobium, a waterborne trematode, in the female genital tract (1,2). The egg-deposition is a consequence of entrapment during egg migration from the pelvic venous plexus which induces an inflammatory response leading to the formation of granulomas, and epithelial damage presenting as characteristic cervicovaginal mucosal lesions (1,2). Untreated, FGS is associated with sexual dysfunction and reproductive tract morbidity, including infertility, dyspareunia and genital symptoms mimicking sexually transmitted infections (STIs) (2). Despite its high prevalence and clinical burden, FGS remains largely underdiagnosed and overlooked in schistosomiasis, and sexual and reproductive health programmes (1,2). There are currently no guidelines for FGS screening, diagnosis, treatment, or case management, and awareness is low among communities and healthcare providers in many endemic settings (2,3,4). Conventional diagnosis involves collecting cervicovaginal images in clinics using a colposcope (2, 3,4). Images are then analysed by gynaecologists and classified as suggestive of ‘visual FGS if characteristic cervicovaginal mucosal findings, including homogeneous sandy patches, grainy sandy patches, rubbery papules, or abnormal blood vessels are observed (5). Visual diagnosis of FGS lesions requires expensive equipment, advanced clinical infrastructures, and specialised training, which are often not available in S. haematobium endemic settings (2,6). In addition, concordance between expert reviewers is poor (Cohen’s kappa statistics=0.16), highlighting the low specificity and

of visual FGS diagnosis on cervicovaginal images (6). Molecular testing using polymerase chain reaction (PCR) to detect S. haematobium DNA in genital swabs (‘molecular FGS’) offers a potentially more scalable and specific diagnostic method (3,7). Genital samples can be collected in the clinic by a health worker or self-collected at home by an individual, potentially increasing screening coverage (3,7). Cervical cancer incidence and mortality is highest among women in SSA (8-10). Zambia has the third highest incidence and mortality rates of cervical cancer in the world, with 65.5 new cases and 43.4 cancer deaths per 100,000 women per year (11). Persistent infection with one of the 12 high-risk (HR-) human papillomavirus (HPV) types (HPV types 16, 18, 31, 33, 35, . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 5 39, 45, 51, 52, 56, 58, and 59) is the primary cause of cervical cancer globally (12). HPV16 and 18 are responsible for 70% of all cervical cancer cases, while HPV31, 33, 45, 52, and 58 contribute to an additional 20% of cases (12,13). HR-HPV is primarily sexually transmitted, and risk factors include early sexual debut, greater number of lifetime sexual partners, high parity, hormonal contraceptive use, and co-infection with other STIs (14). Women living with HIV have a two-fold increased risk of acquiring HR-HPV (15), and a six-fold increased risk of cervical cancer, compared to women without HIV (16). The recovery of cell-mediated immunity following initiation of antiretroviral therapy (ART) does not necessarily remove this risk, although early initiation of ART before significant immune depletion reduces the risk of cervical cancer (17). The chronic genital inflammation caused by S. haematobium eggs may facilitate HR-HPV acquisition, persistence and progression to cervical precancer, yet this association requires further investigation (2,18). The World Health Organization (WHO) has called for the elimination of cervical cancer by 2030, with targets including vaccinating 90% of girls by age 15; screening of 70% of women twice by age 35 and 45 with high-performance test; and treating 90% of women with cervical precancer and cancer (19). Zambia launched its national HPV vaccination programme in 2019 and is currently transitioning from visual inspection with acetic acid (VIA) to HPV DNA-based screening for both the general population of women and women living with HIV, due to its higher sensitivity and specificity to detect cervical precancer (20). HPV DNA testing can be performed on provider- or self-collected sample (20). Self-sampling for HPV screening has comparable sensitivity and specificity to clinician-collected samples when tested using PCR (21,22). Molecular testing for FGS could be integrated into the cervical cancer screening programmes and delivered at home for multi-pathogen community-based screening (7,8). Understanding the epidemiological overlap between FGS and HR-HPV infection is essential to inform integrated screening strategies (7). Previous studies exploring the association of FGS and HPV in SSA showed mixed results (2,18). A study in Zimbabwe among 236 women of reproductive age (15-49 years) found evidence of an association between FGS, defined with the composite diagnosis of visual and molecular methods, and HR-HPV infection (age-adjusted OR=1.9, 95%CI 1.1-3.6, p- value=0.032) (23). Similarly, another cross-sectional study among 933 women in South Africa found strong evidence of an association between visual FGS by colposcopy and any HR-HPV infections (detected by GP5+/6+ HPV PCR test) (adjusted [a] OR: 1.71 95% . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 6 CI:1.14-2.56, p=0.010) (24). In contrast, a study of 302 women in Madagascar, found no evidence of an association between visual FGS and prevalence of any HPV infection (both high and low risk genotypes diagnosed using the E7-multiplex genotyping PCR assay) (OR=1.0, 95%CI 0.82-1.2) (25). A recent study in Tanzania, found no differences in rates of HR-HPV infection between women with and without Schistosoma infection, detected by circulating anodic antigen (CAA), an indirect measure of Schistosoma infection that does not indicate genital involvement (26). To our knowledge no study to date has evaluated the association between FGS diagnosed using both visual and molecular diagnostic methods and individual HR-HPV genotypes. This study aims to determine the risk factors for HR-HPV and the association of HR-HPV prevalence and FGS diagnosed by visual and molecular diagnostic methods, in an ongoing longitudinal cohort in Zambia ( Zipime-Weka-Schista study).

Study design and participants The Zipime-Weka-Schista (Do-self-testing sister!) study is a four-year longitudinal cohort study evaluating the performance and acceptability of multi-pathogen self-sampling for genital infections among women in Zambia, (27). This analysis uses baseline data collected between January 2022 and April 2023, across three sites (Livingstone, Sikoshwe, and Chanyanya). Briefly, girls and women aged from 15 to 50 years old, non-pregnant, sexually active, and who had been resident for at least a year in one of the study sites were eligible for enrolment. Participants were randomly selected through community-based random sampling and enrolled at home by trained Schista Community Workers (SCWs) (27). Further details are described in elsewhere (27). Samples collection During the home visit, participants received study information, provided written informed consent, completed a questionnaire administerd by a SCW, and self-collected two cervicovaginal swabs and a urine specimen (27). One swab was stored in PrimeStore® MTM molecular transport media (donated by Longhorn Vaccines and Diagnostics LLC, Bethesda, . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 7 US) for the detection of Schistosoma DNA (S1 Text) (27). The second swab was used for HR-HPV testing and was predominantly stored in PrimeStore® MTM molecular transport media (80% of baseline samples), with a smaller subset stored in ThinPrep Cytopreserve® solution (S1 Text). Urine was tested on the same day at the field laboratory for S. haematobium egg-patent infection by urinary egg microscopy (S2 Text). A 2mL urine sample was shipped to Leiden University Medical Centre (LUMC), The Netherlands for Schistosoma CAA detection using the up-converting reporter particle lateral flow CAA test (UCAA hT417 format, CAA-levels >0.6 pg/mL were considered positive) (S3 Text) (28). Participants were also offered HIV ( OraQuick® HIV Self-Test) and Trichomonas (T.) vaginalis self-tests (OSOM® Trichomonas Rapid Test). For both self-tests, results were read by the SCW and immediately shared with the participant. HIV-positive self-test results were confirmed on-site using a point-of-care diagnostic test (Determine TM) (27). Participants who tested positive for HIV or T. vaginalis at home were referred to the clinic for treatment and linkage to care. Following the home visit, enrolled participants who were not menstruating were invited for the clinic follow-up (27). After speculum insertion, a midwife collected two cervicovaginal swabs, a cervicovaginal lavage (CVL), and cervicovaginal images with a point-of-care colposcope (EVA MobileODT®, Tel Aviv, Israel), which are saved to an online portal for remote review. Similarly to the home visit, one cervicovaginal swab was stored in PrimeStore® MTM molecular transport (donated by Longhorn Vaccines and Diagnostics LLC, Bethesda, US) media and the second in Cytopreserve®. A CVL specimen was obtained by flushing 10mL of normal saline across the cervix and vaginal walls for one minute using a bulb syringe. The fluid was then collected from the posterior fornices with a pipette and transferred into a centrifuge tube containing PrimeStore® MTM. The CVL sample was stored at -20 oC on site (S1 Text). Visual FGS Colposcopic cervicovaginal images were independently evaluated remotely by two experienced gynaecologists (BD and DK). In the case of disagreement between the two reviewers, a third reviewer (IH) was asked to independently analyse the images of the discordant case. Partcipant were defined as ‘visual FGS’ positive if at least two of the reviewers independently identified at least one of the four lesion types; homogeneous yellow sandy patches, grainy sandy patches, rubbery papules, or abnormal blood vessels, and as . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 8 negative if none of these lesions were observed (5). Women with evidence of schistosomiasis, ‘molecular FGS’ and/or ‘visual FGS’ were treated with 40mg/kg praziquantel delivered as a single dose (30). Molecular FGS Cervicovaginal swabs stored in Primestore® MTM were processed at Zambart central laboratory (Lusaka, Zambia) for the detection of Schistosoma DNA using Internal- trasncribed-spacer-2 (ITS-2) by real-time PCR (ITS qPCR) (S4 Text). Total nucleic acid (TNA) extraction (PrimeXtract™ Longhorn Vaccines & Diagnostics, USA) was performed as per manufacturer’s instructions, using a simplified silica-based spin column extraction process. qPCR was performed as previously reported and results were reported in cycle threshold values (Ct-values) and considered positive if any C t-value was observed and negative if no C t-value was observed (3,29). Women were classified as ‘molecular FGS’ positive if either self- or provider-collected cervicovaginal swab tested positive for Schistosoma DNA via qPCR. HR-HPV detection Self-collected cervicovaginal swabs stored in either PrimeStore® Molecular Transport Medium (MTM) or in ThinPrep Cytopreserve® were tested for HR-HPV detection using a multiplex real-time PCR assay (GeneXpert HPV®, Cepheid, Sunnyvale, CA, USA) which simultaneously detects 14 HR-HPV types (HPV 16, 18, 45, 31, 33, 35, 52, 58, 51, 59, 39, 56, 66, 68), grouped into three channels: HPV type 16; HPV types 18 or 45 (or both); and any other HR-HPV types. DNA extraction for samples stored in PrimeStore® Molecular Transport Medium (MTM) was performed using a modified PrimeXtract™ spin column protocol (S5 Text). For GeneXpert HPVanalysis, 50 µL of the extracted DNA was diluted in 1mL of normal saline and loaded into the GeneXpert cartridge, following the standard assay protocol. A sample adequacy control (SAC) and a Probe Check Control (PCC) was also provided in the cartride (S5 Text). If a test result on the self-collected swab was invalid, HR- HPV testing was done using the healthcare provider-collected swab (S6 Text). HR-HPV definitions . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 9 Participants were classified as HR-HPV positive if positive for at least one of the 14 HR- HPV types (HPV 16, 18, 45, 31, 33, 35,52,58,51,39, 56, 66, 68); HPV16/18/45 positive if positive for the HPV type 16, and/or the HPV type 18 and/or 45 channels; and HPV16 positive if only the HPV type 16 channel was positive (S1 Figure). Samples were classified as invalid if both the home-based self-collected swab and clinic-based provider-collected swab returned invalid results (S6 Text). This classification allowed to distinguish HPV16 and HPV18 and HPV45 from the other HR-HPV genotypes as they are the most oncogenic genotypes (12,13). HR-HPV positive women were referred to a gynaecologist for colposcopy and a two-quadrant cervical biopsy according to age and HIV status (27). All women with cervical precancer were referred for management as per national guidelines (20). Statistical analyses Data were entered on hand-held electronic devices using Open Data Kit (ODK) and analysed using Stata 17.0 (StataCorp, LP, College Station, US). Primary outcomes were detection of any HR-HPV, HPV type 16 or 18 and/or 45 (HPV16/18/45) and HPV type 16 only. The HPV16/18/45 outcome was defined by combining outputs from the HPV type 16, and the HPV type 18 and/or 45 channels. The denominator throughout this analysis was all women with valid HPV DNA test results. Descriptive statistics were used to summarise participants’ characteristics, stratified by HR-HPV status. Univariable logistic regression analyses were used to estimate crude odds ratios (cOR) and 95% confidence intervals (CI) for the associations between HR-HPV and potential risk factors. Potential risk factors were informed by the published literature. Multivariable logistic regression models were used to estimate adjusted odds ratios (aOR) and 95% CI for the associations between HR-HPV and factors associated with HR-HPV in univariable analysis. (p-value<0.05). Covariates with missing data or those applicable only to a subgroup were excluded. Multicollinearity was assessed between variables in the final models. Ethical considerations The study was approved by the University of Zambia Biomedical Research Ethics Committee (UNZABREC) (reference: 1858-2021), the National Health Research Authority (NHRA) (Reference: 00012/24/09/2021), and the London School of Hygiene and Tropical Medicine . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 10 (LSHTM) (reference: 25258). Ministry of Health and local superintendents approved the study in September 2021.

Figure 1 shows the study flow. At baseline, 2,532 women (median age: 28 years, interquartile range [IQR] 22-36) were enrolled at home, and 67% (1,694/2,532) completed the clinic follow-up after a median of two days (IQR: 1-11 days). Cervicovaginal swabs and urine samples were collected from all women at enrolment. All urine samples were tested for S. haematobium ova detection by microscopy, and 99.4% (2,517/2,532) were tested for presence of CAA. Visual FGS status was available for 99.8% (1,691/1,694) of participants who completed the clinic follow-up. HR-HPV DNA testing was performed on 98.3% (2,488/2,532) of participants, and 96.5% (2,401/2,488) gave a valid HR-HPV result. Molecular FGS diagnosis was available for all study participants (Figure 1). Data for both HR-HPV and molecular FGS status were available for 94.8% (2,401/2,532) of participants, and for HR-HPV and visual FGS in 96.7% (1,639/1,694) of clinic attendees. Participant characteristics Of 2,532 women, 165 (6.5%) tested positive for molecular FGS (median Ct-value= 35.1, IQR:7.4-31.6) (Table 1). Visual FGS was identified in 35.2% (595/1,691) of participants, (Table 1). Egg-patent S. haematobium infection was detected in 5.2% (132/2,532) of participants (mean intensity: 4.8 eggs/10mL of urine; Standard deviation [SD]: 5.5). Schistosoma CAA positivity was observerd in 15.4% (388/2,517) (median CAA concentration=4.6 pg/mL; IQR 1.1-31.0) (Table 1). HIV prevalence was 17.5% (443/2,532), with 91.6% (406/443) of self-reporting antiretroviral therapy (ART) use (Table 1). The prevalence of T. vaginalis by rapid diagnostic test (RDT) was 10.3% (246/2,389) (Table 1). Distribution of infection by age The distribution of molecular FGS, visual FGS and HR-HPV infection by age is shown in Figure 2 (S1 Table). The prevalence of molecular FGS was highest among adolescents aged 15-19 years (14.6%) and declined with age ( χ ² < 0.00) (Figure 2, S1 Table). In contrast, prevalence of visual FGS increased with age, peaking among women aged 46-50 years (53.4%) χ ² < 0.001) (Figure 2, S1 Table). HR-HPV prevalence declined significantly with age (p-value<0.001). Compared to women aged 46-50 years, girls and women aged 15-25 years old had higher risk of HR-HPV (15-19 years vs. 46-50 years; 36.0% vs. 20.6%; cOR =2.2, . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 11 95%CI 1.3-3.5; 20-25 years vs. 46-50 years: 35.1% cOR=2.1, 95% CI 1.3-3.3) (Figure 2 and Table 1). Prevalence and risk factor analysis for prevalence of any HR-HPV Prevalence of any HR-HPV genotypes was 28.7% (690/2,401) (Table 1). HR-HPV prevalence declined significantly with age (p-value<0.001). Any HR-HPV prevalence was higher among women with molecular FGS compared to those without (36.1% vs. 28.2%; cOR= 1.5, 95%CI 1.0-2.0) (Table 1). No statistically significant difference was observed by visual FGS status (visual FGS positive vs. negative 28.0% vs. 31.2%, cOR=0.9, 95%CI 0.7- 1.1), either overall or by lesion type (Table 1 and S2 Table). Women with urinary S. haematobium by microscopy had a higher prevalence of any HR-HPV compared to those without (40.2% vs. 28.1, cOR=1.7, 95%CI 1.2-2.5). However, this association was not observed with Schistosoma infection by CAA (cOR=1.0, 95%CI 0.8-1.3) (Table 1). No significant differences in HR-HPV prevalence were observed by HIV status (cOR=1.0, 95%CI 0.8-1.2) or T. vaginalis status (cOR= 1.2, 95%CI 0.9-1.6) (Table 1). After adjusting for age, marital status, and number of pregnancies molecular FGS was not significantly associated with any HR-HPV prevalence (aOR=1.3, 95% CI=0.9-1.9) (Figure 3). Women aged 20-25 years had higher odds of HR-HPV infection compared to women aged >= 45 years (aOR=1.65, 95%CI 1.1-2.5). Married women had lower odds of HR-HPV infection compared to single women (aOR=0.6, 95%CI 0.5-0.8) (Table 1, Figure 3. Due to multicollinearity between ‘molecular FGS’ and urinary S. haematobium infection (r=0.56), a separate model evaluated the association between urinary S. haematobium infection by microscopy and infection with any HR-HPV (aOR=1.7, 95%CI 1.1–2.4) (S3 Table) Prevalence and risk factor analysis for infection with high oncogenic types; HPV16, 18 and 45 HPV 16/18/45 Prevalence of infection with any of the HPV16/18/45 was 9.6% (231/2,401) (Table 2). In univariable analysis, higher prevalence was observed among HIV-positive versus HIV- negative women (12.5% [53/424] vs. 8.9% [166/1,864], cOR=1.5, 95%CI 1.1-2.0), and among women with T. vaginalis compared to those without (14.6% [35/240] vs. 8.8% [177/2,019], cOR=1.8, 95%CI 1.2-2.6) (Table 2). HPV16/18/45 prevalence was higher among women with molecular FGS compared to those without (15.8% [25/158] vs. 9.2% . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 12 [206/2,243], cOR=1.9, 95%CI 1.2-2.9), but no association was observed with visual FGS (cOR=0.8, 95%CI 0.6-1.2) (Table 2, S4 Table). In adjusted analysis, molecular FGS (aOR=1.7, 95%CI 1.0-2.8), HIV status (aOR=1.7, 95%CI 1.2-2.4), and T. vaginalis status (aOR=1.5, 95%CI 1.0-2.2) were associated with increased odds of HPV16/18/45 infection (Figure 4).In addition, single women had higher odds of HPV16/18/45 infection compared to married women, (aOR=1.9, 95%1.4-2.9), and participants residing in Chanyanya were more likely to be infected than those from Shikoswe (aOR=3.6, 95%CI 1.4-9.3) (Figure 4). HPV16 only HPV16 prevalence was 4.8% (114/2,401) (Table 3). HPV16 prevalence was higher among single women compared to married women (6.6% [58/886] vs. 3.5% [46/1,329], cOR=2.0, 95%CI 1.3-2.9) (Table 3). Women with molecular FGS had higher HPV16 prevalence compared to those without (8.2% [13/158] vs. 4.5% [101/2,243]; cOR=1.9, 95%CI 1.0-3.5) (Table 3). No significant association was observed with visual FGS status (cOR=0.8, 95%CI 0.5-1.2), urinary S. haematobium status by microscopy (cOR=1.4, 95%CI 0.7-2.9), Schistosoma status by CAA (cOR=1.2, 95%CI 0.8-2.0), HIV status (cOR=1.4, 95%CI 0.9- 2.2), or T. vaginalis status (cOR=1.4, 95%CI 0.8-2.5) (Table 3, S5 Table). After adjusting for marital status and parity, women with molecular FGS had 1.8 higher odds of being HPV16 positive compared to those without (aOR=1.8, 95%CI 1.0-3.4) (Figure 5).

To our knowledge, the Zipime-Weka-Schista study is the first to investigate the association between HR-HPV and FGS, diagnosed using both visual and molecular methods, in a large cohort of women with and without HIV in Zambia (27). We found a significant association between women with FGS defined as DNA detected by qPCR from cervicovaginal swabs (molecular FGS) and HPV16/18/45, the most frequently associated with cervical precancer and cancer. In contrast, no significant association was found between visual FGS, diagnosed using colposcopy, and HR-HPV infection. These findings highlight the need to recognize FGS as a sexual and reproductive health (SRH) condition and to integrate FGS screening into cervical cancer control programmes to improve early detection and reduce the dual burden of diseases in S. haematobium endemic settings (7). . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 13 Women with molecular FGS were almost 1.7 times more likely to test positive for HPV16/18/45, the most oncogenic genotypes which contribute to the majority of cervical precancer and cancer globally (12,13). To our knowledge, this is the first study to compare molecular FGS with molecular detected HR-HPV infection from cervicovaginal self-swabs for both infections. This finding suggests that FGS may play a role in the natural history of cervical HPV infection. HPV infects the undifferentiated, proliferating basal cells of the cervicovaginal epithelium through microabrasion, often resulting from co-existence of other STIs or co-factors that compromise the epithelial barrier (31). The epithelial damage of the anogenital mucosa caused by S. haematobium egg deposition in women with FGS may facilitate HPV viral entry (18). Further, the chronic genital inflammation caused by the S. haematobium egg deposition in the female genital tract may impair local immune responses, promoting immune evasion and HR-HPV persistence (18,31). Although the cross-sectional nature of this analysis does not allow to distinguish between incident and persistent HR-HPV infections, the observed association between molecular FGS and HPV16/18/45 support the hypothesis that FGS may contribute to HPV persistence. This aligns with findings from a recent study in Tanzania that followed 96 HIV-negative women and found higher odds of HR-HPV persistence at 9-12 months among women with Schistosoma infection, diagnosed by CAA (32). This analysis did not assess for genital involvement of schistosome infection but it supports the hypothesis that the schistosomiasis-related inflammation may contribute to persistence of HR-HPV infection (32). Longitudinal data from the ongoing Zipime-Weka- Schista study will further evaluate whether FGS promotes persistence or delays clearance of HR-HPV (27). Women with egg-patent urinary S. haematobium infection were more likely to have prevalent HR-HPV infection, compared to those without. In contrast, no significant association was observed between schistosomiasis detected by CAA and HR-HPV infection. This may reflect the differences between diagnostic method (30). CAA is a highly sensitive diagnostic method for active Schistosoma infection, detecting antigens released by live adult worms in the host’s bloodstream (28). However, it does not provide information on egg deposition or differentiate between species (28). The absence of an observed association between CAA and HR-HPV but a positive association with egg-patent urinary schistosomiasis highlights the complexity of active infection in the pathogenesis of HR-HPV in the presence of S.haematobium. . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 14 In our study, visual FGS, diagnosed by colposcopy, was not associated with HR-HPV prevalence. Previous studies on this association reported mixed results, likely due to differences in outcome definitions, with one study including any HPV type (both high- and low- risk genotypes) and the other any HR-HPV type (24,25). Although colposcopy is widely used to assess FGS-related morbidity, its scalability in S. haematobium endemic settings is limited by high cost, infrastructure requirements, and need for trained personnel (2,6). Importantly, the mucosal changes in visual FGS positive women can be similar to changes from other SRH, including cervical lesions caused by HPV, resulting in limited diagnostic specificity (6,7). In our study, agreement between two expert reviewers in detecting visual FGS was low, consistent with previous research in Zambia (6). This reinforces the limitation of visual diagnosis for FGS and highlights the need for standardised, scalable diagnostic

(6). Emerging technologies such as computer vision, powered by artificial intelligence (AI), are being explored to aid in the visual diagnosis of FGS (33,34,35). Computer vision tools are in the later stages of validation for the automated detection of cervical precancer and cancer in colposcopy images, potentially offering a point of integration for visual diagnosis of both FGS and cervical cancer (36). Prevalence of HR-HPV was highest among women young women 15-25 years old, consistent with previous studies (37-40). Across our study population, prevalence of molecular FGS decreased with increasing age and peaked among adolescents aged 15-19 years old. In contrast, more older women (aged 41-50 years old) were positive for visual FGS . These findings are consistent with previous studies (3, 4, 29, 42). The similar age distribution supports possible opportunities to integrate FGS into cervical cancer control programmes (7). This is particularly timely as Zambia transitions from VIA to HPV DNA-based cervical screening programmes (20). For instance, existing self-collection platform and laboratory infrastructures for cervical cancer screening could include molecular FGS testing in endemic districts, improving earlier detection and more efficient use of resources (7). Younger women are more susceptible to HR-HPV infection due to behavioural and biological factors, including early sexual debut, multiple sexual partners, low contraception use, and cervical ectopy (37-40). In S. haematobium endemic settings, women in this age group also tend to have higher intensity of S. haematobium infection and higher rates of Schistosoma DNA retrieval from the genital tract, likely due to increased vascularization which promotes inflammation and parasite DNA shedding on the mucosal surface (3,29,42). In contrast, older women typically show higher prevalence of visually diagnosed lesions from long-standing S. . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 15 haematobium egg deposition or chronic infection, reflecting the cumulative burden of FGS over time (3,29,42). This age-specific pattern suggests that, in S. haematobium endemic settings, molecular FGS screening could be integrated with HPV vaccination and education programmes targetting younger girls (aged 9-14 years old), while community-based integrated HPV and molecular FGS screening can be introduced for women of reproductive age eligible for cervical cancer screening (age 25 or 30 depending on HIV status) (19,20). For older women (aged over 35 years), FGS screening can be integrated into existing cervical cancer clinic-based screening and/or treatment programmes (19,20). These targeted age- specific efforts offer an approach for addressing the dual burden FGS and cervical cancer vulnerable populations. Prevalence of any HR-HPV did not vary by HIV status, differing from previous studies showing higher HR-HPV prevalence and persistence among women living with HIV (15). This finding may reflect the high proportion of participants on ART and younger age in our study population. ART has been reported to reduce HPV persistence and precancer and cancer incidence, especially when initiated early following HIV acquisition and before significant immune suppression (17). Yet, these benefits have primarily been demostranted in monitored cohorts where women achieve sustained viral suppression through long-term ART adherence and regular cervical cancer screening. In our community-based study, ART status was self-reported, and baseline data on CD4+ T-cell count and HIV plasma viral load were not available at the time of this analysis, limiting our ability to assess immune control and its associations with HPV infection. Of note, we observed a 1.7-fold higher prevalence of the most oncogenic HPV types 16/18/45 among women living with HIV compared to HIV negative women, consistent with the literature (43,44,45). With over 2,500 women recruited in the cohort, this is the largest study to date to evaluate the association between HR-HPV prevalence and FGS, diagnosed using both molecular and visual methods. The integrated nature of the study design, combining home and clinic-based sampling with multiple diagnostic methods allowed for comprehensive screening for FGS and SRH co-infections. The feasibility of this approach is reflected in the succesful recruitment and diagnostic completeness obtained. There are some limitations worth noting. Histological examination of cervical tissues for the detection of Schistosoma eggs was not performed, limiting the ability to compare molecular and visual FGS diagnoses against a

standard, as both have imperfect sensitivity and specificity (2,6,46). The reliability . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 16 of visual FGS diagnosis was limited by low agreement between two expert reviewers, highlighting the need for standardised visual diagnostic methods. Implementation of molecular FGS testing in routine clinical or programmatic setting is hindered by cost, technical requirements, and the need for trained personnel. Moreover, variations in assay design may affect comparability across laboratories for PCR testing. Although this study accounted for HIV and T. vaginalis status, it did not address potential confounding by other STIs, including Chlamydia trachomatis, Neisseria gonorrhoea, Mycoplasma genitalium, Herpes simplex virus, syphilis, and bacterial vaginosis, all of which can affect cervical inflammation and epithelial integrity (47). HIV status was self-reported for most participants which may have introduced reporting bias. Data on CD4+ T-cell count, time on ART, ART adherence and HIV plasma viral load among the study participants was not collected, potentially introducing further confounding. Further, the cross-sectional design of this analysis does not allow to distinguish between incident and persistent HR-HPV infections, limiting causal inferences on the association between FGS and HR- HPV. Longitudinal data from the ongoing Zipime-Weka-Schista study (27) will address some of these limitations in future analyses. This study contributes new evidence on the intersection of FGS, HR-HPV and SRH among women of reproductive age living, highlighting a significant association between molecular FGS and the most oncogenic HPV genotypes (HPV16/18/45). In line with the Sustainable Development Goals and the WHO targets to eliminate cervical cancer and schistosomiasis, our findings support the need for integrated strategies using highly specific, field-deployable, and cost-effective diagnostic methods. Declaration of interest We declare no competing interests.

We would like to thank and acknowledge all the study participants and the communities in Kafue and Livingstone for their engagement and support. We acknowledge the invaluable contribution of Zipime-Weka-Schista community workers, field teams and midwives. We also thank the wider Zipime-Weka-Schista Study team who contributed towards the design . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 17 and implementation of the study and Isaac Mshanga for his work on community sensitization and mobilization. We are grateful for our partners in Zambia, including the Ministry of Health and District Health Management Teams, as well as the administrative support teams at both Zambart and LSHTM. We gratefully acknowledge the team at the Leiden University Medical Centre (LUMC) for performing the CAA analysis. We thank the ODK forum for assistance with questionnaire construction and Chrissy Roberts (LSHTM) for his invaluable support with 3D printing of teaching models. Funding The Zipime-Weka-Schista study is funded through a UKRI Future Leaders Fellowship (MR/ T041900/1) awarded to Professor AL Bustinduy. Professor E Webb received funding from MRC Grant Reference MR/K012126/1. This award is jointly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement and is also part of the EDCTP2 programmme supported by the European Union. Olimpia Lamberti is funded by the Nagasaki University ‘Doctoral Program for World-leading Innovative and Smart Education’ for Global Health, KENKYU SHIDO KEIHI. . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 18

1 2 1. Kjetland EF, Leutscher PDC, Ndhlovu PD. A review of female genital 3 schistosomiasis.Trends in Parasitology. 2012 Feb;28(2):58–65. 4 5 2. Bustinduy AL, Randriansolo B, Sturt AS, Kayuni SA, Leustcher PDC, Webster BL, et al. 6 An update on female and male genital schistosomiasis and a call to integrate efforts to 7 escalate diagnosis, treatment and awareness in endemic and non-endemic settings: The time 8 is now. In: Advances in Parasitology [Internet]. Elsevier; 2022 [cited 2022 Mar 23]. p. 1–44. 9 Available from: https://linkinghub.elsevier.com/retrieve/pii/S0065308X21000592 10 11 3. Sturt AS, Webb EL, Phiri CR, Mweene T, Chola N, van Dam GJ, et al. Genital self 12 sampling compared with cervicovaginal lavage for the diagnosis of female genital 13 schistosomiasis in Zambian women: The BILHIV study. Cools P, editor. PLoS Negl Trop 14 Dis. 2020 Jul 14;14(7):e0008337. 15 16 4. Pillay P, Downs JA, Changalucha JM, Brienen EAT, Ramarokoto CE, Leutscher PDC, et 17 al. Detection of Schistosoma DNA in genital specimens and urine: A comparison between 18 five female African study populations originating from S. haematobium and/or S. mansoni 19 endemic areas. Acta Tropica. 2020 Apr;204:105363. 20 21 5. World Health Organization. Female genital schistosomiasis, a pocket atlas for clinical 22 health-care professionals. 23 24 6.Sturt A, Bristowe H, Webb E, Hansingo I, Phiri C, Mudenda M, et al. Visual diagnosis of 25 female genital schistosomiasis in Zambian women from hand-held colposcopy: agreement of 26 expert image review. Wellcome Open Res. 2023 Jan 10;8:14. 27 28 7. Lamberti O, Bozzani F, Kiyoshi K, Bustinduy AL. Time to bring female genital 29 schistosomiasis out of neglect. British Medical Bulletin. 2024 Jan 13;ldad034. 30 31 8. Bray F, Parkin DM, Gnangnon F, Tshisimogo G, Peko JF, Adoubi I, et al. Cancer in sub- 32 Saharan Africa in 2020: a review of current estimates of the national burden, data gaps, and 33 future needs. The Lancet Oncology. 2022 Jun;23(6):719–28. 34 35 9. Singh D, Vignat J, Lorenzoni V, Eslahi M, Ginsburg O, Lauby-Secretan B, et al. Global 36 estimates of incidence and mortality of cervical cancer in 2020: a baseline analysis of the 37 WHO 38 Global Cervical Cancer Elimination Initiative. The Lancet Global Health. 2023 39 Feb;11(2):e197–206. 40 41 10. Arbyn M, Weiderpass E, Bruni L, De Sanjosé S, Saraiya M, Ferlay J, et al. Estimates of 42 incidence and mortality of cervical cancer in 2018: a worldwide analysis. The Lancet Global 43 Health. 2020 Feb;8(2):e191–203. 44 45 11. Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global 46 cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 47 cancers in 185 countries. CA Cancer J Clin. 2024 May-Jun;74(3):229-263. doi: 48 10.3322/caac.21834. Epub 2024 Apr 4. PMID: 38572751. 49 50 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 19 12. IARC Working Group on the Evaluation of Cancer-Preventive Interventions, editor. 51 Cervical cancer screening. Lyon, France: International Agency for Research on Cancer; 2022. 52 1 p. (IARC handbooks of cancer prevention). 53 54 13. Wei F, Georges D, Man I, Baussano I, Clifford GM. Causal attribution of human 55 papillomavirus genotypes to invasive cervical cancer worldwide: a systematic analysis of the 56 global literature. The Lancet. 2024 Aug;404(10451):435–44. 57 58 14. Veldhuijzen NJ, Snijders PJ, Reiss P, Meijer CJ, Van De Wijgert JH. Factors affecting 59 transmission of mucosal human papillomavirus. Lancet Infect Dis. 2010 Dec;10(12):862–74. 60 61 15. Looker KJ, Rönn MM, Brock PM, Brisson M, Drolet M, Mayaud P, et al. Evidence of 62 synergistic relationships between HIV and Human Papillomavirus ( HPV ): systematic 63 reviews 64 and meta/i2 analyses of longitudinal studies of HPV acquisition and clearance by HIV status, 65 and 66 of HIV acquisition by HPV status. J Intern AIDS Soc [Internet]. 2018 Jun [cited 2022 Sep 67 7];21(6). Available from: https://onlinelibrary.wiley.com/doi/10.1002/jia2.25110 68 69 16. Stelzle D, Tanaka LF, Lee KK, Ibrahim Khalil A, Baussano I, Shah ASV, et al. Estimates 70 of the global burden of cervical cancer associated with HIV. The Lancet Global Health. 2021 71 Feb;9(2):e161–9. 72 73 17. Kelly H, Weiss HA, Benavente Y, De Sanjose S, Mayaud P, Qiao Y lin, et al. Association 74 of antiretroviral therapy with high-risk human papillomavirus, cervical intraepithelial 75 neoplasia, and invasive cervical cancer in women living with HIV: a systematic review and 76 meta-analysis. The Lancet HIV. 2018 Jan;5(1):e45–58. 77 78 18. Sturt A, Omar T, Hansingo I, Kamfwa P, Bustinduy A, Kelly H. Association of female 79 genital schistosomiasis and human papillomavirus and cervical pre-cancer: a systematic 80 review. BMC Women’s Health. 2025 Jan 3;25(1):2. 81 82 19. World Health Organization. Global strategy to accelerate the elimination of cervical 83 cancer 84 as a public health problem [Internet]. Geneva: World Health Organization; 2020 [cited 2022 85 Jan 27]. 52 p. Available from: https://apps.who.int/iris/handle/10665/336583 86 87 20. World Health Organization. WHO guideline for screening and treatment of cervical pre- 88 cancer lesions for cervical cancer prevention, second edition [Internet]. 2021. Available from: 89 Licence: CC BY-NC-SA 3.0 IGO. 90 91 21. Arbyn M, Verdoodt F, Snijders PJF, Verhoef VMJ, Suonio E, Dillner L, et al. Accuracy 92 of 93 human papillomavirus testing on self-collected versus clinician-collected samples: a meta- 94 analysis. The Lancet Oncology. 2014 Feb;15(2):172–83. 95 96 22. Arbyn M, Smith SB, Temin S, Sultana F, Castle P. Detecting cervical precancer and 97 reaching underscreened women by using HPV testing on self-samples: updated meta-98 analyses. 99 BMJ. 2018 Dec 5;k4823. 100 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 20 101 23. Kjetland EF, Ndhlovu PD, Mduluza T, Deschoolmeester V, Midzi N, Gomo E, et al. The 102 effects of genital schistosoma haematobium on human papillomavirus and the development 103 of 104 cervical neoplasia after five years in a Zimbabwean population. Eur J Gynaecol Oncol. 105 2010;31(2):169–73. 106 107 24. Shukla JD, Kleppa E, Holmen S, Ndhlovu PD, Mtshali A, Sebitloane M, et al. The 108 Association Between Female Genital Schistosomiasis and Other Infections of the Lower 109 Genital Tract in Adolescent Girls and Young Women: A Cross-Sectional Study in South 110 Africa. J Low Genit Tract Dis. 2023 Jul;27(3):291–6. 111 112 25. Kutz JM, Rausche P, Rasamoelina T, Ratefiarisoa S, Razafindrakoto R, Klein P, et al. 113 Female genital schistosomiasis, human papilloma virus infection, and cervical cancer in rural 114 Madagascar: a cross-sectional study. Infect Dis Poverty. 2023 Sep 25;12(1):89. 115 116 26. Mukerebe C, Cordeiro AA, Aristide C, Colombe S, Bullington BW, Kalluvya S, et al. 117 Schistosome Infection is Associated with High-Risk Human Papillomavirus Persistence, 118 Together with Altered Cervicovaginal Microbiota. J Infect Dis. 2025 Aug 22;jiaf447. 119 120 27. Shanaube K, Ndubani R, Kelly H, Webb EL, Mayaud P, Lamberti O, et al. The Zipime- 121 Weka-Schista study protocol: a longitudinal cohort study and economic evaluation of an 122 integrated home-based approach for genital multi-pathogen screening in women, including 123 female genital schistosomiasis, HPV, Trichomonas and HIV in Zambia. BMJ Open. 2024 124 Jun; 125 14(6):e080395. 126 127 28. Corstjens PLAM, De Dood CJ, Kornelis D, Tjon Kon Fat EM, Wilson RA, Kariuki TM, 128 et al. Tools for diagnosis, monitoring and screening of Schistosoma infections 129 utilizing lateral-flow based assays and upconverting phosphor labels. Parasitology. 2014 130 Dec;141(14):1841–55. 131 132 29. Kjetland EF, Hove RJT, Govo E, Midzi N, Gwanzura L. et al. Schistosomiasis PCR in 133 Vaginal Lavage as an Indicator of Genital Schistosoma haematobium Infection in Rural 134 Zimbabwean Women. The American Journal of Tropical Medicine and Hygiene. 2009 Dec 135 1;81(6):1050–5. 136 137 30. World Health Organization (WHO). WHO guideline on control and elimination of human 138 schistosomiasis. 2022. 139 140 31. Woodman CBJ, Collins SI, Young LS. The natural history of cervical HPV infection: 141 unresolved issues. Nat Rev Cancer. 2007 Jan;7(1):11–22. 142 143 32. Mukerebe C, Cordeiro AA, Aristide C, Colombe S, Bullington BW, Kalluvya S, et al. 144 Schistosome Infection is Associated with High-Risk Human Papillomavirus Persistence, 145 Together with Altered Cervicovaginal Microbiota. J Infect Dis. 2025 Aug 22;jiaf447. 146 147 33. Holmen SD, Kjetland EF, Taylor M, Kleppa E, Lillebø K, Gundersen SG, et al. 148 C olourimetric image analysis as a diagnostic tool in female genital schistosomiasis. Medical 149 Engineering & Physics. 2015 Mar;37(3):309–14. 150 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 21 151 34. Jin E, Noble JA, Gomes M. A Review of Computer-Aided Diagnostic Algorithms for 152 Cervical Neoplasia and an Assessment of Their Applicability to Female Genital 153 Schistosomiasis. Mayo Clinic Proceedings: Digital Health. 2023 Sep;1(3):247–57. 154 155 35. Lemin ME, Bustinduy AL, Roberts CH. Visual diagnostics for female genital 156 schistosomiasis and the opportunity for improvement using computer vision. Parasitology. 157 2025 Sep 12;1–41. 158 159 36. Befano B, Kalpathy-Cramer J, Egemen D, Inturrisi F, Jeronimo J, Rodríguez AC, et al. 160 Initial evaluation of a new cervical screening strategy combining human papillomavirus 161 genotyping and automated visual evaluation: the Human Papillomavirus-Automated 162 Visual Evaluation Consortium. J Natl Cancer Inst. 2025 Oct 1;117(10):2124–9. 163 164 37. Muchaili L, Simushi P, Mweene BC, Mwakyoma T, Masenga SK, Hamooya BM. 165 Prevalence and correlates of Human Papillomavirus infection in females from Southern 166 Province, Zambia: A cross-sectional study. Okunade KS, editor. PLoS ONE. 2024 Aug 167 1;19(8):e0299963. 168 169 38. Tchouaket MCT, Ka’e AC, Semengue ENJ, Sosso SM, Simo RK, Yagai B, et al. 170 Variability 171 of High-Risk Human Papillomavirus and Associated Factors among Women in Sub-Saharan 172 Africa: A Systematic Review and Meta-Analysis. Pathogens. 2023 Aug 11;12(8):1032. 173 174 39. Watson-Jones D, Baisley K, Brown J, Kavishe B, Andreasen A, Changalucha J, et al. 175 High 176 prevalence and incidence of human papillomavirus in a cohort of healthy young African 177 female 178 subjects. Sex Transm Infect. 2013 Aug;89(5):358–65. 179 180 40. Winer RL, Hughes JP, Feng Q, Xi LF, Cherne S, O’Reilly S, et al. Early Natural History 181 of Incident, Type-Specific Human Papillomavirus Infections in Newly Sexually Active 182 Young 183 Women. Cancer Epidemiology, Biomarkers & Prevention. 2011 Apr 1;20(4):699–707. 184 185 42. Lamberti O, Kayuni S, Kumwenda D, Ngwira B, Singh V, Moktali V, et al. Female 186 genital 187 schistosomiasis burden and risk factors in two endemic areas in Malawi nested in the 188 Morbidity 189 Operational Research for Bilharziasis Implementation Decisions (MORBID) cross-sectional 190 study. Ekpo UF, editor. PLoS Negl Trop Dis. 2024 May 8;18(5):e0012102. 191 192 43. Okoye JO, Ofodile CA, Adeleke OK, Obioma O. Prevalence of high-risk HPV genotypes 193 in sub-Saharan Africa according to HIV status: a 20-year systematic review. Epidemiol 194 Health. 195 2021 May 25;43:e2021039. 196 197 44. Clifford GM, Tully S, Franceschi S. Carcinogenicity of Human Papillomavirus (HPV) 198 Types in HIV-Positive Women: A Meta-Analysis From HPV Infection to Cervical Cancer. 199 Clinical Infectious Diseases. 2017 May 1;64(9):1228–35. 200 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 201 45. Seyoum A, Assefa N, Gure T, Seyoum B, Mulu A, Mihret A. Prevalence and Genotype 202 Distribution of High-Risk Human Papillomavirus Infection Among Sub-Saharan African 203 Women: A Systematic Review and Meta-Analysis. Front Public Health. 2022 Jul 204 8;10:890880. 205 206 46. Ndubani R, Lamberti O, Kildemoes A, Hoekstra P, Fitzpatrick J, Kelly H, et al. The first 207 BILGENSA Research Network workshop in Zambia: identifying research priorities, 208 challenges and needs in genital bilharzia in Southern Africa. Wellcome Open Res. 2024 Jul 209 10;9:360. 210 211 47. Lamberti O, Kumwenda D, Kelly H, Kamfwa P, Kayuni SK, Stothard JR, Bustinduy AL. 212 Female genital schistosomiasis and other cervicovaginal co-infection including zoonotic and 213 hybrid schistosomes. Lancet Microbes 2025. In press. 214 215 216 Tables and figures for the manuscript “Association between female genital 217 schistosomiasis and high-risk human papillomavirus among women of reproductive age 218 in Zambia: the Schista study” 219 220 221 222 223 Figure 1: Zipime-Weka-Schista study flow diagram for participant recruitment at baseline 224 and screening of molecular FGS, visual FGS and HR-HPV. 225 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 23 226 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint A 227 228 B 229 230 Figure2: Distribution of positive diagnostic test results by age categories. A: Distribution of 231 molecular FGS and visual FGS by age groups. B: Prevalence of any HR-HPV infection, 232 HPV16/18/45 and HPV16 only by age categories. The corresponding data is presented in 233 Table 1 and S1 Table. 234 235 236 Table 1: Prevalence of any high-risk HPV (HR-HPV) stratified by socio-demographic 237 characteristics and co-infections, with univariable logistic regression estimates across the 238 study population (N = 2,401). 239 N (%) HR-HPV Neg N (%) HR-HPV Pos N (%) Crude OR (95%CI) p-value . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 25 Total 2,532 (100) 1,711(71.3) 690 (28.7) Socio-demographic characteristics Age (years) 15-19 330 (13.0) 199 (64.0) 112 (36.0) 2.2 (1.3-3.5) <0.001 20-25 674 (26.6) 412 (64.9) 223 (35.1) 2.1 (1.3-3.3) 26-30 553 (21.8) 380 (72.1) 147 (27.9) 1.5 (0.9-2.4) 31-35 341 (13.5) 245 (75.9) 78 (24.2) 1.2 (0.8-2.0) 36-40 293 (11.6) 223 (80.2) 55 (19.8) 1.0 (0.6-1.6) 41-45 200 (7.9) 144 (75.4) 47 (24.6) 1.3 (0.7-2.1) 46-50 141 (5.6) 108 (79.4) 28 (20.6) Ref Marital status Single 330 (13.0) 559 (63.1) 327 (36.9) 2.0 (1.6-2.4) <0.001 Married 674 (26.6) 1,023 (77.0) 306 (23.0) Ref Divorced/separated 553 (21.8) 92 (71.9) 36 (28.1) 1.3 (0.9-2.0) Widowed 341 (13.5) 36 (63.2) 21 (36.8) 2.0 (1.1-3.4) Education No schooling 49 (1.9) 36 (78.3) 10 (21.7) Ref 0.21 Some/Completed primary school 909 (35.9) 620 (72.6) 234 (27.4) 1.4 (0.7-2.8) Some/completed secondary school 1,344 (53.1) 898 (70.2) 381 (29.8) 1.5 (0.8-3.1) Some/completed trade school or degree 229 (9.1) 156 (70.6) 65 (29.4) 1.5 (0.7-3.2) District of residence Shikoshwe 1,176 (46.5) 818 (72.1) 316 (27.9) Ref 0.44 Livingstone 1,196 (47.2) 781 (70.4) 328 (29.6) 1.1 (0.9-1.3) Chanyanya 160 (6.3) 112 (70.9) 46 (29.1) 1.1 (0.7-1.5) Sexual and Reproductive health behaviours and outcomes Number of sexual partners in the last 6 months 0 131 (5.2) 88 (69.8) 38 (30.2) Ref 0.49 1 2,144 (84.7) 1,457 (71.7) 574 (28.3) 0.9 (0.6-1.4) 2 152 (6.0) 96 (67.1) 47 (32.9) 1.1 (0.7-1.9) 2 or more 105 (4.2) 70 (69.3) 31 (30.7) 1.0 (0.6-1.8) Age of sexual debut 20 years old 282 (11.2) 200 (75.8) 64 (24.2) 0.7 (0.5-1.0) Time to conception of previous pregnancy 0-3 months 401 (19.2) 277 (74.1) 97 (25.9) Ref 0.4 4-6 months 95 (4.5) 66 (69.5) 29 (30.5) 1.3 (0.8-2.1) 10-12 months 1,038 (49.6) 722 (73.7) 258 (26.3) 1.0 (0.8-1.3) I don’t remember 31 (1.5) 24 (80.0) 6 (20.0) 0.7 (0.3-1.8) Pregnancy was unplanned 529 (25.3) 354 (70.0) 152 (30.0) 1.2 (0.9-1.7) Number of pregnancies Never pregnant 437 (17.3) 267 (64.3) 148 (35.7) 1.8 (1.4-2.5) <0.001 1 pregnancy 551 (21.8) 335 (64.6) 184 (35.5) 1.8 (1.4-2.5) 2 pregnancies 431 (17.0) 289 (71.0) 118 (29.0) 1.4 (1.0-1.9) 3 pregnancies 402 (15.9) 287 (74.4) 99 (25.7) 1.1 (0.8-1.6) 4 pregnancies 289 (11.4) 227 (82.3) 49 (17.8) 0.7 (0.5-1.1) > 4 pregnancies 422 (16.7) 306 (76.9) 92 (23.1) Ref Type of contraception used None 10 (0.8%) 7 (77.8) 2 (22.2) Ref 0.41 Barrier method (condom, diaphragm or IUD) 139 (11.4%) 101 (74.8) 34 (25.2) 1.2 (0.2-5.9) Hormonal method (implant, injectable or oral pill) 999 (82.1%) 697 (71.7) 275 (28.3) 1.4 (0.3-6.7) Sterilization method 1 (0.1%) 1 Not enough data . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 26 Combination (hormonal and barrier) 69 (5.7%) 46 (68.7) 21 (31.3) 1.6 (0.3-8.4) Number of stillbirths None 1,978 (94.5) 1,360 (72.6) 513 (27.4) Ref 0.006 One or more 116 (5.5) 351 (66.5) 177 (33.5) 1.3 (1.1-1.6) Co-infections HIV status Negative 1,970 (77.8) 1,330 (71.4 ) 534 (28.7) Ref 0.74 Positive 443 (17.5) 304 (71.7) 120 (28.3) 1.0 (0.8-1.2) Unknown 119 (4.7) 77 (68.1) 36 (31.9) 1.2 (0.8-1.8) Self-reported antiretroviral therapy (ART) use among HIV-positive (Ntot=443) No 38 (8.6) 20 (54.1) 17 (45.7) 2.3 (1.2-2.4) 0.02 Yes 405 (91.4) 284 (73.4) 103 (26.6) Ref Trichomonas vaginalis status Negative 2,143 (89.7) 1,444 (71.5) 575 (28.5) Ref 0.15 Positive 246 (10.3) 161 (67.1) 79 (32.9) 1.2 (0.9-1.6) Molecular FGS1 Negative 2,366 (93.5) 1,610 (71.8) 633 (28.2) Ref 0.04 Positive 165 (6.5) 101 (63.9) 57 (36.1) 1.5 (1.0-2.0) Median Ct (IQR) 35.1 (7.4-31.6) 35.7 (31.3-39.0) 35.1 (31.8-38.7) Visual FGS by colposcopy2 Negative 1,096 (64.8) 729 (68.8) 331 (31.2) Ref 0.17 Positive 595 (35.2) 417 (72.0) 162 (28.0) 0.9 (0.7-1.1) Schistosoma infection by Circulating Anodic Antigen (CAA) Negative 2,129 (84.6) 1,437 (71.2) 580 (28.8) Ref 0.99 Positive 388 (15.4) 263 (71.3) 106 (28.7) 1.0 (0.8-1.3) Median pg/mL3 (IQR) 4.6 (1.1-30.6) 3.4 (1.0-26.7) 10.2 (1.2-50.3) S. haematobium by microscopy Negative 2,400 (94.8) 1,635 (71.9) 639 (28.1) Ref 0.004 Positive 132 (5.2) 76 (59.8) 51 (40.2) 1.7 (1.2-2.5) Mean egg-count (SD) per 10mL3 4.8 (5.5) 4.9 (4.8) 4.8 (6.7) Percentages (%) in the first column are based on the total number of observations (N=2,532). Percentages (%) on the second and third columns are calculated within each row total. 1Molecular FGS refers to PCR diagnosis of either home-based self-collected cervicovaginal swabs or clinic-based provider-collected cervicovaginal swabs. 2 Visual FGS defined as a positive if confirmed by both reviewers 1 and 2, or in case of disagreement, by reviewer 3. The association between the single visual FGS and HR-HPV infection are presented in S2 Table 3Mean egg count, CAA concentrations and PCR Ct-values are restricted to positive tests. Abbreviations: AOR = Adjusted Odds Ratio, CI = Confidence Interval 240 241 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 242 The regression model was adjusted for molecular FGS status, age, marital status and number of pregnancies. 243 Abbreviations: aOR= Adjusted odds ratios. 244 245 Figure 3: Multivariable logistic regression model parameter estimates with prevalence of any 246 HR-HPV as the dependent variable across the study population (N=2,401). 247 248 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 28 249 Table 2: Prevalence of HPV16/18/45 stratified by socio-demographic characteristics and co-250 infections, with univariable logistic regression estimates across the study population (N = 251 2,401). 252 HPV16/18/45 Neg N (%) HPV16/18/45 Pos N (%) Crude OR (95%CI) p-value Total 2,170 (90.4) 231 (9.6) Socio-demographic characteristics Age (years) 15-19 279 (89.7) 32 (10.3) 2.1 (0.91-4.9) 0.09 20-25 569 (89.6) 66 (10.4) 2.1 (1.0-4.8) 26-30 472 (89.6) 55 (10.4) 2.1 (1.0-4.8) 31-35 291 (90.1) 32 (9.9) 2.0 (0.9-4.7) 36-40 260 (93.5) 18 (6.5) 1.3 (0.5-3.1) 41-45 170 (89.0) 21 (11.0) 2.3 (0.9-5.1) 46-50 129 (94.9) 7 (5.2) Ref Marital status Single 770 (86.9) 116 (13.1) 1.9 (1.5-2.6) 0.001 Married 1,233 (92.8) 96 (7.2) Ref Divorced/ separated 113 (88.3) 15 (11.7) 1.7 (1.0-3.0) Widowed 53 (93.0) 4 (7.0) 1.0 (0.3-2.7) Education No schooling 44 (95.7) 2 (4.4) Ref 0.87 Some/Completed primary school 769 (90.1) 85 (9.9) 2.4 (0.6-10.2) Some/completed secondary school 1,157 (90.5) 122 (9.5) 2.3 (0.6-9.7) Some/completed trade school or degree 199 (90.1) 22 (10.0) 2.4 (0.6-10.7) District of residence Shikoshwe 1,047 (92.3) 87 (7.7) Ref <0.001 Livingstone 990 (89.3) 119 (10.7) 1.4 (1.1-1.9) Chanyanya 133 (84.2) 25 (15.8) 2.3 (1.4-3.7) Sexual and Reproductive health behaviours and outcomes Number of sexual partners in the last 6 months 0 115 (91.3%) 11 (8.7%) Ref 0.60 1 1,836 (90.4%) 195 (9.6%) 1.1 (0.6-2.1) 2 129 (90.2%) 14 (9.8%) 1.1 (0.5-2.6) More than 2 90 (89.1%) 11 (10.9%) 1.3 (0.5-3.0) Age of sexual debut 20 years old 239 (90.5%) 25 (9.5%) 0.8 (0.5-1.3) Time to conception of previous pregnancy 0-3 months 350 (93.6) 24 (6.4) Ref 0.26 4-6 months 85 (89.5) 10 (10.5) 1.7 (0.8-3.7) 10-12 months 891 (90.9) 89 (9.1) 1.5 (0.9-2.3) I don’t remember 29 (93.3) 2 (6.7) 1.0 (0.2-4.6) Pregnancy was unplanned 452 (89.3) 54 (10.7) 1.7 (1.1-2.9) . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 29 Type of contraception used None 78 (86.7%) 12 (13.3%) Ref 0.50 Barrier method (condom, diaphragm or IUD) 22 (91.7%) 2 (8.3%) 0.6 (0.1-2.8) Hormonal method (implant, injectable or oral pill) 254 (90.1%) 28 (9.9%) 0.7 (0.3-1.5) Sterilization method+ 1 (100%) 0 Not enough data Combination (hormonal and barrier) 681 (90.3%) 73 (9.7%) 0.7 (0.4-1.3) Number of pregnancies Never pregnant 363 (87.5) 52 (12.5) 1.9 (1.1-3.4) 0.01 1 pregnancy 469 (90.4) 50 (9.6) 1.4 (0.8-2.5) 2 pregnancies 361 (88.7) 46 (11.3) 1.7 (1.0-3.0) 3 pregnancies 355 (92.0) 31 (8.0) 1.2 (0.7-2.1) 4 pregnancies 257 (93.1) 19 (6.9) 1.2 (0.7-2.2) > 4 pregnancies 365 (91.7) 33 (8.3) Ref Number of stillbirths None 1,708 (91.1) 166 (8.9) Ref 0.02 One or more 463 (87.7) 65 (12.3) 1.4 (1.1-2.0) Co-infections Molecular FGS1 Negative 2,037 (90.8) 206 (9.2) Ref 0.007 Positive 133 (84.2) 25 (15.8) 1.9 (1.2-2.9) Visual FGS by colposcopy2 Negative 947 (89.3) 113 (10.7) Ref 0.28 Positive 527 (91.0) 52 (9.0) 0.8 (0.6-1.2) HIV status Negative 1,698 (91.1) 166 (8.9) Ref 0.07 Positive 371 (87.5) 53 (12.5) 1.5 (1.1-2.0) Unknown 101 (89.4) 12 (10.6) 1.2 (0.7-2.3) Self-reported antiretroviral therapy (ART) use among HIV-positive No 30 (81.1) 7 (18.9) 1.8 (0.7-4.2) 0.22 Yes 341 (88.1) 46 (11.9) Ref Trichomonas (T.) vaginalis status (Ntot=1,556) Negative 1,842 (91.2) 177 (8.8) Ref 0.004 Positive 205 (85.4) 35 (14.6) 1.8 (1.2-2.6) S. haematobium by Circulating Anodic Antigen (CAA) (Ntot=1,685) Negative 1,829 (90.7) 188 (9.3) Ref 0.22 Positive 327 (88.6) 42 (11.4) 1.2 (0.9-1.8) S. haematobium by urine microscopy (Ntot=1,691) Negative 2,063 (90.7) 211 (9.3) Ref 0.02 Positive 107 (84.3) 20 (15.8) 1.8 (1.1-3.0) Percentages (%) on the second and third columns are calculated within each row total. 253 1Molecular FGS refers to PCR diagnosis of either home-based self-collected cervicovaginal swabs or clinic-based provider-254 collected cervicovaginal swabs. 255 2 Visual FGS defined as a positive if confirmed by both reviewers 1 and 2, or in case of disagreement, by reviewer 3. The 256 association between the single visual FGS and infection with HPV16/18/45 are presented in S4 Table 257 Abbreviations: AOR = Adjusted Odds Ratio, CI = Confidence Interval 258 259 260 261 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 262 263 The model was adjusted for molecular FGS status, HIV status, T. vaginalis status, district of residence, marital 264 status and number of pregnancies. Abbreviations: aOR=Adjusted Odds Ratio, CI=Confidence Intervals. 265 Figure 4: Multivariable logistic regression model parameter estimates for prevalence of HPV16/18/45 266 as the dependent variable in the study population (N=2,401). 267 268 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 31 Table 3: Prevalence of HPV16 only stratified by socio-demographic characteristics and co-269 infections, with univariable logistic regression estimates across the study population (N = 270 2,401). 271 HPV16 Neg N (%) HPV16 Pos N (%) Crude OR (95%CI) p-value Total 2,287 (95.3) 114 (4.8) Socio-demographic characteristics Age (years) 15-19 296 (95.2) 15 (4.8) 1.1 (0.4-2.9) 0.50 20-25 602 (94.8) 33 (5.2) 1.2 (0.5-2.9) 26-30 504 (95.6) 23 (4.4) 1.0 (0.4-2.5) 31-35 302 (93.5) 21 (6.5) 1.5 (0.6-3.8) 36-40 271 (97.5) 7 (2.5) 0.6 (0.2-1.7) 41-45 182 (95.3) 9 (4.7) 1.1 (0.4-3.1) 46-50 130 (95.6) 6 (4.4) Ref Marital status Single 828 (93.5) 58 (6.6) 2.0 (1.3-2.9) 0.03 Married 1,283 (96.5) 46 (3.5) Ref Divorced/ separated 120 (93.8) 8 (6.3) 1.9 (0.9-4.0) Widowed 55 (96.5) 2 (3.5) 1.0 (0.2-4.3) Education No schooling 45 (97.8) 1 (2.2) Ref 0.38 Some/Completed primary school 815 (95.4) 39 (4.6) 2.2 (0.3-16.0) Some/completed secondary school 1,218 (95.2) 61 (4.8) 2.3 (0.3-16.6) Some/completed trade school or degree 208 (94.1) 13 (5.9) 2.8 (0.4-22.1) District of residence Shikoshwe 1,091 (96.2) 43 (3.8) Ref 0.055 Livingstone 1,047 (94.4) 62 (5.6) 1.5 (1.0-2.2) Chanyanya 149 (94.3) 9 (5.7) 1.5 (0.7-3.2) Sexual and Reproductive Health Behaviours and Outcomes Number of sexual partners in the last 6 months 0 118 (94.4%) 7 (5.6%) Ref 0.94 1 1,937 (95.4%) 94 (4.6%) 0.8 (0.4-1.8) 2 134 (93.7%) 9 (6.3%) 1.1 (0.4-3.2) More than 2 97 (96.0%) 4 (4.0%) 0.7 (0.2-2.5) Age of sexual debut 20 years-old 257 (97.4%) 7 (2.7%) 0.5 (0.2-1.2) Time to conception 0-3 months 363 (97.1) 11 (2.9) Ref 0.28 4-6 months 90 (94.7) 5 (5.3) 1.8 (0.6-5.4) 10-12 months 938 (95.7) 42 (4.3) 1.5 (0.8-2.9) I don’t remember 28 (93.3) 2 (6.7) 2.4 (0.5-11.2) Pregnancy was unplanned 476 (94.1) 30 (5.9) 2.1 (1.0-4.2) Type of contraception used None 84 (93.3%) 6 (6.7%) Ref 0.72 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 32 Barrier method (condom, diaphragm or IUD) 23 (95.8%) 1 (4.2%) 0.6 (0.07-5.3) Hormonal method (implant, injectable or oral pill) 268 (95.4%) 13 (4.6%) 0.7 (0.2-1.8) Sterilization method+ 1 (100%) No data Combination (hormonal and barrier) 714 (94.7%) 40 (5.3%) 0.8 (0.32-1.9) Number of pregnancies Never pregnant 391 (94.2) 24 (5.8) 1.7 (0.9-3.3) 0.04 1 pregnancy 493 (95.0) 26 (5.0) 1.4 (0.7-2.8) 2 pregnancies 380 (93.4) 27 (6.6) 1.9 (1.0-3.8) 3 pregnancies 373 (96.6) 13 (3.4) 1.0 (0.4-2.1) 4 pregnancies 266 (96.4) 10 (3.6) 1.0 (0.5-2.4) > 4 pregnancies 384 (96.5) 14 (3.5) Ref Number of stillbirths None 1,789 (95.5) 84 (4.5) Ref 0.25 One or more 498 (94.3) 30 (5.7) 1.3 (0.8-2.0) Co-infections Molecular FGS1 Negative 2,142 (95.5) 101 (4.5) Ref 0.04 Positive 145 (91.8) 13 (8.2) 1.9 (1.0-3.5) Visual FGS by point-of-care colposcopy2 Negative 1,003 (94.6) 57 (5.4) Ref 0.27 Positive 555 (95.9) 24 (4.2) 0.8 (0.5-1.2) HIV status Negative 1,782 (95.6) 82 (4.4) Ref 0.15 Positive 399 (94.1) 25 (5.9) 1.4 (0.9-2.2) Unknown 106 (93.8) 7 (6.2) 1.4 (0.6-3.2) Self-reported antiretroviral therapy (ART) use among HIV-positive No 35 (94.6) 2 (5.4) Ref 0.89 Yes 364 (94.1) 23 (5.9) 1.1 (0.3-4.9) Trichomonas (T.) vaginalis status (Ntot=1,556) Negative 1,927 (95.4) 92 (4.6) Ref 0.25 Positive 225 (93.8) 15 (6.2) 1.4 (0.8-2.5) S. haematobium by Circulating Anodic Antigen (CAA) (Ntot=1,685) Negative 1,924 (95.4) 93 (4.6) Ref 0.42 Positive 348 (94.3) 21 (5.7) 1.2 (0.8-2.0) S. haematobium by urine microscopy (Ntot=1,691) Negative 2,168 (95.3) 106 (4.7) Ref 0.40 Positive 119 (93.7) 8 (6.3) 1.4 (0.7-2.9) Percentages (%) on the second and third columns are calculated within each row total. 1 Molecular FGS refers to PCR diagnosis of either home-based self-collected cervicovaginal swabs or clinic-based provider-collected cervicovaginal swabs. 2 Visual FGS defined as a positive if confirmed by both reviewers 1 and 2, or in case of disagreement, by reviewer 3. The associa tion between the single visual FGS and infection with HPV16 are presented in S5 Table Abbreviations: AOR = Adjusted Odds Ratio, CI = Confidence Interval 272 273 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint 274 The logistic regression model was adjusted for molecular FGS status, marital status and number of pregnancies. 275 Abbreviations: aOR= Adjusted odds ratio, CI= Confidence Intervals 276 Figure 5: Multivariable logistic regression model parameter estimates for prevalence of 277 HPV16 as the dependent variable in the study population (N=2,401). 278 279 280 281 282 283 284 . CC-BY-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint The copyright holder for thisthis version posted November 30, 2025. ; https://doi.org/10.1101/2025.11.27.25341145doi: medRxiv preprint