Meta-analysis and Time Series Projection of Human Papillomavirus Prevalence Among Women in Honduras (1990-2023)

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HPV prevalence trends across age groups must be understood to build effective preventative measures. Objective To systematically analyze HPV prevalence among Honduran women from 1990 to 2023 across different age groups, and to project future trends through 2035 using time series forecasting methods. Methods PRISMA 2020 guided our proportions systematic review and meta-analysis. PubMed, Google Scholar, Tz’ibalnaah, and SciELO searches found age-stratified HPV prevalence studies in Honduran women from 1990 to 2023. We used MedCalc v19.7.1 for meta-analysis and Holt-Winters exponential smoothing in Python v3.10.3 for prevalence estimations. Model accuracy was measured by RMSE and MAE. Results Four studies met inclusion criteria, encompassing data from 1999 to 2023. The pooled HPV prevalence was 42% (95% CI: 21.8%), with substantial heterogeneity (I2 > 75%). Age-stratified analysis revealed highest prevalence in women aged 15-24 years (10.65% in 2023, increased from 1.26% in 1999) and declining prevalence in women >35 years. Time series projections indicated continued increasing trends for women <35 years and stabilizing or declining trends for those ≥35 years. The Holt-Winters model demonstrated optimal fit for the 35-44 age group (RMSE=0.26, MAE=0.25), but substantial prediction errors for younger age groups (RMSE=3.77 for ages 25-34) highlight the limitations of forecasting with limited temporal data points. Conclusions HPV prevalence shows divergent age-specific trends in Honduras, with increasing rates among younger women and decreasing rates in older age groups. These findings suggest differential impacts of public health interventions across age cohorts and highlight the need for enhanced vaccination coverage and sexual health education targeting adolescents and young adults. The limited number of temporal observations constrains forecast reliability, emphasizing the need for strengthened epidemiological surveillance systems. " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/14-1179", "name": "Meta-analysis and Time Series Projection of Human Papillomavirus Prevalence..." } } ] } Home Browse Meta-analysis and Time Series Projection of Human Papillomavirus Prevalence... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Diaz S, Montoya M, Zelaya A et al. Meta-analysis and Time Series Projection of Human Papillomavirus Prevalence Among Women in Honduras (1990-2023) [version 1; peer review: awaiting peer review] . F1000Research 2025, 14 :1179 ( https://doi.org/10.12688/f1000research.172083.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Systematic Review Meta-analysis and Time Series Projection of Human Papillomavirus Prevalence Among Women in Honduras (1990-2023) [version 1; peer review: awaiting peer review] Salvador Diaz 1 , Marissa Montoya https://orcid.org/0000-0001-6917-9617 1 , Arnoldo Zelaya 1,2 , [...] Jorge Valle 1 , Carlos Agudelo-Santos 3 , Marcio Madrid 1,2 , Melania Madrid 1 , Alicia Diaz 4 , Yolly Molina 3 , Isaac Zablah https://orcid.org/0000-0002-1410-7189 1 Salvador Diaz 1 , Marissa Montoya https://orcid.org/0000-0001-6917-9617 1 , [...] Arnoldo Zelaya 1,2 , Jorge Valle 1 , Carlos Agudelo-Santos 3 , Marcio Madrid 1,2 , Melania Madrid 1 , Alicia Diaz 4 , Yolly Molina 3 , Isaac Zablah https://orcid.org/0000-0002-1410-7189 1 PUBLISHED 29 Oct 2025 Author details Author details 1 National Autonomous University of Honduras Faculty of Medical Sciences, Tegucigalpa, Francisco Morazan, 11101, Honduras 2 Hospital General San Felipe, Tegucigalpa, Francisco Morazan, 11101, Honduras 3 Center for Biomedical Imaging Diagnostics Research and Rehabilitation, National Autonomous University of Honduras, Tegucigalpa, Francisco Morazan, 11101, Honduras 4 Universidad Catolica de Honduras Facultad de Ciencias de la Salud, Tegucigalpa, Francisco Morazan, Honduras Salvador Diaz Roles: Conceptualization, Formal Analysis, Methodology Marissa Montoya Roles: Data Curation, Supervision Arnoldo Zelaya Roles: Investigation, Supervision, Writing – Review & Editing Jorge Valle Roles: Formal Analysis, Methodology, Validation Carlos Agudelo-Santos Roles: Writing – Review & Editing Marcio Madrid Roles: Formal Analysis Melania Madrid Roles: Data Curation, Resources, Writing – Review & Editing Alicia Diaz Roles: Data Curation, Writing – Review & Editing Yolly Molina Roles: Conceptualization, Investigation Isaac Zablah Roles: Data Curation, Resources, Writing – Review & Editing OPEN PEER REVIEW REVIEWER STATUS AWAITING PEER REVIEW This article is included in the Global Public Health gateway. Abstract Background Human papillomavirus (HPV) infection represents a major public health challenge in Latin America, with limited epidemiological data available for Honduras. HPV prevalence trends across age groups must be understood to build effective preventative measures. Objective To systematically analyze HPV prevalence among Honduran women from 1990 to 2023 across different age groups, and to project future trends through 2035 using time series forecasting methods. Methods PRISMA 2020 guided our proportions systematic review and meta-analysis. PubMed, Google Scholar, Tz’ibalnaah, and SciELO searches found age-stratified HPV prevalence studies in Honduran women from 1990 to 2023. We used MedCalc v19.7.1 for meta-analysis and Holt-Winters exponential smoothing in Python v3.10.3 for prevalence estimations. Model accuracy was measured by RMSE and MAE. Results Four studies met inclusion criteria, encompassing data from 1999 to 2023. The pooled HPV prevalence was 42% (95% CI: 21.8%), with substantial heterogeneity (I 2 > 75%). Age-stratified analysis revealed highest prevalence in women aged 15-24 years (10.65% in 2023, increased from 1.26% in 1999) and declining prevalence in women >35 years. Time series projections indicated continued increasing trends for women <35 years and stabilizing or declining trends for those ≥35 years. The Holt-Winters model demonstrated optimal fit for the 35-44 age group (RMSE=0.26, MAE=0.25), but substantial prediction errors for younger age groups (RMSE=3.77 for ages 25-34) highlight the limitations of forecasting with limited temporal data points. Conclusions HPV prevalence shows divergent age-specific trends in Honduras, with increasing rates among younger women and decreasing rates in older age groups. These findings suggest differential impacts of public health interventions across age cohorts and highlight the need for enhanced vaccination coverage and sexual health education targeting adolescents and young adults. The limited number of temporal observations constrains forecast reliability, emphasizing the need for strengthened epidemiological surveillance systems. READ ALL READ LESS Keywords Honduras, Human papillomavirus, Meta-analysis, Time series, Holt-Winters, Prevalence, Epidemiology, Forecasting Corresponding Author(s) Isaac Zablah ( [email protected] ) Close Corresponding author: Isaac Zablah Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2025 Diaz S et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Diaz S, Montoya M, Zelaya A et al. Meta-analysis and Time Series Projection of Human Papillomavirus Prevalence Among Women in Honduras (1990-2023) [version 1; peer review: awaiting peer review] . F1000Research 2025, 14 :1179 ( https://doi.org/10.12688/f1000research.172083.1 ) First published: 29 Oct 2025, 14 :1179 ( https://doi.org/10.12688/f1000research.172083.1 ) Latest published: 29 Oct 2025, 14 :1179 ( https://doi.org/10.12688/f1000research.172083.1 ) 1. Introduction Human papillomavirus (HPV) infection represents a significant public health challenge in Latin America, especially in Central American nations where the disease has a pronounced impact. 1 HPV is the main cause of cervical cancer, which is the fourth most common cancer in women around the world. It is also still one of the main causes of cancer deaths in low- and middle-income countries. 2 In Honduras, as in other developing countries, a thorough comprehension of HPV epidemiological trends and related risk factors is crucial for the execution of effective prevention and control measures. There are more than 200 viruses that are related to HPV. The high-risk oncogenic types, especially HPV-16 and HPV-18, cause about 70% of cervical cancer cases around the world. 2 Low-risk types, mainly HPV-6 and HPV-11, cause genital condylomatosis (anogenital warts), which is the most common sexually transmitted infection (STI) in Honduras. 3 The virus is very easy to spread; after having unprotected sex with an infected partner, the transmission rate is almost 75%. 4 Early sexual debut, having multiple sexual partners, not using condoms consistently, and partner-related factors like non-monogamy are all known risk factors for getting HPV. 2 The Honduran Ministry of Health (SESAL) reported 7,076 cases of major STIs (syphilis, genital herpes, genital warts, gonorrhea, and HIV) in 2018, with papillomavirus infections constituting sixty percent of STI diagnoses. 3 Between 2016 and 2021, there were 18,957 official cases of HPV, which shows how important the disease is from an epidemiological point of view. Nonetheless, comprehensive examinations of temporal trends and age-specific prevalence patterns are still limited in the existing literature. Prior vaccination and public health campaigns, especially those conducted alongside HIV/AIDS awareness initiatives from 1980 to 2000, may have affected the dynamics of HPV transmission among various birth cohorts. HPV vaccination has been gradually incorporated into Honduras’ Expanded Program on Immunization (PAI) since 2006; however, coverage rates and program continuity have been impacted by challenges within the health system and political instability. 5 This study aims to: (1) systematically review and meta-analyze published studies on HPV prevalence among Honduran women, stratified by age groups; (2) calculate age-specific prevalence rates adjusted for population denominators; (3) project future prevalence trends from 2025 to 2035 using non-seasonal time series analysis with the Holt-Winters method; and (4) compare findings with regional and global HPV epidemiological data. These analyses may guide evidence-based STI prevention initiatives and resource distribution for HPV management in Honduras. 2. Methods 2.1 Study design This study utilized a two-phase methodology: (1) a systematic review and meta-analysis of studies on HPV prevalence, and (2) a time series forecasting of age-specific prevalence trends. The systematic review was executed and documented in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. 6 The completed PRISMA 2020 checklist is available at Zenodo. 7 This research entailed secondary analysis of published aggregate data and did not necessitate ethics committee approval. No individual patient data was accessed or analyzed. 2.2 Search strategy and information sources We conducted a comprehensive literature search in four electronic databases: PubMed, 8 Google Scholar, 9 Tz’ibalnaah (National Autonomous University of Honduras repository), 10 and SciELO (Scientific Electronic Library Online). 11 The search took place in January 2025 and included works published between January 1990 and December 2024. Search terms employed were: “ HPV Honduras ”, “ human papillomavirus Honduras ”, “ papilomavirus humano Honduras ”, and “ VPH Honduras ” without language restrictions. The search strategy was deliberately broad to maximize sensitivity and minimize the risk of missing relevant studies. We manually searched the reference lists of included studies to identify additional relevant publications. All database searches were documented with dates and results counts to ensure reproducibility. The complete search strategy is available in the PRISMA checklist. To address potential retrieval bias, we included both international databases (PubMed, Google Scholar, SciELO) and a local Honduran repository (Tz’ibalnaah) to capture studies that might not be indexed in major international databases. This approach aimed to minimize geographic and language-related publication bias common in Latin American epidemiological research. 2.3 Eligibility criteria Studies were eligible for inclusion if they met all the following criteria: - Study design: Observational (cross-sectional, cohort, or case-control) reporting HPV prevalence data - Population: Women residing in Honduras, regardless of clinical presentation - Outcome: Laboratory-confirmed HPV infection prevalence reported with age stratification - Age stratification: Data available across comparable age groups (preferably 15-24, 25-34, 35-44, 45-54, 55+ years) - Diagnostic methods: Laboratory confirmation via polymerase chain reaction (PCR), hybrid capture assay, histopathology, or validated clinical diagnostic criteria - Time period: Studies conducted between 1990 and 2023 - Publication type: Full-text peer-reviewed articles, theses, or institutional reports Exclusion criteria were: - Studies reporting only cervical cancer incidence or HPV-associated disease without baseline prevalence data - Studies lacking age-specific prevalence information or using incompatible age categorizations - Conference abstracts without full-text availability or sufficient methodological detail - Duplicate publications of the same study population - Studies with inadequate methodological description preventing quality assessment - Non-human or in-vitro studies 2.4 Study selection and data collection Two independent reviewers (MM, AM) screened all titles and abstracts identified in the database searches. Studies flagged as potentially eligible by either reviewer proceeded to full-text evaluation. Full-text articles were independently assessed by both reviewers using a standardized eligibility form. Disagreements regarding inclusion were resolved through discussion and, if necessary, arbitration by a third reviewer (SD). Data extraction was performed independently by two reviewers using a standardized, pilot-tested data extraction form. The following information was systematically extracted from each included study: - Study characteristics: first author, publication year, study location within Honduras, study design - Population characteristics: sample size overall and by age group, recruitment setting (clinic-based, community-based, mixed) - Diagnostic methods: specific laboratory technique employed, HPV types detected (if specified) - Outcome data: number of HPV-positive cases overall and stratified by age group (15-24, 25-34, 35-44, 45-54, 55+ years) - Quality indicators: sampling methodology, response rates, follow-up duration (if applicable) Discrepancies in extracted data were resolved by consensus between extractors. When information was unclear or missing, we attempted to contact study authors. If authors could not be reached or data could not be clarified, we used conservative assumptions documented in our analysis. 2.5 Population-based prevalence adjustment To enable comparison of prevalence rates across studies conducted in different years and settings, we calculated population-adjusted prevalence rates per 10,000 inhabitants. Age-specific population denominators were obtained from the National Statistics Institute of Honduras (INE) Population and Housing Census. 12 For each study, we selected census data from the year closest to the study midpoint. This adjustment approach has inherent limitations; these should be considered when interpreting population-adjusted prevalence estimates: - Census data represent national-level population estimates and may not reflect the specific demographic composition of study catchment areas (e.g., urban Tegucigalpa vs. rural Danlí) - Linear interpolation between census years (1988, 2001, 2013) may not accurately capture population changes during intervening periods - The assumption of uniform age-sex structure across geographic regions may introduce bias in studies from regions with atypical demographics - Clinic-based studies may oversample high-risk populations, making direct comparison with population-based estimates problematic 2.6 Quality assessment We assessed study quality using the following criteria adapted for prevalence studies: 1. Sampling methodology : Was the sample representative of the target population? Were consecutive patients enrolled or was selection randomized? 2. Sample size adequacy : Was sample size calculation reported? Did the sample provide adequate precision for age-stratified estimates? 3. Diagnostic test validity : Were validated, reproducible laboratory methods employed? Was quality control described? 4. Case definition clarity : Were HPV-positive cases clearly defined with explicit diagnostic criteria? 5. Response rate and attrition : Were participation rates reported? Was attrition accounted for? 6. Statistical analysis appropriateness : Were confidence intervals reported? Were appropriate denominators used? Due to the limited number of studies meeting basic inclusion criteria (n=4), we included all studies that met minimal methodological standards rather than excluding studies based on quality scores. However, we noted quality concerns and incorporated them into our interpretation of results and assessment of evidence certainly. Several sources of bias were identified and addressed: - Selection bias : Clinic-based recruitment in three of four studies may oversample symptomatic or high-risk individuals. We acknowledged this limitation and interpreted prevalence estimates as potentially representing upper bounds. - Publication bias : With only four identified studies spanning 25 years, publication bias favoring positive or significant findings cannot be ruled out. Studies with null findings or unpublished institutional reports may exist but were not accessible through our search strategy. - Detection bias : Variability in diagnostic methods (clinical diagnosis vs. PCR-based detection) and differences in laboratory quality may introduce differential measurement error across studies and time periods. - Temporal confounding : Studies conducted across different time periods may capture secular trends (e.g., introduction of vaccination programs, changes in screening practices, evolution of diagnostic technologies) in addition to true prevalence changes. 2.7 Statistical analysis Meta-analysis of proportions was conducted using MedCalc statistical software v19.7.1 (64-bit). 13 We calculated pooled prevalence estimates with 95% confidence intervals (CI) using random-effects models (DerSimonian-Laird method), anticipating heterogeneity across studies. Random-effects models were chosen a priori given expected variability in study populations, settings, diagnostic methods, and time periods. Statistical heterogeneity was quantified using the I 2 statistic and Cochran’s Q test. I 2 values of 25%, 50%, and 75% were interpreted as representing low, moderate, and high heterogeneity, respectively. Forest plots were generated to visually present individual study estimates with confidence intervals and the pooled effect estimate. Time series analysis and forecasting were performed using Python programming language v3.10.3 with the following libraries: NumPy v1.18 (numerical computing), Pandas v2.1 (data manipulation), SciPy v1.10.1 (scientific computing), Matplotlib v3.7 (visualization), and Seaborn v0.12.2 (statistical graphics). 14 , 15 The Holt-Winters exponential smoothing method 16 was employed for prevalence forecasting from 2025 to 2035. This method decomposes time series into three components: level (average value), trend (directional change), and seasonality (periodic fluctuation). Given our data structure, comprising only four temporal observations at irregular intervals without cyclical patterns; we applied the non-seasonal variant focusing exclusively on level and trend components. The method employs exponential smoothing with two smoothing parameters: α (level smoothing, range 0-1) and β (trend smoothing, range 0-1). These parameters were optimized automatically using least-squares minimization to fit historical data. Forecasts were generated for each age group independently. Critical limitations of the forecasting approach: 1. Sample size insufficiency: Our models were trained on only four temporal observations (1999, 2009, 2017, 2023), far below the recommended minimum of 10-20 observations for reliable time series modeling. This severely constrains forecast reliability and increases parameter uncertainty. 2. Irregular time intervals : Observations are not evenly spaced (gaps of 8, 8, and 6 years), violating the assumption of regular periodicity and potentially introducing artifacts in trend estimation. 3. Non-stationarity : Visual inspection and statistical tests suggest non-stationary behavior (changing variance, non-linear trends) in several age groups, violating Holt-Winters assumptions. 4. Structural breaks : Introduction of HPV vaccination (2006), health system disruptions (2009 political crisis, 2014 failed reform), and the COVID-19 pandemic (2020-2021) represent unmodeled structural changes that may have fundamentally altered transmission dynamics. 5. Model misspecification : The appearance of negative prevalence forecasts for older age groups indicates inappropriate linear extrapolation for data approaching lower bounds. Biologically, prevalence cannot fall below zero; these estimates represent model artifacts rather than plausible predictions. 6. Extrapolation uncertainty : Forecasts extending 10+ years beyond the last observation (2023 to 2035) venture far beyond the data support, exponentially increasing uncertainty. Near-term forecasts (2025-2028) are more reliable than long-term projections (2030-2035). Given these limitations, forecasts should be interpreted as illustrative of general directional trends (increasing vs. decreasing) rather than precise point estimates. Confidence intervals for forecasts were not calculated due to insufficient data points, further limiting interpretability. We recommend viewing projections as hypothesis-generating rather than definitive predictions suitable for policy planning. Forecast accuracy was evaluated using root mean square error (RMSE) and mean absolute error (MAE), 17 , 18 with following formulas: (1) RMSE = [ ∑ ( observed − predicted ) 2 n ] (2) MAE = ∑ | observed − predicted | n Lower RMSE and MAE values indicate superior model fit. RMSE penalizes larger errors more heavily, while MAE provides an average absolute deviation metric. Both metrics are reported in prevalence percentage units for interpretability. All analyses were conducted in a Microsoft Windows 10 (64-bit) environment. 13 – 15 Statistical significance was set at α = 0.05 for all tests. Analysis scripts are available upon reasonable request to promote reproducibility. 2.8 Data availability and reproductibility All data underlying the results are available as part of the article and no additional source data is required. The four primary studies included in the meta-analysis are publicly available through peer-reviewed publications: Ferrera et al. 1999, 19 Tabora et al. 2009, 20 Avilez et al. 2017, 21 and Montoya 2023. 1 Population denominator data were obtained from publicly accessible census records maintained by the National Statistics Institute of Honduras (INE). 12 Age-specific population estimates used for prevalence rate calculations are provided in supplementary materials to facilitate replication. Python analysis scripts, data extraction forms, and complete search documentation are available from the corresponding author upon reasonable request. The PRISMA 2020 checklist with item-by-item reporting locations has been deposited in Zenodo with DOI: 10.5281/zenodo.17429814 under a CC0 1.0 Universal (CC0 1.0) Public Domain Dedication license. 7 3. Results The database search identified 3,760 records. After removing duplicates and screening titles and abstracts, 15 full-text articles were assessed for eligibility. Four studies met all inclusion criteria and were included in the meta-analysis. 5 , 19 – 21 The main reason for exclusion was lack of age-stratified prevalence data (n=11 studies), see Figure 1 for PRISMA flow. Figure 1. Flow diagram showing the identification, screening, eligibility assessment, and inclusion of studies. From 3,760 initial records, four studies met all inclusion criteria for meta-analysis. 1 , 19 – 21 Four studies spanning from 1999 to 2023 were included (see Table 1 ). The overall pooled HPV prevalence across all studies and age groups was 42% (95% CI: 36.1-63.9%), with substantial heterogeneity among studies (I 2 = 96.8%, p < 0.001). Individual study prevalence ranged from 14.8% (Avilez 2017) to 52.8%. 19 , 20 All studies used same age groups (15-24, 25-34, 35-44, 45-54, 55+). Table 1. Characteristics of studies included in meta-analysis. Study Year Location Sample Size HPV+ Cases Diagnostic Method Ferrera et al. 19 1999 Tegucigalpa 603 319 PCR Tabora et al. 20 2009 Tegucigalpa 540 278 PCR/Sequencing Avilez et al. 21 2017 Tegucigalpa 2,148 317 Clinical/PCR Montoya 1 2023 Danlí 100 50 Clinical The overall pooled HPV prevalence across all studies and age groups was 42% (95% CI: 36.1-63.9%), with substantial heterogeneity among studies (I 2 = 96.8%, p < 0.001). Individual study prevalence ranged from 14.8% 21 to 52.8%. 19 , 20 See Table 2 for more details. Table 2. Meta-analysis summary statistics. Study Year Prevalence (%) Standard Error 95% CI Lower 95% CI Upper Ferrera et al. 19 1999 52.8 2.39 47.6 57.0 Tabora et al. 20 2009 51.4 2.11 47.3 55.6 Avilez et al. 21 2017 14.8 0.75 13.3 16.2 Montoya 1 2023 50.0 7.07 36.1 63.9 Pooled estimate 42.0 21.8 62.2 The forest plot ( Figure 2 ) demonstrates considerable between-study variability, with Avilez 2017 showing notably lower prevalence than other studies. The wide confidence interval for Montoya 1 reflects the small sample size (n=100). Figure 2. Forest plot of HPV prevalence meta-analysis. Random-effects meta-analysis showing individual study prevalence estimates (blue diamonds) with 95% confidence intervals (horizontal lines). Pooled estimate (green diamond) is 42% (95% CI: 21.8-62.2%). Substantial heterogeneity observed (I 2 =96.8%). The red dashed vertical line indicates pooled prevalence; shaded red area represents 95% CI of pooled estimate. Study weights proportional to precision, with Avilez 2017 (n=2,148) contributing highest weight (35.8%) despite showing lowest prevalence (14.8%). Age-stratified analyses revealed divergent trajectories across cohorts (see Table 3 ). Among women aged 15–24 years, prevalence was low in early studies (1.26–2.00%), fell to 0% in 2017, and then rose sharply to 10.65% by 2023, indicating a recent resurgence. In the 25–34 group, prevalence fluctuated, peaking at 15.69% in 2017 before declining to 6.54% in 2023. Older groups showed sustained declines: among women 35–44 years, prevalence decreased from 11.88% (1999) to 6.45% (2023), and among those 45–54 years it fell from 13.82% to 3.30% over the same period. Prevalence in women aged ≥55 years remained consistently low, reaching 0% in 2023. Collectively, these patterns suggest a shifting age distribution, with increasing burden in younger women alongside continued improvements in older cohorts. Figure 3 illustrates these temporal trends, showing divergent patterns between younger (<35 years) and older (≥35 years) age groups. Table 3. Age-specific HPV prevalence rates (per 10,000 population). Study Year 15-24 25-34 35-44 45-54 55+ Ferrera et al. 19 1999 1.26 6.21 11.88 13.82 5.36 Tabora et al. 20 2009 2.00 7.39 10.44 9.51 1.39 Avilez et al. 21 2017 0.00 15.69 8.88 6.31 2.21 Montoya 1 2023 10.65 6.54 6.45 3.30 0.00 Figure 3. Age-specific HPV prevalence trends in Honduras (1999-2023). Bar chart showing prevalence rates per 10,000 population across five age groups and four study years. Rising trends evident in younger age groups (15-24, 25-34), with particularly dramatic increase in 15-24 group from 0% (2017) to 10.65% (2023). Declining trends observed in older age groups (35-44, 45-54, 55+). Employing Holt-Winters smoothing, we produced age-specific forecasts extending to 2035 ( Figure 4 ). The prevalence among women aged 15–24 years is anticipated to escalate significantly from 10.02% in 2025 to 33.57% in 2035, whilst the 25–34 age group exhibits a more gradual growth (11.28% to 19.64%). Conversely, forecasts for the 35–44 age group decrease from 4.95% in 2025 to nil by 2035, while estimates for the 45–54 and ≥55 age groups persist in their drop, with certain figures dipping below zero. The negative estimates are biologically implausible and represent an artifact of linear trend extrapolation with restricted temporal resolution, suggesting that Holt–Winters is inadequately applicable to this dataset. The prevalence in elderly demographics is likely to stabilize around zero, making bounded alternatives, such as exponential decay or logistic models more suitable for forecasting. The model demonstrated acceptable performance for age groups 35-54 years (RMSE 3.0), reflecting greater variability in these populations and limitations of forecasting with only four observations. See Table 4 . Figure 4. Holt-Winters projections with uncertainty bands (2025-2035). Age-specific prevalence projections from 2025-2035 using Holt-Winters exponential smoothing. Solid lines represent historical observations (1999-2023); dashed lines show forecasts. Younger age groups (15-24, 25-34) show projected increases; older age groups (35-44, 45-54, 55+) show projected stabilization near zero. Error metrics indicate poor model fit for younger groups (RMSE >3.0) and good fit for 35-44 age group (RMSE=0.26). Note: Projections constrained to 0-40% range to maintain biological plausibility. Table 4. Holt-Winters Model Error Metrics. Age group RMSE MAE Interpretation 15-24 3.02 2.48 Poor fit; high uncertainty 25-34 3.77 3.13 Poor fit; high uncertainty 35-44 0.26 0.25 Good fit; low uncertainty 45-54 0.34 0.33 Good fit; low uncertainty 55+ 0.98 0.81 Moderate fit 4. Discussion This systematic review and meta-analysis main finding reveal a significant HPV prevalence among Honduran women (pooled estimate: 42%), characterized by considerable between-study heterogeneity and varying age-specific temporal trends. The prevalence among women under 35 years has either increased or varied over time, while among women aged 35 years and older, there is a steady decline. In summary, these patterns are in line with the idea that public health interventions work better for some birth cohorts than others, and that sexual behavior, screening participation, and access to healthcare may change from one generation to the next. 4.1 Interpretation of age-specific trends Among younger women (15–34 years), the sharp rise, particularly in those aged 15–24 years, from 0% in 2017 to 10.65% in 2023; it is concerning and may reflect declining vaccination coverage following health-system disruptions; earlier sexual debut in more recent cohorts; reduced awareness of STI prevention due to waning public health campaigns; expanded access to diagnostic services that is detecting previously missed infections; and random variability related to small sample sizes in the most recent study. 5 In contrast, the sustained decline among women ≥35 years likely reflects the cumulative impact of STI prevention campaigns implemented during 1980–2000; cohort-level benefits of HPV vaccination (with today’s 35–44-year-olds having been adolescents or young adults at program initiation); age-related changes in sexual behavior and partner numbers; natural immune clearance of infections acquired earlier in life; and cohort effects arising from differential exposure to risk factors. 4.2 Comparison with regional and global Data Our findings correspond with regional trends indicating increased prevalence in the age groups under 34 and over 55 years, and decreased rates in intermediate ages, when juxtaposed with HPV Information Centre data for Central America. 22 , 23 Nonetheless, direct comparison is constrained by variations in diagnostic methodologies, study cohorts, and HPV type-specific detection. When compared to official SESAL data ( Figure 5 ), there is some agreement, especially for the 25–34 age group, but not for other age groups. SESAL projections indicate a greater prevalence in the 35-54 age demographic compared to our meta-analysis predictions, potentially highlighting discrepancies between clinical reporting systems (SESAL) and research study samples. Figure 5. Comparison of meta-analysis versus SESAL administrative data projections (2025-2035), Comparison of age-specific projections from research-based meta-analysis (solid lines) versus Honduras Ministry of Health (SESAL) administrative surveillance data (dashed lines). Agreement observed for 25-34 age group projections. Divergence is evident for other age groups, particularly 15-24 (meta-analysis shows steep rise, SESAL shows stability) and 35-54 (meta-analysis predicts decline, SESAL predicts persistence). Discrepancies likely reflect differences in data sources, populations, and detection methods. 4.3 Methodological limitations and forecast reliability The main methodological problem is that there aren’t enough time observations, only four (1999, 2009, 2017, and 2023) for time-series forecasting. Standard practice says that there should be at least 10–20 observations for stable trend estimation. With such limited data, it is impossible to tell the difference between short-term stochastic variation and long-term trends. Parameter estimates are very uncertain, projections beyond 2–3 years become less reliable, and the model can’t handle non-linear dynamics or structural breaks. The appearance of negative prevalence forecasts for individuals aged 35 years and older further illustrates model misspecification; prevalence cannot decrease below zero, and these figures represent artifacts of linear extrapolation approaching a low asymptote. This pattern shows that we need bounded models that set natural limits (0–100%), that Holt-Winters is not a good fit for behavior close to zero, and that long-horizon projections (2030–2035) are hard to understand. In addition to forecasting constraints, significant heterogeneity between studies (I 2 = 96.8%) restricts the generalizability of pooled estimates. This heterogeneity is caused by differences in diagnostic methods (clinical vs. PCR), study populations (clinic-based vs. community-based), geographic settings (e.g., Tegucigalpa vs. Danlí), changes in HPV epidemiology and testing practices over time, and sample sizes (100 to 2,148 participants). There is also a possibility of publication and selection bias due to the limited number of published studies and the tendency to favor reporting positive results or specific age groups, while some clinic-based studies remain in institutional reports. Lastly, population adjustments based on national census data assume that the population is evenly spread out, which may not be true for the populations at risk in the study areas. The forecasting model produced biologically implausible negative prevalence estimates for older age groups (35+) in later projection years (2030-2035). These negative values represent artifacts of linear trend extrapolation when data approach lower bounds and indicate model misspecification rather than true predictions. In practice, prevalence in these age groups is expected to stabilize near zero rather than become negative. This artifact underscores the limitations of applying Holt-Winters exponential smoothing to sparse temporal data with only four observations and highlights the need for bounded forecasting approaches (e.g., logistic models, exponential decay) when modeling processes with natural constraints. 4.4 Implications for Honduran Public Health Policy Even with methodological flaws, these results have clear implications for policy. The sharp rise in HPV cases among women aged 15 to 24 years necessitates an immediate escalation of HPV vaccination efforts, preferably before the initiation of sexual activity, coupled with thorough school- and community-based sexual health education that highlights prevention and the advantages of vaccination. To enhance decision-making, a systematic annual surveillance system employing standardized age strata is essential for facilitating comprehensive trend analysis and forecasting. The ongoing declines seen in older women show that past prevention efforts have worked, which means that more money should be spent on broad STI control programs. Finally, it is important to strengthen the resilience of the health system by fixing the weaknesses that were shown during times of political instability (for example, the 2009 constitutional crisis ( curfew ) 24 and the failed 2014 health reform 25 ) to keep public health gains. 4.5 Sociopolitical context Honduras has experienced periods of political and economic instability with direct and persistent effects on the delivery of health services. The constitutional crisis of 2009 messed up public health programs and messed up supply chains, vaccination schedules, and the normal running of health facilities. 24 In 2014, efforts to reform health care didn’t fix the problems with financing, governance, and stewardship that were built into the system. 25 These shocks probably led to inconsistent vaccination coverage, less screening and treatment for STIs, a smaller budget for prevention campaigns, and a loss of skilled workers due to migration and staff changes. At the operational level, higher opportunity costs for users, restrictions on mobility and security, and a more informal labor force may have reduced the demand for preventive services, while staff turnover and institutional fragmentation compromised the continuity of interventions. These contextual conditions provide a reasonable basis for elucidating the observed epidemiological trends: increases or variations in prevalence among young women may signify accumulated deficiencies in primary and secondary prevention, generational shifts in sexual behavior, and inequitable access to diagnosis, alongside methodological discrepancies across studies. The decline in women aged ≥35 years may indicate delayed effects of prior interventions and immunological clearance, as well as potential biases stemming from the selection of the served population or alterations in test sensitivity. The COVID-19 pandemic and other macroeconomic shocks, along with the fact that systems are different, mean that we should be careful when trying to figure out trends. 26 This shows how important it is to have standardized periodic surveillance by age group, better information systems, and evaluations of implementation. To keep up the progress and close the gaps in HPV prevention and control, it’s important to come up with strong strategies that include protected financing, strong supply chains, keeping staff, and working together across sectors. 27 4.6 Recommendations for future research Research priorities should encompass prospective cohorts with age-stratified follow-up to elucidate the natural history and persistence of HPV infection; type-specific genotyping analyses that differentiate oncogenic from non-oncogenic variants and facilitate the estimation of vaccination impact; and a standardized surveillance system featuring annual surveys, uniform sampling frames and laboratory methods, and consistent age bands to enhance the comparability and validity of trends. 28 , 29 Simultaneously, mixed-methods studies investigating barriers to vaccination and healthcare access would inform the optimization of implementation, while comprehensive economic evaluations contrasting expanded vaccination with diverse screening strategies would facilitate effective resource allocation. Finally, it is important to have multicenter collaborations at the Central American level to understand how diseases spread in the region and how they vary from place to place. 5. Conclusions This meta-analysis shows that a lot of Honduran women have HPV, and that the number of cases is rising among younger age groups, which is worrying. Although older women exhibit signs of effective intervention outcomes, the resurgence among adolescents and young adults necessitates an immediate public health response. Time series forecasting with limited temporal observations yields directional insights but should not be excessively interpreted for long-term predictions. The negative prevalence forecasts underscore intrinsic constraints associated with the application of conventional forecasting techniques to sparse epidemiological data. Strengthening HPV vaccination initiatives, improving sexual health education, and developing comprehensive epidemiological surveillance systems are essential priorities. Future research necessitates more frequent temporal assessments and expanded sample sizes to ensure dependable trend analysis and predictions that inform evidence-based policy decisions. Generative AI and tools We used WORDVICE.AI online service with the only purpose of improving semantics and other language concerns. Data availability All data underlying the results are available as part of the article and no additional source data is required. The four primary studies included in the meta-analysis are publicly available through their respective peer-reviewed publications: Ferrera et al. 1999, 19 Tabora et al. 2009, 20 Avilez et al. 2017, 21 and Montoya 2023. 1 Population denominator data were obtained from publicly accessible census records maintained by the National Statistics Institute of Honduras (INE). 12 The PRISMA 2020 checklist for this systematic review and meta-analysis has been deposited in Zenodo with the title “PRISMA 2020 Checklist: Meta-analysis and Time Series Projection of HPV Prevalence Among Women in Honduras (1990-2023)”, DOI: 10.5281/zenodo.17429814 , under a CC0 1.0 Universal (CC0 1.0) Public Domain Dedication license. 30 Acknowledgments This research was supported by the Institute for Research in Medical Sciences and Right to Health (ICIMEDES), Faculty of Medical Sciences (FCM), and Directorate of Scientific, Humanistic, and Technological Research (DICIHT) of the National Autonomous University of Honduras (UNAH). 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Publisher Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 29 Oct 2025 ADD YOUR COMMENT Comment Author details Author details 1 National Autonomous University of Honduras Faculty of Medical Sciences, Tegucigalpa, Francisco Morazan, 11101, Honduras 2 Hospital General San Felipe, Tegucigalpa, Francisco Morazan, 11101, Honduras 3 Center for Biomedical Imaging Diagnostics Research and Rehabilitation, National Autonomous University of Honduras, Tegucigalpa, Francisco Morazan, 11101, Honduras 4 Universidad Catolica de Honduras Facultad de Ciencias de la Salud, Tegucigalpa, Francisco Morazan, Honduras Salvador Diaz Roles: Conceptualization, Formal Analysis, Methodology Marissa Montoya Roles: Data Curation, Supervision Arnoldo Zelaya Roles: Investigation, Supervision, Writing – Review & Editing Jorge Valle Roles: Formal Analysis, Methodology, Validation Carlos Agudelo-Santos Roles: Writing – Review & Editing Marcio Madrid Roles: Formal Analysis Melania Madrid Roles: Data Curation, Resources, Writing – Review & Editing Alicia Diaz Roles: Data Curation, Writing – Review & Editing Yolly Molina Roles: Conceptualization, Investigation Isaac Zablah Roles: Data Curation, Resources, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (1) version 1 Published: 29 Oct 2025, 14:1179 https://doi.org/10.12688/f1000research.172083.1 Copyright © 2025 Diaz S et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Diaz S, Montoya M, Zelaya A et al. Meta-analysis and Time Series Projection of Human Papillomavirus Prevalence Among Women in Honduras (1990-2023) [version 1; peer review: awaiting peer review] . 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Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 29 Oct 2025 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status AWAITING PEER REVIEW Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. 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