Comparative Evaluation of IgG Antibody Response to HPV Vaccination among Urban and Rural Populations in Ebonyi State, Nigeria

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Immunization, especially the production of IgG antibodies is an essential pointer of protection that has been induced by the vaccine. The research study measured and compared the levels of IgG antibody and the immune index (ABS and INDEX) after the HPV vaccination among the urban and rural communities in Ebonyi State, Nigeria. There were 278 participants who received the vaccination that had been recruited; 139 in Abakaliki (urban) and 139 in Ezza North (rural). Methods : In order to determine the levels of serum IgG, Enzyme-Linked Immunosorbent Assay (ELISA) was used and the test results were analyzed through independent t-tests, Chi-square, and logistic regression. Results : The findings showed that the mean levels of IgG were also significantly more in Abakaliki (ABS 0.598 ± 0.340; INDEX 3.62 ± 2.08) than in Ezza North (ABS 0.072 ± 0.096; INDEX 0.43 ± 0.58). The difference in the response of antibodies was significantly different (t = 17.53, p < 0.00001). The percentage of vaccination and IgG positivity was also larger in Abakaliki (86.3%) compared to Ezza North (69.1%). The logistic regression analysis revealed that the participants in urban areas were two and half times more likely to develop a positive IgG response in comparison to the participants in the rural area (p = 0.032)(p<0.05). Conclusion : The results indicate that there is a strong urban-rural gap in immunity developed due to HPV vaccination, and that vaccine manipulation, access to healthcare, and socio-environmental conditions affect the immune measures. Strengthening cold-chain infrastructure, enhance outreach vaccination in rural areas, and increase awareness of the population to have equal vaccine efficacy can play a role in the reduction of HPV-related diseases in Nigeria. Immunology Human Papillomavirus IgG Antibody Vaccine Efficacy Urban–Rural Disparity Ebonyi State Figures Figure 1 Introduction Human Papillomavirus (HPV) is among the commonest sexually transmitted disease in the world and a leading etiological agent of cervical cancer [ 1 ] which is a major public health concern, especially in underdeveloped nations with low and middle incomes [ 2 ]. According to the estimates by the World Health Organization (WHO), persistent HPV infection, and in particular, the high-risk genotypes of HPV 16 and 18, are the cause of cervical cancer in more than 95 percent of cases [ 3 ]. HPV vaccination has shown to be a beneficial preventative measure against HPV, which causes strong humoral responses and long protection against HPV infection and malignancy [ 4 ]. HPV vaccine protection is immunologically based on the production of the neutralizing antibodies, mainly Immunoglobulin G (IgG), preventing the viral entry and replication in the host epithelial cells. The level of serum IgG is consequently one of the most significant biomarkers to determine the power and duration of immune response after vaccination [ 5 ]. Some of the studies have shown that high IgG levels are associated with long-term protection and low exposure to HPV-associated diseases [ 6 ]. Nevertheless, the new data shows that socioeconomic, environmental, and healthcare delivery disparities have the potential to affect vaccine immunogenicity resulting in uneven antibody responses across various populations [ 7 ]. The coverage of HPV vaccination is not optimal in Nigeria, and the disparity between Nigerian cities and rural populations is very high [ 8 ]. Urban residents have more advantages in the form of improved healthcare infrastructure, the availability of vaccines, and cold-chain, and rural communities have issues with poor vaccine storage, low awareness, and poor healthcare-seeking behavior [ 9 ]. These disparities can be converted into quantifiable variations in subsequent vaccination outcomes of immunization, and finally influence the effectiveness of HPV immunization strategies, as a whole. The awareness of such disparities is important to maximize the benefits of vaccination methods and attain fair cervical cancer prevention activities [ 10 ]. Although the introduction of HPV vaccination campaigns in Nigeria has been carried out, there are limited studies that have looked at the immunological response of this vaccine in various population settings. Past studies have devoted a lot of attention to vaccine uptake and awareness and very few studies have dealt with comparative antibody response in both urban and rural population. It is thus necessary to measure the immunology of the HPV vaccination in these different settings to determine any possible gaps in the delivery and efficacy of the vaccine. The purpose of this study was to compare and contrast IgG antibody and immune indexes (ABS and INDEX) between vaccinated people living in urban (Abakaliki) and rural (Ezza North) communities of the city of Ebonyi, Nigeria. The study can inform the immunological efficacy of HPV vaccination in various population settings by examining the magnitude of the vaccine-induced IgG responses as well as the factors affecting the magnitude of responses. Method Study Area The research was carried out in the Ebonyi State Ezza North and Abakalik LGA, Nigeria. Ezza North is a largely rural area whose healthcare amenities are low, with low vaccine coverage, and low socioeconomic indicators. The capital of the state, Abakaliki, is urbanized and has a more developed health care infrastructure, a greater level of literacy, and a relatively greater vaccination rate. The target population is those that are aged 926 years old and have previously received at least one dose of the HPV vaccine. This is the age range in the WHO guidelines regarding the HPV vaccination which is aimed at preadolescents, adolescents and young adults. The participants were recruited in the two LGAs in schools, health facilities, and community outreach programs. These are the peculiarities that allow comparing the two LGAs in this study (Fig. 1 ) Research Design The present study was a comparative cross-sectional research design to measure the IgG immune response of HPV-vaccinated people in Ezza North and Abakaliki LGAs. Cross-sectional designs are most suitable in assessing the immune response and distinguishing between the populations of different populations at a given time [ 11 ]. The criteria of inclusion are that the individuals must be aged between 9 and 26 years old, be residents of Ezza North or Abakaliki LGA at least one year long and be willing to give an informed consent or assent (with parental consent in cases of minors). The exclusion criteria are those people who have not received all vaccinations or have no idea of their vaccination status, pregnant people (hormonal changes can affect the level of IgG), as well as those who have known immunosuppressive conditions or immunosuppressive treatment. 3.4 Sample Size Determination The sample size was determined using a standard formula for cross-sectional studies: studies. $$\:n=\frac{{Z}^{2}\:P(1-P)}{{d}^{2}}$$ Where: n = sample size Z = standard normal deviation at 95% confidence level (1.96) p = estimated HPV prevalence in similar populations (based on previous studies or literature, often at 10%) e = margin of error (typically set at 5%): Therefore: $$\:{n}_{0}=({1.96)}^{2}\times\:\frac{0.10\left(1-0.10\right)}{{\left(0.05\right)}^{2}}$$ $$\:{n}_{0}=\frac{3.8416\times\:0.09}{0.0025}=\frac{0.3457}{0.0025}=139$$ Thus, the computed sample size was 139 participants for one study location Sampling Method and Collection of Samples . Multi-stage sampling was used where the selection of wards in each LGA was done randomly in order to provide geographical coverage. In the chosen wards, schools, health, and communities, the selection was purposively convenient with regard to the possibility of having participants who qualify under the inclusion criteria. 5mL of venous blood was collected using sterile syringes and vacutainer tubes and a certified phlebotomist recruited the participants and collected the blood [ 12 ]. The venipuncture was done in accordance with WHO-suggested guidelines regarding the blood collection practices to prevent any complications and discharge the samples intact [ 13 ]. The minimization of the risk of contamination was achieved by the use of standard aseptic procedures such as gloves, alcohol swabs, and disposable needles [ 14 ]. All the gathered blood specimen was marked with special identifiers so as to track it and send it to the laboratory in coolers with ice packs. Separated serum was frozen at -20 o C until analysis [ 15 ]. Observation of participants was conducted in the short term following the collection of samples in case of adverse reactions. Laboratory Analysis The individual sample serums were tested on IgG concentrations using Enzyme-Linked Immunosorbent Assay (ELISA) kits of HPV antibodies. ELISA is a gold standard method of detecting antibodies because it is highly sensitive and specific. The assay had been conducted in two doses in order to guarantee reliability and consistency of the results. Lab procedures were done as per the instructions given by the manufacturer in ELISA kit. These involve preparation of reagents, serial dilutions of samples and optical densities on ELISA plate reader. The findings were then related to the standard curve to measure the levels of IgG. The standard operating procedures were also followed by all the staff in the laboratories to ensure accuracy and reproducibility [ 16 ]. Data Analysis The comparison of the means of IgG between the Ezza North and Abakaliki LGAs was done using independent samples t-tests. T-test was used to determine the difference in IgG levels among sub-groups through R coding statistical analysis software. Statistical analysis (Independent t-test, Chi-square, logistic regression) Results The IgG levels in HPV-vaccinated individuals in Ezza North LGA and Abakaliki LGA Table 1 indicates that there is a pronounced difference in IgG antibody levels and the indices of the immune response in the population of the Abakaliki LGA and Ezza North LGA with respect to the vaccination status. The mean IgG level (ABS) in Abakaliki was 0.598 and standard deviation = 0.340. Its median was 0.574, range of interquartile is 0.287 to 0.922, and values were in the range of 0.056 to 1.185. Conversely, the standard deviation of 0.096 gave the mean ABS of 0.072 in Ezza North. The median was 0.057 with the interquartile range of 0.020 to 0.091 with the values of 0.001 to 0.946. This implies that the mean concentration of IgG in Abakaliki was approximately eight times greater when compared to Ezza North and most of the rural responses were concentrated towards the lower end of the scale. On the same note, the index of immune response (INDEX) in Abakaliki was a lot higher than in Ezza North. The standard deviation of 2.08 and the mean of 3.62 gave the mean of 3.58 and the range of the interquartile of 1.82 to 5.16 as the mean INDEX in Abakaliki. The values were ranging between 0.36 and 7.94. In Ezza North, the mean INDEX was 0.43 and standard deviation was 0.58, median was 0.35, interquartile of 0.12–0.55 and the range was 0.006 to 5.73. Once again, the mean response in Abakaliki was greater than eight times bigger than the one in Ezza North (Table 1 a) Table 1 a : IgG Levels (ABS) and INDEX in-vaccinated individuals in Ezza North LGA and Abakaliki LGA. Group N ABS Mean ± SD ABS Median (IQR) ABS Range INDEX Mean ± SD INDEX Median (IQR) INDEX Range Abakaliki 139 0.598 ± 0.340 0.574 (0.287–0.922) 0.056–1.185 3.62 ± 2.08 3.58 (1.82–5.16) 0.36–7.94 Ezza North 139 0.072 ± 0.096 0.057 (0.020–0.091) 0.001–0.946 0.43 ± 0.58 0.35 (0.12–0.55) 0.006–5.73 Percentage of Neg/POS of IgG Levels (ABS) and INDEX in-vaccinated individuals in Ezza North and Abakaliki LGA The findings indicate that there are drastic differences in the level of IgG and response rates of the two study groups. The IgG concentration (ABS) mean of Abakaliki was 0.598 as 0.340 with a median of 0.574 (IQR: 0.287–0.922). There was also a high index of immune response with the average of immune response being 3.62 + 2.08 but the median of this index was 3.58 (IQR: 1.82 5.16). On the IgG status, 86.3% (n = 120) of the participants were positive, 8.6% (n = 12) negative and only 5.0% (n = 7) were equivocal. Comparatively, the members of Ezza North responded with considerably reduced immunity. They had a mean ABS of 0.072, SD = 0.096 with a median of 0.057 (IQR: 0.020–0.091), and a mean INDEX of 0.43, SD = 0.58 with a median of 0.35 (IQR: 0.12–0.55). Distribution of the IgG status demonstrated that 69.1% (n = 96) were positive, 27.3% (n = 38) negative and 3.6% (n = 5) equivocal. (Table 1 b) Table 1 b : Percentage of Neg/POS of IgG Levels (ABS) and INDEX in-vaccinated individuals in Ezza North and Abakaliki LGA Group N ABS Mean ± SD ABS Median (IQR) INDEX Mean ± SD INDEX Median (IQR) EQ (n, %) NEG (n, %) POS (n, %) Abakaliki 139 0.598 ± 0.340 0.574 (0.287–0.922) 3.62 ± 2.08 3.58 (1.82–5.16) 7 (5.0%) 12 (8.6%) 120 (86.3%) Ezza North 139 0.072 ± 0.096 0.057 (0.020–0.091) 0.43 ± 0.58 0.35 (0.12–0.55) 5 (3.6%) 38 (27.3%) 96 (69.1%) The independent t-test comparing IgG levels (ABS) between Abakaliki and Ezza North Independent t-test between the IgG levels (ABS) of Abakaliki and Ezza North indicates that the t-statistics is 17.53 with a p-value of less than 0.00001 which is highly significant. This indicated that the level of IgG antibody in vaccinated people of Abakaliki was significantly higher than in Ezza North, which means that the difference in immune responses was statistically significant and not accidental (Table 2 ). Table 2 The independent t-test comparing IgG levels (ABS) between Abakaliki and Ezza North Comparison t-Statistic p-Value Abakaliki vs. Ezza North (ABS) 17.53 < 0.00001 The summary results of IgG antibody levels and positivity rates and HPV vaccination rates in urban community of Abakaliki and the rural community of Ezza North It also show a great disparity in the level of IgG antibodies and the coverage of HPV vaccination between the rural community of Ezza North and urban community of Abakaliki. Regarding the level of antibody, the participants in Abakaliki had significantly higher levels of ABS, which was 0.598 +/- 0.340 mean of IgG and ABS of 0.072 +/- 0.096 in Ezza North. This difference was also observed in the median values, as Abakaliki had the median of 0.574 (IQR 0.2870.922) and Ezza North had the median of 0.057 (IQR 0.0200.091). Equally, the IgG index value was significantly higher in the city of Abakaliki (mean 3.62 ± 2.08; median 3.58) compared to that of Ezza North (mean 0.43 ± 0.58; median 0.35). Categorically in serostatus, 86.3 percent of the persons in Abakaliki were found to be IgG positive, but only 69.1 percent in Ezza North and over three times higher in the rural compared to the urban groups, who were IgG negative (27.3 and 8.6 percent). This was a significant difference as indicated in the independent t-test of the IgG levels (t = 17.53, p < 0.00001). Regarding the uptake in terms of the vaccination coverage, Abakaliki was found to have a higher uptake rate since 120 out of the 139 participants (86.3 percent) in Abakaliki were vaccinated compared to 96 out of the 139 participants (69.1 percent) in Ezza North. This difference was statistically significant using chi -square test (Chi 2 = 10.981, p = 0.00092) (Table 5 ). Table 5 The IgG antibody levels and positivity rates and HPV vaccination rates Group N ABS Mean ± SD ABS Median (IQR) INDEX Mean ± SD INDEX Median (IQR) EQ (n, %) NEG (n, %) POS (n, %) Vaccination Rate (%) Abakaliki (Urban) 139 0.598 ± 0.340 0.574 (0.287–0.922) 3.62 ± 2.08 3.58 (1.82–5.16) 7 (5.0%) 12 (8.6%) 120 (86.3%) 86.3% Ezza North (Rural) 139 0.072 ± 0.096 0.057 (0.020–0.091) 0.43 ± 0.58 0.35 (0.12–0.55) 5 (3.6%) 38 (27.3%) 96 (69.1%) 69.1% Key : ABS: IgG absorbance (antibody concentration), INDEX: Computed immune response index, EQ: Equivocal; NEG: Negative; POS: Positive IgG, t = 17.53, p Rural) , χ² = 10.981, p = 0.00092 → Significant difference in vaccination rate (Urban > Rural) Logistic Regression Coefficients of comparison of factors that affect immune response to HPV vaccine between urban and rural communities of Ebonyi State The findings of the logistic regression analysis that assessed predictors of IgG antibody response after vaccination against HPV are given in Table 10 . There was a significant positive intercept (= 0.7919, p < 0.001), thus, a high probability of the immune response with no or very minimal input to mounting the immune response. ABS variable (3.5790, p = 0.363) and INDEX ( -0.5731, p = 0.363) failed to demonstrate statistically significant relationships with IgG positivity indicating that in this dataset neither of these two variables was a strong predictor. A large effect was observed, however, with group (urban vs rural). Group Binary coefficient was 1.0068 (p = 0.032) with a 95% interval of 0.085 to 1.928. This means that the subjects in urban Abakaliki had a higher tendency of a positive IgG response than the rural Ezza North. Table 10 Logistic Regression Coefficients of comparison of factors that affect immune response to HPV vaccine between urban and rural communities of Ebonyi State Variable Coef. (β) Std. Err. Z p-Value 95% CI [Lower, Upper] Intercept 0.7919 0.190 4.166 0.000 0.419–1.164 ABS 3.5790 3.937 0.909 0.363 -4.137–11.295 INDEX -0.5731 0.630 -0.910 0.363 -1.808–0.661 Group_Binary 1.0068 0.470 2.141 0.032 0.085–1.928 Odds Ratios (from Logistic Regression) of comparison of factors that affect immune response to HPV vaccine between urban and rural communities of Ebonyi State It is the odds ratios based on the logistic regression model and it provides a better understanding of the role of each factors in the development of IgG antibody response following the HPV vaccination. The intercept indicates an odds ratio of 2.21 (p < 0.001) which means that there is a high likelihood of seroconversion at the baseline. The odds ratio of ABS was very high (35.84), however, this was not statistically significant (p = 0.363), which implies that it is not reliable to predict response in this dataset. Equally, INDEX had an odds ratio that was lower than 1 (0.56, p = 0.363), which was not significant, indicating weak predictive ability. On the contrary, the odds ratio of the group variable (urban vs rural) was 2.74 (p = 0.032), which indicated that the participants in Abakaliki (urban) were nearly three times more likely to mount an IgG response than those in Ezza North (rural). This supports previous results of the chi-square tests and descriptive analysis that location along with the social and healthcare factors related to it determines the ultimate outcome of immune response (Table 11 ) decisively. Table 11 Odds Ratios (from Logistic Regression) of comparison of factors that affect immune response to HPV vaccine between urban and rural communities of Ebonyi State Variable Odds Ratio p-Value Intercept 2.21 0.00003 ABS 35.84 0.363 INDEX 0.56 0.363 Group_Binary 2.74 0.032 Discussion The significantly higher average IgG absorbance and the immune index in Abakaliki than in Ezza North (Abakaliki ABS 0.598 + 0.340 vs Ezza North 0.072 + 0.096: t = 17.53, p = 0.00001) is in agreement with the fact that licensed HPV vaccines can produce robust and long-lasting humoral immunity under optimal conditions. Sustained seropositivity and maintenance of antibody levels several years after full vaccination confirmed by long-term follow-up and clinical trial data demonstrate that the vaccine has enough biological potential to induce a long-term IgG response in case storage, handling and dosing regimens are maintained [ 17 ]. Population level syntheses underscore the fact that the coverage and strategy of delivery of programmes on HPV immunization has both a direct and herd effects on HPV immunization. Multi-cohort campaigns and high coverage have been reportedly associated with the highest decrease in HPV infection and pre-cancerous lesions, and patchy or low coverage suppresses individual and population-level benefits [ 18 ]. The fact that Abakaliki (86.3) had higher rates of vaccination and IgG-positivity than Ezza North (69.1) therefore may mean that these gaps may be major contributors to the greater antibody reactions of the urban cohort and may imply that the rural population may not be getting much of the indirect benefits of herd protection in the event that these gaps do not improve [ 19 ]. Operational and logistics issues allow us to offer a plausible proximate explanation of the decreased measured antibody titers in rural environments. The implementation studies and program evaluations in low- and middle-income countries report that the last-mile distribution issues, intermittent power, and cold-chain leakage is an ordinary problem in the resource-constrained regions and may lower the vaccine potency and the observed immunogenicity [ 20 ]. In the context of cold-chain integrity and complete dosing is not achievable, field-measured antibody levels can be weakened despite an effective vaccine because of the importance of fortifying these supply-chain factors has been noted [21]. Both uptake and immunological outcomes are also determined by the sociodemographic and delivery-platform determinants. Recent mixed-methods and survey research in sub-Saharan Africa demonstrates that caregiver knowledge, access to delivery in schools, organization of service and vaccine hesitancy are associated with individuals who are vaccinated and adherence to schedule; all these factors are associated with timing and completion of dosing and subsequent magnitude of the antibody [33,34]. Your logistic regression that urban residence is an indicator of seropositivity (OR 2.74, p = 0.032) is consistent with the regional data that urban populations are more likely to use an organized delivery platform and have better completion rates, which is presumably intended to contribute to the stronger serological responses in the urban cohort [33,34]. New findings of lower dose schedules introduce a twist in the interpretation of the intergroup differences in the antibody levels. Since 2019, there have been several observational and trial reports indicating that single dose or delayed dose regimens can offer strong protection in many settings; however, serotiter is often less following the single dose and the long term durability is still the matter of ongoing study (recent reviews 2019–2023). In addition, suggesting that the disparity between your cohorts in terms of dosing completeness/length of time since vaccination could partly account for lower rural titers, this study underscores the importance of including verified dosing-history and time data in future studies (recent reviews and trial updates). Put collectively, the literature suggests three practical implications to your findings. To begin with, contextual and programmatic deficiencies explain (better) the low rural titers than does an inherent vaccine failure. Second, there is a need to lessen the disparity in the coverage and delivery of HPV in cities and rural areas at both the individual level and to obtain the population-wide reductions in HPV-related illness that elimination models predict. Third, targeting of operational research linking serology with cold chain monitoring and keeping dosages-verified histories of contextual variables, such as nutrition, comorbidity, Lange's timing could better isolate drivers of given interventions such as strengthening cold chains, expanding school-based delivery or catch-up campaigns that could be directed at rural areas (Brisson et al., 2020; WHO, 2021; Gavi, 2020). They also need to recognize limitations of interpretation: recommended studies on measured antibody titers are sensitive to time since last dose and number of doses administered and without absolute and well validated dosing histories and cold-chain records they cannot be unambiguously ascribed to any single cause low rural titers. Combined operational monitoring data and longitudinal serology will be most informative in future work in order to inform programmatic decision-making (Brisson et al., 2020; Otieno et al., 2021). Conclusion The findings of the study show that there exists an urban-rural disparity in HPV vaccine-elicited IgG antibody reaction among vaccinated individuals in the Ebonyi State in Nigeria. The levels of IgG (mean ABS 0.598 0.340) and the levels of the immune index (mean INDEX 3.62 2.08) were significantly higher in the participants of Abakaliki (urban) than the participants of Ezza North (rural) whose mean ABS and INDEX 0.072 0.096 0.43 0.58, respectively. This was very significant as indicated by independent t -test ( t = 17.53, p less than 0.00001) but the logistic regression ( OR = 2.74, p = 0.032) revealed that urban participants were almost three times more apt to mount positive response in IgG in contrast to rural participants. These results suggest that the HPV vaccination is immunologically active but effects are enhanced by environmental, infrastructural and socio-economic determinants of HPV vaccinations that differ between the urban and rural populations. The reasons that could have explained these differences include the ease of access to healthcare, more robust systems of administering vaccines, and improved cold-chain systems in urban locations. On the other hand, the rural environment has been challenged in the aspect of the lack of uniform supply of vaccines, lack of sufficient healthcare centers, lack of effective community health education, and the likelihood of cold-chain interferences. Such discrepancies may influence the efficiency of the HPV immunization programme in Nigeria overall and slack the goal of providing equal cervical cancer prevention. These results draw attention to the fact that it is necessary to address logistical, infrastructural, and behavioral determinants limiting the measures against vaccine coverage and immune response in rural populations. Recommendations Enhancement of the Rural Immunization Infrastructure: The government and the public health organizations are intended to enhance healthcare infrastructure and avail good cold-chain facilities in the rural communities. The storage facilities in which the vaccines are kept have to be checked and assessed regularly in order to make sure that the immunogenicity is not lost as well as the vaccines remain in their potent state. Enhanced Community-Based Outreach: door to door immunization, school based programmes, mobile clinics should be intensified in order to promote the rural vaccination programmes. These efforts will enhance accessibility and more so in the case of adolescent girls who are the central subjects of HPV vaccination. It is necessary to create comprehensive education programmes which will dispel the myths about vaccines against HPV and make people know more about their benefits. The positive attitude towards vaccination needs to be promoted by the involvement of social leaders, educators, and churches. Policy and Governmental Pledge: The Ministry of Health should pay attention to the equal access to vaccines and invest in the under-serviced places. It will be sustainable by introducing the use of HPV vaccination to the existing primary healthcare services and National Immunization Programme. Research and Monitoring: The problems concerning the immune response such as nutritional state, intervals of administration, and management of vaccines in rural settings require to be researched. Continuous serological monitoring will help in assessing the efficacy of the vaccine, and providing a policy adjustment. Declarations Authors contribution All the authors contributed to this research work, starting from the beginning of the research to the stage of developing the manuscripts and approved their submission. Ethical Considerations Ethical approval was obtained from the Ebonyi State Ministry of Health Ethics Review Committee with assigned number EBSHREC 2025/011. Informed consent was secured from adult participants, and assent was obtained from minors with parental consent. Participation was voluntary, and confidentiality was strictly maintained by anonymizing data and restricting access to authorized personnel only. Conflict of Interest The authors declared that there was no conflict of interest. Funding This research work was funded by all the Authors References Arbyn M, Weiderpass E, Bruni L, de Sanjosé S, Saraiya M, Ferlay J, Bray F (2020) Estimates of incidence and mortality of cervical cancer in 2018: A worldwide analysis. 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J Immunol Vaccines 3(5):225–233 Ncube B, Jerneck A, Malmström M (2021) Socioeconomic inequalities in HPV vaccination coverage in sub-Saharan Africa. J Health Inequalities 2(2):112–124 Onu EN, Ilang DC, Azi CI, Eze TO, Akpa CO, Ogbonna OE, Agada SE, Onwe MC (2024) Surveillance of High-Risk Type-16 and 18 Human Papillomavirus among HIV Positive and Non-Positive Individuals at Federal Teaching Hospital Ebonyi State Nigeria. Adv Microbiol 14:647–662 Ngoma T, Autier P (2019) Cancer prevention strategies in Africa: Lessons from HPV vaccination. J Cancer Prev Control 5(3):101–110 Okoye CN, Anyanwu EG, Ekwueme OC (2022) Cold-chain management and vaccine efficacy in southeastern Nigeria: An operational assessment. J Public Health Manage 8(6):678–686 Yahya AI, Usman AR, Hassan LM (2021) Knowledge and perception of HPV vaccination among Nigerian adolescents. J Health Promotion Educ 6(4):214–222 Zhao J, Chen W, Xu H (2023) Comparison of HPV vaccine immunogenicity between urban and rural populations: A systematic review. J Immunological Res 9(1):95–106 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8047715","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":541000366,"identity":"a13bb415-501b-4507-a657-93de23a1710b","order_by":0,"name":"Onu Euslar Nnenna","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYHACxgMQmvnAByDJA8QGBPVAtbAlziBVC4/hDKgAfi38EukPDvzcwyBnLpHzsZl3h50MA3vzNgnGHbU4tUjOyDE42POMwdhyRu7GZt4zyTwMPMfKJBjPHMepxeBGDsMBngMMiRtu5G5/zNvGzMMgkWMmwdh2DKcW+xvpDw7+AWvJedjM21bPwyD/Br8WA4kEg8MQW3IYgVoOA23hAWmpwalF4swbg8MyBySMDc48M2yc23ach40nrdgise0ATi387ekPH745YCNncDz5YcPbtmp7fvbDG298bKvDqQVmGYLJBiISGA4T0oIJCNoyCkbBKBgFIwcAAMNQU9AKYI5SAAAAAElFTkSuQmCC","orcid":"","institution":"Alex-Ekwueme Federal University Ebonyi State","correspondingAuthor":true,"prefix":"","firstName":"Onu","middleName":"Euslar","lastName":"Nnenna","suffix":""},{"id":541001233,"identity":"32ee471f-1c1d-49d6-ba0c-ae1dd2d4a33b","order_by":1,"name":"Obaji Ezekiel Amuche","email":"","orcid":"","institution":"Alex-Ekwueme Federal University Ebonyi State","correspondingAuthor":false,"prefix":"","firstName":"Obaji","middleName":"Ezekiel","lastName":"Amuche","suffix":""},{"id":541007655,"identity":"985817ea-9807-4544-b4b2-8d69ad3776a8","order_by":2,"name":"Azi Cornelius Ituma","email":"","orcid":"","institution":"Northern Care Alliance NHS Foundation Trust, Manchester City, United Kingdom","correspondingAuthor":false,"prefix":"","firstName":"Azi","middleName":"Cornelius","lastName":"Ituma","suffix":""},{"id":541007784,"identity":"b75dfbfa-ff55-46ea-989c-f8d2129cdcb5","order_by":3,"name":"Akpa Chinedu Obasi","email":"","orcid":"","institution":"Department of Haematology, Faculty of Basic Clinical Sciences, Alex-Ekwueme Federal University Teaching Hospital, Abakaliki City Ebonyi State, Nigeria","correspondingAuthor":false,"prefix":"","firstName":"Akpa","middleName":"Chinedu","lastName":"Obasi","suffix":""},{"id":541008649,"identity":"dd52c8dc-d369-4ae7-ad6b-e4c69de49eec","order_by":4,"name":"Onu Emmanuel Mbah","email":"","orcid":"","institution":"Department of Pathology, Faculty of Basic Clinical Sciences, Alex-Ekwueme Federal University Teaching Hospital, Abakaliki City Ebonyi State, Nigeria","correspondingAuthor":false,"prefix":"","firstName":"Onu","middleName":"Emmanuel","lastName":"Mbah","suffix":""},{"id":541008952,"identity":"01050640-66a5-4c6b-ad15-c0ed312e2e69","order_by":5,"name":"Orji Christian Echezona","email":"","orcid":"","institution":"Alex-Ekwueme Federal University Ebonyi State","correspondingAuthor":false,"prefix":"","firstName":"Orji","middleName":"Christian","lastName":"Echezona","suffix":""},{"id":541016937,"identity":"c968837c-9a8e-4255-8895-0d197f391dea","order_by":6,"name":"Ologwu Richard Ogbonnaya","email":"","orcid":"","institution":"Akanu Ibiam Federal Polytechnic Unwana, Afikpo Ebonyi State. 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1","display":"","copyAsset":false,"role":"figure","size":945318,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Ebonyi State showing Ezza North and Abakaliki local government\u003c/p\u003e\n\u003cp\u003eSource: Ude (2011).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8047715/v1/46255a945298be873b6abf9b.jpeg"},{"id":95530766,"identity":"fcd5539c-d100-4b9c-8cc7-c8b83b95c69b","added_by":"auto","created_at":"2025-11-10 10:21:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1972299,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8047715/v1/1bfdac10-1369-4020-8880-86b61afef3ee.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eComparative Evaluation of IgG Antibody Response to HPV Vaccination among Urban and Rural Populations in Ebonyi State, Nigeria\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman Papillomavirus (HPV) is among the commonest sexually transmitted disease in the world and a leading etiological agent of cervical cancer [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] which is a major public health concern, especially in underdeveloped nations with low and middle incomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to the estimates by the World Health Organization (WHO), persistent HPV infection, and in particular, the high-risk genotypes of HPV 16 and 18, are the cause of cervical cancer in more than 95 percent of cases [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. HPV vaccination has shown to be a beneficial preventative measure against HPV, which causes strong humoral responses and long protection against HPV infection and malignancy [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHPV vaccine protection is immunologically based on the production of the neutralizing antibodies, mainly Immunoglobulin G (IgG), preventing the viral entry and replication in the host epithelial cells. The level of serum IgG is consequently one of the most significant biomarkers to determine the power and duration of immune response after vaccination [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Some of the studies have shown that high IgG levels are associated with long-term protection and low exposure to HPV-associated diseases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Nevertheless, the new data shows that socioeconomic, environmental, and healthcare delivery disparities have the potential to affect vaccine immunogenicity resulting in uneven antibody responses across various populations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe coverage of HPV vaccination is not optimal in Nigeria, and the disparity between Nigerian cities and rural populations is very high [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Urban residents have more advantages in the form of improved healthcare infrastructure, the availability of vaccines, and cold-chain, and rural communities have issues with poor vaccine storage, low awareness, and poor healthcare-seeking behavior [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These disparities can be converted into quantifiable variations in subsequent vaccination outcomes of immunization, and finally influence the effectiveness of HPV immunization strategies, as a whole. The awareness of such disparities is important to maximize the benefits of vaccination methods and attain fair cervical cancer prevention activities [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough the introduction of HPV vaccination campaigns in Nigeria has been carried out, there are limited studies that have looked at the immunological response of this vaccine in various population settings. Past studies have devoted a lot of attention to vaccine uptake and awareness and very few studies have dealt with comparative antibody response in both urban and rural population. It is thus necessary to measure the immunology of the HPV vaccination in these different settings to determine any possible gaps in the delivery and efficacy of the vaccine.\u003c/p\u003e\u003cp\u003eThe purpose of this study was to compare and contrast IgG antibody and immune indexes (ABS and INDEX) between vaccinated people living in urban (Abakaliki) and rural (Ezza North) communities of the city of Ebonyi, Nigeria. The study can inform the immunological efficacy of HPV vaccination in various population settings by examining the magnitude of the vaccine-induced IgG responses as well as the factors affecting the magnitude of responses.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Area\u003c/h2\u003e\u003cp\u003eThe research was carried out in the Ebonyi State Ezza North and Abakalik LGA, Nigeria. Ezza North is a largely rural area whose healthcare amenities are low, with low vaccine coverage, and low socioeconomic indicators. The capital of the state, Abakaliki, is urbanized and has a more developed health care infrastructure, a greater level of literacy, and a relatively greater vaccination rate. The target population is those that are aged 926 years old and have previously received at least one dose of the HPV vaccine. This is the age range in the WHO guidelines regarding the HPV vaccination which is aimed at preadolescents, adolescents and young adults. The participants were recruited in the two LGAs in schools, health facilities, and community outreach programs. These are the peculiarities that allow comparing the two LGAs in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eResearch Design\u003c/h3\u003e\n\u003cp\u003eThe present study was a comparative cross-sectional research design to measure the IgG immune response of HPV-vaccinated people in Ezza North and Abakaliki LGAs. Cross-sectional designs are most suitable in assessing the immune response and distinguishing between the populations of different populations at a given time [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The criteria of inclusion are that the individuals must be aged between 9 and 26 years old, be residents of Ezza North or Abakaliki LGA at least one year long and be willing to give an informed consent or assent (with parental consent in cases of minors). The exclusion criteria are those people who have not received all vaccinations or have no idea of their vaccination status, pregnant people (hormonal changes can affect the level of IgG), as well as those who have known immunosuppressive conditions or immunosuppressive treatment.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.4 Sample Size Determination\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe sample size was determined using a standard formula for cross-sectional studies:\u003c/p\u003e\u003cp\u003estudies.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:n=\\frac{{Z}^{2}\\:P(1-P)}{{d}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere:\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;sample size\u003c/p\u003e\u003cp\u003eZ\u0026thinsp;=\u0026thinsp;standard normal deviation at 95% confidence level (1.96)\u003c/p\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;estimated HPV prevalence in similar populations (based on previous studies or literature, often at 10%)\u003c/p\u003e\u003cp\u003ee\u0026thinsp;=\u0026thinsp;margin of error (typically set at 5%):\u003c/p\u003e\u003cp\u003eTherefore:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{n}_{0}=({1.96)}^{2}\\times\\:\\frac{0.10\\left(1-0.10\\right)}{{\\left(0.05\\right)}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{n}_{0}=\\frac{3.8416\\times\\:0.09}{0.0025}=\\frac{0.3457}{0.0025}=139$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThus, the computed sample size was 139 participants for one study location\u003c/p\u003e\u003cp\u003e\u003cb\u003eSampling Method and Collection of Samples\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eMulti-stage sampling was used where the selection of wards in each LGA was done randomly in order to provide geographical coverage. In the chosen wards, schools, health, and communities, the selection was purposively convenient with regard to the possibility of having participants who qualify under the inclusion criteria. 5mL of venous blood was collected using sterile syringes and vacutainer tubes and a certified phlebotomist recruited the participants and collected the blood [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The venipuncture was done in accordance with WHO-suggested guidelines regarding the blood collection practices to prevent any complications and discharge the samples intact [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The minimization of the risk of contamination was achieved by the use of standard aseptic procedures such as gloves, alcohol swabs, and disposable needles [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. All the gathered blood specimen was marked with special identifiers so as to track it and send it to the laboratory in coolers with ice packs. Separated serum was frozen at -20 o C until analysis [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Observation of participants was conducted in the short term following the collection of samples in case of adverse reactions.\u003c/p\u003e\n\u003ch3\u003eLaboratory Analysis\u003c/h3\u003e\n\u003cp\u003eThe individual sample serums were tested on IgG concentrations using Enzyme-Linked Immunosorbent Assay (ELISA) kits of HPV antibodies. ELISA is a gold standard method of detecting antibodies because it is highly sensitive and specific. The assay had been conducted in two doses in order to guarantee reliability and consistency of the results.\u003c/p\u003e\u003cp\u003eLab procedures were done as per the instructions given by the manufacturer in ELISA kit. These involve preparation of reagents, serial dilutions of samples and optical densities on ELISA plate reader. The findings were then related to the standard curve to measure the levels of IgG. The standard operating procedures were also followed by all the staff in the laboratories to ensure accuracy and reproducibility [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eThe comparison of the means of IgG between the Ezza North and Abakaliki LGAs was done using independent samples t-tests. T-test was used to determine the difference in IgG levels among sub-groups through R coding statistical analysis software. Statistical analysis (Independent t-test, Chi-square, logistic regression)\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eThe IgG levels in HPV-vaccinated individuals in Ezza North LGA and Abakaliki LGA\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e indicates that there is a pronounced difference in IgG antibody levels and the indices of the immune response in the population of the Abakaliki LGA and Ezza North LGA with respect to the vaccination status. The mean IgG level (ABS) in Abakaliki was 0.598 and standard deviation\u0026thinsp;=\u0026thinsp;0.340. Its median was 0.574, range of interquartile is 0.287 to 0.922, and values were in the range of 0.056 to 1.185. Conversely, the standard deviation of 0.096 gave the mean ABS of 0.072 in Ezza North. The median was 0.057 with the interquartile range of 0.020 to 0.091 with the values of 0.001 to 0.946. This implies that the mean concentration of IgG in Abakaliki was approximately eight times greater when compared to Ezza North and most of the rural responses were concentrated towards the lower end of the scale.\u003c/p\u003e\u003cp\u003eOn the same note, the index of immune response (INDEX) in Abakaliki was a lot higher than in Ezza North. The standard deviation of 2.08 and the mean of 3.62 gave the mean of 3.58 and the range of the interquartile of 1.82 to 5.16 as the mean INDEX in Abakaliki. The values were ranging between 0.36 and 7.94. In Ezza North, the mean INDEX was 0.43 and standard deviation was 0.58, median was 0.35, interquartile of 0.12\u0026ndash;0.55 and the range was 0.006 to 5.73. Once again, the mean response in Abakaliki was greater than eight times bigger than the one in Ezza North (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003ea)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003ea\u003c/b\u003e: IgG Levels (ABS) and INDEX in-vaccinated individuals in Ezza North LGA and Abakaliki LGA.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eABS Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eABS Median (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eABS Range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eINDEX Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eINDEX Median (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eINDEX Range\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAbakaliki\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.598\u0026thinsp;\u0026plusmn;\u0026thinsp;0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.574 (0.287\u0026ndash;0.922)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.056\u0026ndash;1.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.58 (1.82\u0026ndash;5.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.36\u0026ndash;7.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEzza North\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.072\u0026thinsp;\u0026plusmn;\u0026thinsp;0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.057 (0.020\u0026ndash;0.091)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u0026ndash;0.946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.35 (0.12\u0026ndash;0.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.006\u0026ndash;5.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePercentage of Neg/POS of IgG Levels (ABS) and INDEX in-vaccinated individuals in Ezza North and Abakaliki LGA\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe findings indicate that there are drastic differences in the level of IgG and response rates of the two study groups. The IgG concentration (ABS) mean of Abakaliki was 0.598 as 0.340 with a median of 0.574 (IQR: 0.287\u0026ndash;0.922). There was also a high index of immune response with the average of immune response being 3.62\u0026thinsp;+\u0026thinsp;2.08 but the median of this index was 3.58 (IQR: 1.82 5.16). On the IgG status, 86.3% (n\u0026thinsp;=\u0026thinsp;120) of the participants were positive, 8.6% (n\u0026thinsp;=\u0026thinsp;12) negative and only 5.0% (n\u0026thinsp;=\u0026thinsp;7) were equivocal.\u003c/p\u003e\u003cp\u003eComparatively, the members of Ezza North responded with considerably reduced immunity. They had a mean ABS of 0.072, SD\u0026thinsp;=\u0026thinsp;0.096 with a median of 0.057 (IQR: 0.020\u0026ndash;0.091), and a mean INDEX of 0.43, SD\u0026thinsp;=\u0026thinsp;0.58 with a median of 0.35 (IQR: 0.12\u0026ndash;0.55). Distribution of the IgG status demonstrated that 69.1% (n\u0026thinsp;=\u0026thinsp;96) were positive, 27.3% (n\u0026thinsp;=\u0026thinsp;38) negative and 3.6% (n\u0026thinsp;=\u0026thinsp;5) equivocal. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003eb)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eb\u003c/b\u003e: Percentage of Neg/POS of IgG Levels (ABS) and INDEX in-vaccinated individuals in Ezza North and Abakaliki LGA\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eABS Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eABS Median (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eINDEX Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eINDEX Median (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEQ (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNEG (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ePOS (n, %)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbakaliki\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.598\u0026thinsp;\u0026plusmn;\u0026thinsp;0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.574 (0.287\u0026ndash;0.922)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.58 (1.82\u0026ndash;5.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e7 (5.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e12 (8.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e120 (86.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEzza North\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.072\u0026thinsp;\u0026plusmn;\u0026thinsp;0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.057 (0.020\u0026ndash;0.091)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.35 (0.12\u0026ndash;0.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5 (3.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e38 (27.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e96 (69.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eThe independent t-test comparing IgG levels (ABS) between Abakaliki and Ezza North\u003c/h3\u003e\n\u003cp\u003eIndependent t-test between the IgG levels (ABS) of Abakaliki and Ezza North indicates that the t-statistics is 17.53 with a p-value of less than 0.00001 which is highly significant. This indicated that the level of IgG antibody in vaccinated people of Abakaliki was significantly higher than in Ezza North, which means that the difference in immune responses was statistically significant and not accidental (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe independent t-test comparing IgG levels (ABS) between Abakaliki and Ezza North\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComparison\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003et-Statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbakaliki vs. Ezza North (ABS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.00001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe summary results of IgG antibody levels and positivity rates and HPV vaccination rates in urban community of Abakaliki and the rural community of Ezza North\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIt also show a great disparity in the level of IgG antibodies and the coverage of HPV vaccination between the rural community of Ezza North and urban community of Abakaliki. Regarding the level of antibody, the participants in Abakaliki had significantly higher levels of ABS, which was 0.598 +/- 0.340 mean of IgG and ABS of 0.072 +/- 0.096 in Ezza North. This difference was also observed in the median values, as Abakaliki had the median of 0.574 (IQR 0.2870.922) and Ezza North had the median of 0.057 (IQR 0.0200.091). Equally, the IgG index value was significantly higher in the city of Abakaliki (mean 3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08; median 3.58) compared to that of Ezza North (mean 0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58; median 0.35). Categorically in serostatus, 86.3 percent of the persons in Abakaliki were found to be IgG positive, but only 69.1 percent in Ezza North and over three times higher in the rural compared to the urban groups, who were IgG negative (27.3 and 8.6 percent). This was a significant difference as indicated in the independent t-test of the IgG levels (t\u0026thinsp;=\u0026thinsp;17.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). Regarding the uptake in terms of the vaccination coverage, Abakaliki was found to have a higher uptake rate since 120 out of the 139 participants (86.3 percent) in Abakaliki were vaccinated compared to 96 out of the 139 participants (69.1 percent) in Ezza North. This difference was statistically significant using chi -square test (Chi 2\u0026thinsp;=\u0026thinsp;10.981, p\u0026thinsp;=\u0026thinsp;0.00092) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe IgG antibody levels and positivity rates and HPV vaccination rates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eABS Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eABS Median (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eINDEX Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eINDEX Median (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEQ (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNEG (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ePOS (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eVaccination Rate (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbakaliki (Urban)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.598\u0026thinsp;\u0026plusmn;\u0026thinsp;0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.574 (0.287\u0026ndash;0.922)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.58 (1.82\u0026ndash;5.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e7 (5.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e12 (8.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e120 (86.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e86.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEzza North (Rural)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.072\u0026thinsp;\u0026plusmn;\u0026thinsp;0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.057 (0.020\u0026ndash;0.091)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.35 (0.12\u0026ndash;0.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5 (3.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e38 (27.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e96 (69.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e69.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cb\u003eKey\u003c/b\u003e: ABS: IgG absorbance (antibody concentration), INDEX: Computed immune response index, EQ: Equivocal; NEG: Negative; POS: Positive IgG, \u003cem\u003et\u0026thinsp;=\u0026thinsp;17.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001 \u0026rarr; Significant difference (Urban\u0026thinsp;\u0026gt;\u0026thinsp;Rural)\u003c/em\u003e, \u003cem\u003eχ\u0026sup2; = 10.981, p\u0026thinsp;=\u0026thinsp;0.00092 \u0026rarr; Significant difference in vaccination rate (Urban\u0026thinsp;\u0026gt;\u0026thinsp;Rural)\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLogistic Regression Coefficients of comparison of factors that affect immune response to HPV vaccine between urban and rural communities of Ebonyi State\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe findings of the logistic regression analysis that assessed predictors of IgG antibody response after vaccination against HPV are given in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e10\u003c/span\u003e. There was a significant positive intercept (=\u0026thinsp;0.7919, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), thus, a high probability of the immune response with no or very minimal input to mounting the immune response. ABS variable (3.5790, p\u0026thinsp;=\u0026thinsp;0.363) and INDEX ( -0.5731, p\u0026thinsp;=\u0026thinsp;0.363) failed to demonstrate statistically significant relationships with IgG positivity indicating that in this dataset neither of these two variables was a strong predictor. A large effect was observed, however, with group (urban vs rural). Group Binary coefficient was 1.0068 (p\u0026thinsp;=\u0026thinsp;0.032) with a 95% interval of 0.085 to 1.928. This means that the subjects in urban Abakaliki had a higher tendency of a positive IgG response than the rural Ezza North.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLogistic Regression Coefficients of comparison of factors that affect immune response to HPV vaccine between urban and rural communities of Ebonyi State\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoef. (β)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Err.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI [Lower, Upper]\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIntercept\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.7919\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.419\u0026ndash;1.164\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eABS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.5790\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.937\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.909\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.137\u0026ndash;11.295\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eINDEX\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.5731\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.910\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-1.808\u0026ndash;0.661\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGroup_Binary\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.470\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.085\u0026ndash;1.928\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eOdds Ratios (from Logistic Regression) of comparison of factors that affect immune response to HPV vaccine between urban and rural communities of Ebonyi State\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIt is the odds ratios based on the logistic regression model and it provides a better understanding of the role of each factors in the development of IgG antibody response following the HPV vaccination. The intercept indicates an odds ratio of 2.21 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) which means that there is a high likelihood of seroconversion at the baseline. The odds ratio of ABS was very high (35.84), however, this was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.363), which implies that it is not reliable to predict response in this dataset. Equally, INDEX had an odds ratio that was lower than 1 (0.56, p\u0026thinsp;=\u0026thinsp;0.363), which was not significant, indicating weak predictive ability.\u003c/p\u003e\u003cp\u003eOn the contrary, the odds ratio of the group variable (urban vs rural) was 2.74 (p\u0026thinsp;=\u0026thinsp;0.032), which indicated that the participants in Abakaliki (urban) were nearly three times more likely to mount an IgG response than those in Ezza North (rural). This supports previous results of the chi-square tests and descriptive analysis that location along with the social and healthcare factors related to it determines the ultimate outcome of immune response (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e11\u003c/span\u003e) decisively.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOdds Ratios (from Logistic Regression) of comparison of factors that affect immune response to HPV vaccine between urban and rural communities of Ebonyi State\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.00003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINDEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup_Binary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe significantly higher average IgG absorbance and the immune index in Abakaliki than in Ezza North (Abakaliki ABS 0.598\u0026thinsp;+\u0026thinsp;0.340 vs Ezza North 0.072\u0026thinsp;+\u0026thinsp;0.096: t\u0026thinsp;=\u0026thinsp;17.53, p\u0026thinsp;=\u0026thinsp;0.00001) is in agreement with the fact that licensed HPV vaccines can produce robust and long-lasting humoral immunity under optimal conditions. Sustained seropositivity and maintenance of antibody levels several years after full vaccination confirmed by long-term follow-up and clinical trial data demonstrate that the vaccine has enough biological potential to induce a long-term IgG response in case storage, handling and dosing regimens are maintained [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePopulation level syntheses underscore the fact that the coverage and strategy of delivery of programmes on HPV immunization has both a direct and herd effects on HPV immunization. Multi-cohort campaigns and high coverage have been reportedly associated with the highest decrease in HPV infection and pre-cancerous lesions, and patchy or low coverage suppresses individual and population-level benefits [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The fact that Abakaliki (86.3) had higher rates of vaccination and IgG-positivity than Ezza North (69.1) therefore may mean that these gaps may be major contributors to the greater antibody reactions of the urban cohort and may imply that the rural population may not be getting much of the indirect benefits of herd protection in the event that these gaps do not improve [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOperational and logistics issues allow us to offer a plausible proximate explanation of the decreased measured antibody titers in rural environments. The implementation studies and program evaluations in low- and middle-income countries report that the last-mile distribution issues, intermittent power, and cold-chain leakage is an ordinary problem in the resource-constrained regions and may lower the vaccine potency and the observed immunogenicity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In the context of cold-chain integrity and complete dosing is not achievable, field-measured antibody levels can be weakened despite an effective vaccine because of the importance of fortifying these supply-chain factors has been noted [21].\u003c/p\u003e\u003cp\u003eBoth uptake and immunological outcomes are also determined by the sociodemographic and delivery-platform determinants. Recent mixed-methods and survey research in sub-Saharan Africa demonstrates that caregiver knowledge, access to delivery in schools, organization of service and vaccine hesitancy are associated with individuals who are vaccinated and adherence to schedule; all these factors are associated with timing and completion of dosing and subsequent magnitude of the antibody [33,34]. Your logistic regression that urban residence is an indicator of seropositivity (OR 2.74, p\u0026thinsp;=\u0026thinsp;0.032) is consistent with the regional data that urban populations are more likely to use an organized delivery platform and have better completion rates, which is presumably intended to contribute to the stronger serological responses in the urban cohort [33,34].\u003c/p\u003e\u003cp\u003eNew findings of lower dose schedules introduce a twist in the interpretation of the intergroup differences in the antibody levels. Since 2019, there have been several observational and trial reports indicating that single dose or delayed dose regimens can offer strong protection in many settings; however, serotiter is often less following the single dose and the long term durability is still the matter of ongoing study (recent reviews 2019\u0026ndash;2023). In addition, suggesting that the disparity between your cohorts in terms of dosing completeness/length of time since vaccination could partly account for lower rural titers, this study underscores the importance of including verified dosing-history and time data in future studies (recent reviews and trial updates).\u003c/p\u003e\u003cp\u003ePut collectively, the literature suggests three practical implications to your findings. To begin with, contextual and programmatic deficiencies explain (better) the low rural titers than does an inherent vaccine failure. Second, there is a need to lessen the disparity in the coverage and delivery of HPV in cities and rural areas at both the individual level and to obtain the population-wide reductions in HPV-related illness that elimination models predict. Third, targeting of operational research linking serology with cold chain monitoring and keeping dosages-verified histories of contextual variables, such as nutrition, comorbidity, Lange's timing could better isolate drivers of given interventions such as strengthening cold chains, expanding school-based delivery or catch-up campaigns that could be directed at rural areas (Brisson et al., 2020; WHO, 2021; Gavi, 2020).\u003c/p\u003e\u003cp\u003eThey also need to recognize limitations of interpretation: recommended studies on measured antibody titers are sensitive to time since last dose and number of doses administered and without absolute and well validated dosing histories and cold-chain records they cannot be unambiguously ascribed to any single cause low rural titers. Combined operational monitoring data and longitudinal serology will be most informative in future work in order to inform programmatic decision-making (Brisson et al., 2020; Otieno et al., 2021).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of the study show that there exists an urban-rural disparity in HPV vaccine-elicited IgG antibody reaction among vaccinated individuals in the Ebonyi State in Nigeria. The levels of IgG (mean ABS 0.598 0.340) and the levels of the immune index (mean INDEX 3.62 2.08) were significantly higher in the participants of Abakaliki (urban) than the participants of Ezza North (rural) whose mean ABS and INDEX 0.072 0.096 0.43 0.58, respectively. This was very significant as indicated by independent t -test ( t\u0026thinsp;=\u0026thinsp;17.53, p less than 0.00001) but the logistic regression ( OR\u0026thinsp;=\u0026thinsp;2.74, p\u0026thinsp;=\u0026thinsp;0.032) revealed that urban participants were almost three times more apt to mount positive response in IgG in contrast to rural participants. These results suggest that the HPV vaccination is immunologically active but effects are enhanced by environmental, infrastructural and socio-economic determinants of HPV vaccinations that differ between the urban and rural populations.\u003c/p\u003e\u003cp\u003eThe reasons that could have explained these differences include the ease of access to healthcare, more robust systems of administering vaccines, and improved cold-chain systems in urban locations. On the other hand, the rural environment has been challenged in the aspect of the lack of uniform supply of vaccines, lack of sufficient healthcare centers, lack of effective community health education, and the likelihood of cold-chain interferences. Such discrepancies may influence the efficiency of the HPV immunization programme in Nigeria overall and slack the goal of providing equal cervical cancer prevention. These results draw attention to the fact that it is necessary to address logistical, infrastructural, and behavioral determinants limiting the measures against vaccine coverage and immune response in rural populations.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eRecommendations\u003c/h2\u003e\u003cp\u003eEnhancement of the Rural Immunization Infrastructure: The government and the public health organizations are intended to enhance healthcare infrastructure and avail good cold-chain facilities in the rural communities. The storage facilities in which the vaccines are kept have to be checked and assessed regularly in order to make sure that the immunogenicity is not lost as well as the vaccines remain in their potent state. Enhanced Community-Based Outreach: door to door immunization, school based programmes, mobile clinics should be intensified in order to promote the rural vaccination programmes. These efforts will enhance accessibility and more so in the case of adolescent girls who are the central subjects of HPV vaccination.\u003c/p\u003e\u003cp\u003eIt is necessary to create comprehensive education programmes which will dispel the myths about vaccines against HPV and make people know more about their benefits. The positive attitude towards vaccination needs to be promoted by the involvement of social leaders, educators, and churches. Policy and Governmental Pledge: The Ministry of Health should pay attention to the equal access to vaccines and invest in the under-serviced places. It will be sustainable by introducing the use of HPV vaccination to the existing primary healthcare services and National Immunization Programme. Research and Monitoring: The problems concerning the immune response such as nutritional state, intervals of administration, and management of vaccines in rural settings require to be researched. Continuous serological monitoring will help in assessing the efficacy of the vaccine, and providing a policy adjustment.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthors contribution\u003c/p\u003e\n\u003cp\u003eAll the authors contributed to this research work, starting from the beginning of the research to the stage of developing the manuscripts and approved their submission.\u003c/p\u003e\n\u003cp\u003eEthical Considerations\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Ebonyi State Ministry of Health Ethics Review Committee with assigned number EBSHREC 2025/011. Informed consent was secured from adult participants, and assent was obtained from minors with parental consent. Participation was voluntary, and confidentiality was strictly maintained by anonymizing data and restricting access to authorized personnel only.\u003c/p\u003e\n\u003cp\u003eConflict of Interest\u003c/p\u003e\n\u003cp\u003eThe authors declared that there was no conflict of interest.\u003c/p\u003e\n\u003cp\u003eFunding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research work was funded by all the Authors \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArbyn M, Weiderpass E, Bruni L, de Sanjos\u0026eacute; S, Saraiya M, Ferlay J, Bray F (2020) Estimates of incidence and mortality of cervical cancer in 2018: A worldwide analysis. J Global Health 8(2):191\u0026ndash;203\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBruni L, Saura-L\u0026aacute;zaro A, Montoliu A, Brotons M, Alemany L, Diallo MS, Vall\u0026egrave;s X, de Sanjos\u0026eacute; S (2019) Global progress and challenges in implementing HPV vaccination programs. J Vaccine Res 7(2):219\u0026ndash;225\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization (WHO) (2021) Global strategy to accelerate the elimination of cervical cancer as a public health problem. World Health Organization, Geneva, Switzerland\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarland SM, Paavonen J, Jaisamrarn U, Naud P, Salmer\u0026oacute;n J, Chow SN, Apter D, Castellsagu\u0026eacute; X, Teixeira JC, Germar MJ, Limson G, Romanowski B, Schwarz TF, Poppe WA, de Carvalho NS, Harper DM, David MP, Lehtinen M (2019) Immunogenicity and safety of HPV vaccines: Long-term follow-up results. J Hum Vaccines Immunotherapeutics 5(7\u0026ndash;8):1760\u0026ndash;1769\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEuslar NO, Emmanuel MO, Cornelius IA, Donatus Cl, Chinedu OA, Theophilus OE, Vivian CO, Okechukwu EO, Samuel EA, Samuel UO (2024) Knowledge and Attitude Towards Human Papillomavirus Infection, Vaccines and Cervical Cancer Prevention in Eastern, Nigeria. \u003cem\u003eInternational Journal of Virology, 20: 1\u0026ndash;9.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDrolet M, B\u0026eacute;nard \u0026Eacute;, P\u0026eacute;rez N, Brisson M, Vaccination Impact Study Group (2019) Population-level impact and herd effects following HPV vaccination: Updated systematic review and meta-analysis. J Infect Dis 4(7):497\u0026ndash;509\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrisson M, Kim JJ, Canfell K, Drolet M, Gingras G, Burger EA, Martin D, Simms KT, Benard \u0026Eacute;, Boily MC, Bray F (2020) Global elimination of cervical cancer requires both high-coverage vaccination and screening. J Oncol 2(3):293\u0026ndash;300\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOkunowo AA, Daramola ES, Soibi-Harry AP, Ezenwankwo FE, Okunade KS, Anorlu RI (2021) Awareness and uptake of human papillomavirus vaccine among Nigerian women: A multi-regional study. J Public Health Stud 1(1):64\u0026ndash;72\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOtieno N, Nyangahu DD, Obila JO, Oduor CI, Ochieng J (2021) Urban\u0026ndash;rural differences in HPV vaccine uptake and antibody response among adolescent girls in Kenya. J Vaccine Res 9(2):55\u0026ndash;62\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGavi, The Vaccine Alliance (2020) Improving immunization coverage in low-income countries: Lessons from HPV vaccine delivery. Gavi Secretariat, Geneva, Switzerland\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdepoju P (2022) HPV vaccine rollout in Africa: Barriers and opportunities for equitable immunization. J Global Public Health 7(4):512\u0026ndash;520\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEze CU, Nwafor CC, Ogu RN (2020) Determinants of cervical cancer prevention practices among rural Nigerian women. J Community Med Prim Health Care 3(1):45\u0026ndash;54\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKiggundu R, Okoth F, Mugisha E (2020) Human papillomavirus antibody response following vaccination in rural Uganda: A comparative analysis. J Afr Health Sci 2(4):1872\u0026ndash;1880\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMugo NR et al (2019) Ten-year antibody persistence following HPV vaccination in African adolescents. J Immunol Vaccines 3(5):225\u0026ndash;233\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNcube B, Jerneck A, Malmstr\u0026ouml;m M (2021) Socioeconomic inequalities in HPV vaccination coverage in sub-Saharan Africa. J Health Inequalities 2(2):112\u0026ndash;124\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOnu EN, Ilang DC, Azi CI, Eze TO, Akpa CO, Ogbonna OE, Agada SE, Onwe MC (2024) Surveillance of High-Risk Type-16 and 18 Human Papillomavirus among HIV Positive and Non-Positive Individuals at Federal Teaching Hospital Ebonyi State Nigeria. Adv Microbiol 14:647\u0026ndash;662\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNgoma T, Autier P (2019) Cancer prevention strategies in Africa: Lessons from HPV vaccination. J Cancer Prev Control 5(3):101\u0026ndash;110\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOkoye CN, Anyanwu EG, Ekwueme OC (2022) Cold-chain management and vaccine efficacy in southeastern Nigeria: An operational assessment. J Public Health Manage 8(6):678\u0026ndash;686\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYahya AI, Usman AR, Hassan LM (2021) Knowledge and perception of HPV vaccination among Nigerian adolescents. J Health Promotion Educ 6(4):214\u0026ndash;222\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao J, Chen W, Xu H (2023) Comparison of HPV vaccine immunogenicity between urban and rural populations: A systematic review. J Immunological Res 9(1):95\u0026ndash;106\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Human Papillomavirus, IgG Antibody, Vaccine Efficacy, Urban–Rural Disparity, Ebonyi State","lastPublishedDoi":"10.21203/rs.3.rs-8047715/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8047715/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Human Papillomavirus (HPV) is still one of the most widespread sexually transmitted diseases as well as a major cause of cervical cancer in the world. Immunization, especially the production of IgG antibodies is an essential pointer of protection that has been induced by the vaccine. The research study measured and compared the levels of IgG antibody and the immune index (ABS and INDEX) after the HPV vaccination among the urban and rural communities in Ebonyi State, Nigeria. There were 278 participants who received the vaccination that had been recruited; 139 in Abakaliki (urban) and 139 in Ezza North (rural).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: In order to determine the levels of serum IgG, Enzyme-Linked Immunosorbent Assay (ELISA) was used and the test results were analyzed through independent t-tests, Chi-square, and logistic regression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The findings showed that the mean levels of IgG were also significantly more in Abakaliki (ABS 0.598 ± 0.340; INDEX 3.62 ± 2.08) than in Ezza North (ABS 0.072 ± 0.096; INDEX 0.43 ± 0.58). The difference in the response of antibodies was significantly different (t = 17.53, p \u0026lt; 0.00001). The percentage of vaccination and IgG positivity was also larger in Abakaliki (86.3%) compared to Ezza North (69.1%). The logistic regression analysis revealed that the participants in urban areas were two and half times more likely to develop a positive IgG response in comparison to the participants in the rural area (p = 0.032)(p\u0026lt;0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: The results indicate that there is a strong urban-rural gap in immunity developed due to HPV vaccination, and that vaccine manipulation, access to healthcare, and socio-environmental conditions affect the immune measures. Strengthening cold-chain infrastructure, enhance outreach vaccination in rural areas, and increase awareness of the population to have equal vaccine efficacy can play a role in the reduction of HPV-related diseases in Nigeria.\u003c/p\u003e","manuscriptTitle":"Comparative Evaluation of IgG Antibody Response to HPV Vaccination among Urban and Rural Populations in Ebonyi State, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-07 06:01:19","doi":"10.21203/rs.3.rs-8047715/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f597cfdd-f819-4982-8eb5-c12b6ef09ef4","owner":[],"postedDate":"November 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57551726,"name":"Immunology"}],"tags":[],"updatedAt":"2025-11-07T06:01:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-07 06:01:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8047715","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8047715","identity":"rs-8047715","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}