Infectious Disease Modelling最新文献

{"title":"Bayesian hierarchical modeling of Mpox in the African region (2022–2024): Addressing zero-inflation and spatial autocorrelation","authors":"Woldegebriel Assefa Woldegerima ,&nbsp;Chigozie Louisa J. Ugwu","doi":"10.1016/j.idm.2025.07.011","DOIUrl":"10.1016/j.idm.2025.07.011","url":null,"abstract":"<div><div>Mpox remains a signi_cant public health challenge in endemic regions of Africa. Understanding its spatial distribution and identifying key drivers in high-risk countries is critical for guiding e_ective interventions. This study applies a Zero-Inated Poisson (ZIP) model with spatial autocorrelation to estimate the adjusted relative risk (RR) of Mpox incidence across 24 African countries, strati_ed by Human Development Index (HDI) levels. The model accounts for overdispersion and excess zeros by incorporating spatial random e_ects and socio-environmental covariates, and was validated through model diagnostics and sensitivity analysis, demonstrating robustness of results. Spatial analysis revealed substantial heterogeneity in Mpox incidence, with elevated risk in the Democratic Republic of Congo (DRC), Nigeria, and Central African Republic (CAR) persisting after covariate adjustment (p &lt; 0:001). Higher HDI levels were inversely associated with Mpox risk, with HDI quintile Q4 (very high HDI) showing a signi _cant reduction (aRR = 0.431; 95 % CrI: 0.099{0.724). Protective factors in low-risk areas included increased life expectancy at birth (aRR = 0.768; 95 % CrI: 0.688{0.892), higher educational attainment (aRR = 0.774; 95 % CrI: 0.680{0.921), nonlinear increases in gross national income (GNI) per capita, and a greater density of skilled health workers (aRR = 0.788; 95 % CrI: 0.701{0.934). Conversely, higher urban density was associated with increased Mpox risk, underscoring the inuence of population clustering on transmission dynamics. Notably, statistically signi_cant elevated-risk areas persisted in endemic countries of Western and Central Africa after covariate adjustment (p &lt; 0:001). In contrast, previously undetected risk emerged in parts of Southern and Eastern Africa post-adjustment, revealing latent patterns obscured in the crude analysis (p &lt; 0:001). Exceedance probability maps identi_ed countries with P(RR &gt; 1) &gt; 0.9 as priority areas for intensi_ed surveillance and targeted intervention. These patterns were not fully explained by the included covariates, suggesting the inuence of unmeasured factors such as environmental and climate variability, zoonotic reservoirs, or human{animal interactions. Further research is needed to deepen understanding of Mpox epidemiology and support locally tailored interventions.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1575-1591"},"PeriodicalIF":2.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling the impact of hospitalization-induced behavioral changes on the spread of COVID-19 in New York City","authors":"Alice Oveson ,&nbsp;Michelle Girvan ,&nbsp;Abba B. Gumel","doi":"10.1016/j.idm.2025.05.001","DOIUrl":"10.1016/j.idm.2025.05.001","url":null,"abstract":"<div><div>The COVID-19 pandemic, caused by SARS-CoV-2, highlighted heterogeneities in human behavior and attitudes of individuals with respect to adherence or lack thereof to public health-mandated intervention and mitigation measures. This study is based on using mathematical modeling approaches, backed by data analytics and computation, to theoretically assess the impact of human behavioral changes on the trajectory, burden, and control of the COVID-19 pandemic during the first two waves in New York City. A novel behavior-epidemiology model, which considers <em>n</em> heterogeneous behavioral groups based on level of risk tolerance and distinguishes behavioral changes by social and disease-related motivations (such as peer-influence and fear of disease-related hospitalizations), is developed. In addition to rigorously analyzing the basic qualitative features of this model, a special case is considered where the total population is stratified into two groups: risk-averse (Group 1) and risk-tolerant (Group 2). The 2-group model was calibrated and validated using daily hospitalization data for New York City during the first wave, and the calibrated model was used to predict the data for the second wave. The 2-group model predicts the daily hospitalizations during the second wave almost perfectly, compared to the version without behavioral considerations, which fails to accurately predict the second wave. This suggests that epidemic models of the COVID-19 pandemic that do not explicitly account for heterogeneities in human behavior may fail to accurately predict the trajectory and burden of the pandemic in a population. Numerical simulations of the calibrated 2-group behavior model showed that while the dynamics of the COVID-19 pandemic during the first wave was largely influenced by the behavior of the risk-tolerant (Group 2) individuals, the dynamics during the second wave was influenced by the behavior of individuals in both groups. It was also shown that disease-motivated behavioral changes (i.e., behavior changes due to the level of COVID-19 hospitalizations in the community) had greater influence in significantly reducing COVID-19 morbidity and mortality than behavior changes due to the level of peer or social influence or pressure. Finally, it is shown that the initial proportion of members in the community that are risk-averse (i.e., the proportion of individuals in Group 1 at the beginning of the pandemic) and the early and effective implementation of non-pharmaceutical interventions have major impacts in reducing the size and burden of the pandemic (particularly the total COVID-19 mortality in New York City during the second wave).</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1055-1092"},"PeriodicalIF":8.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends and projections of hepatitis E incidence in Jiangsu Province of eastern China from 2007 to 2021: An analysis based on age-period-cohort models","authors":"Xiaoqing Cheng ,&nbsp;Zehui Zhang ,&nbsp;Weili Kang ,&nbsp;Xuefeng Zhang ,&nbsp;Hui Peng ,&nbsp;Changjun Bao","doi":"10.1016/j.idm.2025.05.011","DOIUrl":"10.1016/j.idm.2025.05.011","url":null,"abstract":"<div><h3>Objective</h3><div>This study aims to evaluate Hepatitis E incidence trends by age, period, and birth cohort in Jiangsu Province from 2007 to 2021 and project the future trends.</div></div><div><h3>Methods</h3><div>Data on Hepatitis E cases in Jiangsu Province were sourced from the National Notifiable Disease Reporting System. Joinpoint regression models analyzed annual percentage changes. Age-period-cohort model decomposed and Bayesian age-period-cohort projected the trends.</div></div><div><h3>Results</h3><div>Between 2007 and 2021, a total of 46180 cases of Hepatitis E were reported. Both the overall and sex-specific trends revealed a single inflection point, and the average annual percentage change was -3.63% (95% CI: -7.33% ∼ -0.87%, <em>P</em> &lt; 0.05) for male. The net drift value is -5.13%, with -6.28% for males and -2.39% for females. Significant local drift variations were observed, especially in the 20–24 age group (-11.51%). The age curve indicated the peak at 15.94 per 100000 for males in the 25–29 age group and at 4.42 per 100000 for females in the 50–54 age group. The period effect demonstrated the incidence rates for females lagged behind for males. The cohort effect indicated earlier cohorts exhibited higher incidence rates. projected an increase in incidence rates for the 65–69 age group from 2022 to 2031, with a overall incidence rate of 11.31 (95% CI: 2.80 ∼ 31.58) per 100000 in 2031.</div></div><div><h3>Conclusion</h3><div>Hepatitis E incidence has decreased from 2007 to 2021 for male in Jiangsu Province, and Age-period-cohort analysis revealed sex differences, which may be associated with different exposure routes. Continuous surveillance and timely interventions are essential to 65–69 age group.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1093-1102"},"PeriodicalIF":8.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mathematical insights into mumps transmission control with optimal strategies","authors":"Stephen Edward,&nbsp;Alberto Kimbuya Mathias","doi":"10.1016/j.idm.2025.06.007","DOIUrl":"10.1016/j.idm.2025.06.007","url":null,"abstract":"<div><div>In this study, we develop an optimal control framework for managing mumps infections through a dynamic model that integrates public health interventions such as awareness programs, isolation protocols, and a two-dose immunization regimen. We begin by establishing the model's fundamental analytical properties, including the existence and stability of disease equilibria, the positivity and boundedness of solutions, and a threshold condition for disease transmission. Local stability analysis is conducted via the Routh-Hurwitz criteria, ensuring robust insights into the disease dynamics. The optimal control problem is formulated and analyzed using Pontryagin's Maximum Principle, which facilitates the derivation of optimal interventions. Numerical simulations are conducted to assess various control strategies and compare the effectiveness of single and combined interventions. Our results indicate that a balanced solution is key to effective disease mitigation. A comprehensive approach employing all four controls: awareness, isolation, primary and booster vaccination, is the most effective strategy. Moreover, strategies that incorporate vaccination consistently outperform those without. Interestingly, a three-control strategy closely approximates the effectiveness of the full four-control intervention, suggesting a cost-effective alternative for practical implementation. While the four-control strategy may incur higher implementation costs, the three-control strategy offers a balanced solution, achieving substantial disease reduction while optimizing resource allocation. Our findings underscore the crucial role of vaccination in mumps control. They offer valuable insights for policymakers, emphasizing the need to balance economic considerations with public health outcomes. Vaccination, as our study demonstrates, is a cornerstone of any effective mumps control strategy.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1208-1228"},"PeriodicalIF":8.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wonder drugs and where to use them: a forecast of ivermectin's impact on malaria in Africa","authors":"Scott Greenhalgh ,&nbsp;Ahmani Roman ,&nbsp;Ashley Provencher","doi":"10.1016/j.idm.2025.06.003","DOIUrl":"10.1016/j.idm.2025.06.003","url":null,"abstract":"<div><div>A study in Burkina Faso revealed ivermectin inhibits malaria transmission by killing malaria parasites and mosquitoes. However, it is unknown what effect this drug will have on the malaria transmission intensities of the rest of sub-Saharan Africa (SSA). To address this issue, we created a mathematical model using malaria transmission data from 41 SSA countries to evaluate the antimalarial benefits of a mass drug administration (MDA) of ivermectin. To account for ivermectin's effect on malaria, we incorporate estimates of its ability to inhibit malaria transmission and kill mosquitoes. We consider scenarios where 0, 12.5 %, 25.0 %, and 50.0 % of the population receive ivermectin over five years and estimate malaria incidence averted, disability-adjusted life years saved, and the incremental cost-effectiveness ratio. Our findings show that an MDA of ivermectin to 12.5 %, 25 %, or 50 % of the population annually averts 248.7, 261.4, and 288.7 incidences per thousand people and saves 5.4, 5.7, and 6.3 disability-adjusted life years, respectively. These values indicate that an MDA of ivermectin would be cost-effective in 41, 18, and 6 countries, and very cost-effective in 22, 6, and 3 countries for the 12.5 %, 25 %, and 50 % scenarios. Altogether, our results indicate that ivermectin would prevent a substantial number of malaria incidences and save disability-adjusted life years in the majority of SSA. Therefore, an MDA of ivermectin would greatly aid in ongoing malaria control efforts and should be considered strongly as a complementary intervention to current malaria protocols.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1229-1237"},"PeriodicalIF":8.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A statistical model for forecasting probabilistic epidemic bands for dengue cases in Brazil","authors":"Laís Picinini Freitas ,&nbsp;Danielle Andreza da Cruz Ferreira ,&nbsp;Raquel Martins Lana ,&nbsp;Daniel Cardoso Portela Câmara ,&nbsp;Tatiana P. Portella ,&nbsp;Marilia Sá Carvalho ,&nbsp;Ayrton Sena Gouveia ,&nbsp;Iasmim Ferreira de Almeida ,&nbsp;Eduardo Correa Araujo ,&nbsp;Luã Bida Vacaro ,&nbsp;Fabiana Ganem ,&nbsp;Oswaldo Gonçalves Cruz ,&nbsp;Flávio Codeço Coelho ,&nbsp;Claudia Torres Codeço ,&nbsp;Luiz Max Carvalho ,&nbsp;Leonardo Soares Bastos","doi":"10.1016/j.idm.2025.07.014","DOIUrl":"10.1016/j.idm.2025.07.014","url":null,"abstract":"<div><div>Dengue is a vector-borne disease and a major public health concern in Brazil. Its continuing and rising burden has led the Brazilian Ministry of Health to request for modelling efforts to aid in the preparedness and response to the disease. In this context, we propose a Bayesian forecasting model based on historical data to predict the number of cases 52 weeks ahead for the 118 health districts of Brazil. We leverage the predictions to build probabilistic epidemics bands to be used for dengue monitoring. We define four disjoint probabilistic bands (≤50% (50%, 75%] (75%, 90%], and <span><math><mo>&gt;</mo></math></span>90%), based on the percentiles of the predicted cases distribution and interpreted according to the historical number of cases and past occurrence probability (below the median, typical; moderately high, fairly typical; fairly high, atypical; exceptionally high, very atypical). We performed out-of-sample validation for 2022–2023 and 2023–2024 and forecasted 2024–2025. In the 2022–2023 and 2023–2024 seasons, the epidemic bands followed the observed cases’ curve shape, with a sharp increase after January and a decline after the peak around April. In 2022–2023, the observed number of cases (1,436,034) was slightly above the estimated 75% percentile (1,405,191), being classified as “fairly high, atypical”. Most health districts in South Brazil showed exceptionally high numbers of cases during this season. The situation worsened in 2023–2024 and the observed number of cases (6,454,020) was way above the 90% percentile (2,221,557), characterising an “exceptionally high, very atypical” season. For the 2024–2025 season, we estimated a median number of cases of 1,526,523 (maximum value for the “below the median, typical” probabilistic epidemic band. The maximum estimated values for the upper bands were 2,213,282 (moderately high, fairly typical) and 3,803,898 (fairly high, atypical) with the upper limits of the probabilistic epidemic bands of 1,452,359. Probabilistic epidemic bands serve as a valuable monitoring tool by enabling prospective comparisons between observed case curves and historical epidemic patterns, facilitating the assessment of ongoing outbreaks about past occurrences.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1479-1487"},"PeriodicalIF":2.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144813861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic modelling of viral infection spread via a Partial Integro-Differential Equation","authors":"Manuel Pájaro ,&nbsp;Irene Otero-Muras ,&nbsp;Carlos Vázquez","doi":"10.1016/j.idm.2025.07.005","DOIUrl":"10.1016/j.idm.2025.07.005","url":null,"abstract":"<div><div>In the present article we propose a Partial Integro-Differential Equation (PIDE) model to approximate a stochastic SIS compartmental model for viral infection spread. First, an appropriate set of reactions is considered, and the corresponding Chemical Master Equation (CME) that describes the evolution of the reaction network as a stochastic process is posed. In this way, the inherent stochastic behaviour of the infection spread is incorporated in the modelling approach. More precisely, by considering that infection is propagated in bursts we obtain the PIDE model as the continuous counterpart to approximate the CME. In this way, the model takes into account that one infectious individual can be in contact with more than one susceptible person at a given time. Moreover, an appropriate semi-Lagrangian numerical method is proposed to efficiently solve the PIDE model. Numerical results and computational times for CME and PIDE models are compared and discussed. We also include a comparison of the main statistics of the PIDE model with the deterministic ODE model. Moreover, we obtain an analytical expression for the stationary solution of the proposed PIDE model, which also allows us to study the disease persistence. The methodology presented in this work is also applied to a real scenario as the COVID-19 pandemic.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1252-1269"},"PeriodicalIF":8.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global stability for a cumulative release Ebola epidemic model from the corpses and infected individuals","authors":"Ning Wang ,&nbsp;Long Zhang ,&nbsp;Yantao Luo ,&nbsp;Zhidong Teng","doi":"10.1016/j.idm.2025.07.002","DOIUrl":"10.1016/j.idm.2025.07.002","url":null,"abstract":"<div><div>In this paper, a SVEIRDP epidemic model is proposed to investigate the transmission dynamics of Ebola by cumulative release from the infected individuals and corpses in the form of infinite integrals. First, the positivity and ultimate boundedness of solutions are proved. Second, the basic reproduction number <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> is calculated. Furthermore, it is proven that if <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>&lt;</mo><mn>1</mn></math></span>, the model has the disease-free equilibrium and is globally asymptotically stable (GAS); If <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>&gt;</mo><mn>1</mn></math></span>, the unique endemic equilibrium is GAS. To clearly illustrate the theoretical results, real data are used to conduct numerical simulations. We discover that modeling the cumulative release of Ebola from the infected individuals and corpses using the infinite integral with an appropriate probability density function (PDF) provides a more realistic and accurate representation of the actual disease spread.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1291-1306"},"PeriodicalIF":8.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144632014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of human papillomavirus model with vaccination and individual heterogeneity","authors":"Jing An ,&nbsp;Wenhui Hao ,&nbsp;Huifen Guo ,&nbsp;Juping Zhang","doi":"10.1016/j.idm.2025.08.001","DOIUrl":"10.1016/j.idm.2025.08.001","url":null,"abstract":"<div><div>The dynamic system of HPV transmission with age subgroups, sexual and nonsexual transmission is established based on HPV vaccination. Firstly, the transmission threshold <em>R</em>₀ of the system is given. Local asymptotically stabilization of disease-free equilibrium when <em>R</em>₀ &lt; 1 is proved. It is proved that there is a positive equilibrium and disease persistence in the system when <em>R</em>₀ &gt; 1. Secondly, parameters estimation of the system is carried out based on the data from Chinese STD surveillance sites using the least square method. Finally, optimal control theory is applied to the system, the existence of optimal control is proved, and Pontryagin maximum principle is utilized to find optimal control strategy, and the spread of human papillomavirus in different age groups is predicted. The results show that for different age groups, vaccination of 16–45 years old is more beneficial to HPV control than vaccination of 9–15 years old, and that for different control costs, low-cost control is more advantageous.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1533-1574"},"PeriodicalIF":2.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of vaccination strategies in a heterosexual HPV transmission model with a case study in Xinjiang of China","authors":"Ramziya Rifhat ,&nbsp;Shayidan Abuduwaili ,&nbsp;Zhidong Teng ,&nbsp;Kai Wang","doi":"10.1016/j.idm.2025.06.004","DOIUrl":"10.1016/j.idm.2025.06.004","url":null,"abstract":"<div><div>Vaccination has confirmed efficacy in preventing human papillomavirus (HPV) infection. The inclusion of males in vaccination programs remains a subject of debate, and the optimal allocation of vaccines across genders for maximizing benefits remains unclear. This work proposes a heterosexual HPV transmission model with vaccination and employs the data from Xinjiang of China, as a case study to assess HPV vaccination strategies. The dynamics of the model, including the nonnegativity and boundedness of solutions, the calculation of the basic reproduction number (BRN), the stability of disease-free equilibrium, and the uniform persistence of disease, are investigated. Theoretical findings highlight the decisive role of the BRN in determining model dynamics. Furthermore, the optimal vaccine distribution strategy between males and females was established when the vaccine amount is limited. Meanwhile, this work involves fitting and estimating parameters and the current BRN based on actual data regarding with HPV infection and secondary cervical cancer (CC) cases in Xinjiang from January 2009 to December 2019. The numerical simulations are employed to explore the sensitivity of model parameters, especially the vaccination rates, to the BRN and HPV infection and CC with time changes, discuss the impact of vaccine distribution between males and females on the dynamic changes in new cases of HPV infection and CC, and further analyzed the control effect of bivalent and nine-valent HPV vaccines in Xinjiang of China. Additionally, several practical strategies are introduced to manage the continued spread of HPV infection and CC in the region.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1153-1178"},"PeriodicalIF":8.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}