Infectious Disease Modelling最新文献

{"title":"An age-structured mathematical model to assess the combined effects of vaccine and non-vaccine interventions on malaria transmission and burden","authors":"Romain Glèlè Kakaï,&nbsp;Ludosky Crédo Djomatin","doi":"10.1016/j.idm.2025.10.007","DOIUrl":"10.1016/j.idm.2025.10.007","url":null,"abstract":"<div><div>Malaria remains a significant public health problem, particularly in sub-Saharan Africa, where its burden remains a concern despite existing control measures. Recent advances in vaccination, particularly with <em>RTS</em>, <em>S</em> and <em>R</em>21, offer new opportunities to mitigate malaria transmission and disease severity. In this study, we develop an age-structured mathematical model to assess the combined effects of vaccination and non-vaccine interventions on malaria transmission dynamics. The model integrates demographic parameters, long-lasting insecticide-treated nets (LLIN), access to treatment for clinical cases, vaccine efficacy profiles, and waning immunity to simulate disease burden in age cohorts over a long-term period. Our approach enables a comparative assessment of projected malaria transmission rates, disease burden, and disability-adjusted life years (DALYs) under different vaccination scenarios. For application purposes, the model is calibrated using national-level demographic data for a low transmission setting (Ethiopia) and a high transmission setting (Nigeria). Preliminary findings suggest that the integration of vaccination with existing malaria control strategies could significantly reduce malaria incidence and mortality over time. This study provides valuable insights into optimizing vaccination strategies and guiding public health policies aimed at long-term malaria control in endemic regions.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 355-376"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519783","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 compartmental model of variant coexistence, dynamics and dominance in infectious diseases: Case for SARS-CoV-2 in Abu Dhabi","authors":"Mauricio Patón ,&nbsp;Mireille Hantouche ,&nbsp;Farida Al-Hosani ,&nbsp;Amrit Sadani ,&nbsp;Jorge Rodríguez ,&nbsp;Rowan Abuyadek","doi":"10.1016/j.idm.2025.10.006","DOIUrl":"10.1016/j.idm.2025.10.006","url":null,"abstract":"<div><div>In recent years, the rapid mutation of SARS-CoV-2 has led to the emergence of new variants. Despite advancements in pandemic control, these new variants could pose substantial public health issues. This study introduces a comprehensive compartmental model that can handle multiple virus variants and population groups. The model also factors the influence of international visitors, per variant and group, on the population, which is pertinent for populations with a high ratio of incoming travellers. The model was applied to simulate the coexistence of different variants in the Emirate of Abu Dhabi from August 2022 until March 2023. Calibration was conducted using the data available from Abu Dhabi health authorities and international data from GISAID to estimate the prevalence of each variant. The model seems to effectively depict the temporal coexistence of multiple strains and, ultimately, the rise of a dominant variant. The simulation results from Abu Dhabi indicate that the XBB variant became the dominant strain by the end of the simulation period. The calibrated parameters for the XBB variant suggest that its dominance can be attributed to its superior ability to evade immunity and its increased infectiousness, estimated to be approximately 15 % more than the BQ.1 variant. The introduction of the XBB variant through infected visitors further amplified its emergence.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 310-324"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466633","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":"Travel-related importation risk of mpox from Hong Kong to Shenzhen in 2023: A modeling study","authors":"Ruohan Chen ,&nbsp;Jia Wan ,&nbsp;Dongfeng Kong ,&nbsp;Cong Niu ,&nbsp;Zengyang Shao ,&nbsp;Chijun Zhang ,&nbsp;Mingda Xu ,&nbsp;Yuan Bai ,&nbsp;Eric Lau ,&nbsp;Zhen Zhang ,&nbsp;Zhanwei Du","doi":"10.1016/j.idm.2025.09.005","DOIUrl":"10.1016/j.idm.2025.09.005","url":null,"abstract":"<div><div>Mpox, a viral zoonotic disease formerly known as monkeypox, has gained global attention following a multi-country outbreak in 2022-23, primarily linked to close intimate contact. In China, mpox cases surged in June 2023, with nearly a quarter of new cases concentrated in Guangdong Province, particularly Shenzhen. This study aimed to estimate the importation risk of mpox cases from Hong Kong to Shenzhen in 2023, utilizing cross-regional population mobility data from January to October 2023. The analysis focused on local transmission in Hong Kong and the probability of mpox importation into Shenzhen. Results revealed a significant importation risk, with over a 50 % chance of at least one travel-based mpox case from Hong Kong in June 2023. The study underscores the necessity of enhancing inbound surveillance for travelers from high mpox prevalence regions. It is suggested that regional governments implement tailored strategies, including enhanced surveillance and dynamic risk assessment for effective cross-border disease management, supported by robust monitoring and coordinated actions across jurisdictions.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 185-190"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267449","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":"Application of the type and target reproduction numbers to the evaluation of the influence of each prefecture in Japan on the disease spread","authors":"Toshikazu Kuniya","doi":"10.1016/j.idm.2025.09.003","DOIUrl":"10.1016/j.idm.2025.09.003","url":null,"abstract":"<div><div>In this study, by applying population mobility data in July, August and September of 2019–2023 in Japan to a multigroup epidemic model, we calculate the type and target reproduction numbers of each prefecture in Japan. Regarding these values as a kind of network centrality measure, we discuss which prefectures are influential on the disease spread in Japan. We show that the values of the type reproduction number are relatively high in 10 prefectures consisting of Hokkaido, Saitama, Chiba, Tokyo, Kanagawa, Aichi, Kyoto, Osaka, Hyogo and Fukuoka. In particular, by calculating the target reproduction number, we show that Tokyo and Kyoto could be the most influential on the disease spread, and the population mobility between the Kanto and Kansai regions could be the key factor for the nationwide epidemic in Japan.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 143-149"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097457","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":"COVID-19, infection fatality rate (IFR) implied by the serology, antibody, testing in New York City","authors":"Linus Wilson","doi":"10.1016/j.idm.2025.10.004","DOIUrl":"10.1016/j.idm.2025.10.004","url":null,"abstract":"<div><div>This paper estimates COVID-19 infection fatality rate (IFR) in early 2020 before pharmaceutical interventions were available on a large population in the United States. The better estimates of COVID-19 deaths in New York City and its high COVID-19 infection rate made it ideal to accurately estimate the IFR. Further, we analyze the deaths and infections in New York City to estimate an overall IFR for the United States of 0.86 percent.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 303-309"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145462892","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":"Novel approach to extract epidemiological information from waves in epidemic's profiles","authors":"Juan Campos ,&nbsp;Maria C.A. Leite","doi":"10.1016/j.idm.2025.08.003","DOIUrl":"10.1016/j.idm.2025.08.003","url":null,"abstract":"<div><div>In this paper, we develop a novel mathematical framework based on the Kermack- McKendrick model to extract epidemiological parameters from real temporal profiles consisting of waves. The approach's key feature is the ability to obtain all model parameters from the geometry of the wave of interest.</div><div>We propose three new quantities to measure the negative impact of the epidemic wave on a specific population, called <em>Fraction of endemicity</em>, <em>Severity</em>, and <em>Asymmetry</em>. These three measures, along with a refined definition of the <em>basic reproduction number</em>, provide crucial epidemiological information.</div><div>We demonstrate analytically that there is an equivalence among these quantities, and such equivalence gives a way of obtaining all parameters in the model since the <em>Asymmetry</em> of a real epidemic wave is easily computed. This is the heart of the novel methodology we introduce. The framework is suitable for public health decision support, as its implementation does not rely on complex mathematical tools.</div><div>We present several case studies to illustrate the simplicity of the framework as well as the distinct aspects of its implementation. In all examples investigated, the numeric solution obtained with the parameterized model shows good agreement with the available data.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 87-106"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047954","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":"HIV/AIDS hidden transmission model with HIV testing and contact tracing in an SID community","authors":"Huiling Ouyang ,&nbsp;Fengying Wei ,&nbsp;Zhen Jin ,&nbsp;Jianfeng Xie","doi":"10.1016/j.idm.2025.10.010","DOIUrl":"10.1016/j.idm.2025.10.010","url":null,"abstract":"<div><div>HIV testing and contact tracing facilitate early detection of HIV/AIDS infections for interrupting the hidden transmission. In this study, a susceptible-undiagnosed-diagnosed transmission model with testing and contact tracing is proposed in heterosexual and homosexual populations. The basic reproduction number, the heterosexual-transmission and homosexual-transmission reproduction numbers of the transmission model are derived by the next generation matrix method. The optimal-fitting results present that the basic reproduction number of Fujian 2012–2022 HIV/AIDS epidemics ranges from 1.93 to 2.74 by phases, which is consistent with the heterosexual-transmission reproduction number. The optimal fittings and the global sensitivity analysis show that the transmission risk mainly originates from the heterosexual contacts. The transmission risk assessments and the 2023–2035 tendency predictions are performed for HIV/AIDS prevalence in Fujian Province by scenarios. The numerical simulation results point out that the decrease of female-to-male transmission rate, the decline of proportion of active diagnosed population, and the reduction of the awareness delay, are the main contributors for declining HIV/AIDS prevalence. The 2023–2035 tendency predictions of Fujian Province reveal that, when the awareness delay is fixed, the rising trends of the infection scales caused by the transmission rates are more significant than those caused by the proportion of active diagnosed population. According to the transmission risk assessments and the tendency prediction results, several suggestions are provided to the policymakers for curbing the HIV/AIDS transmission in Fujian Province.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 325-337"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466632","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":"Applications and reporting of causal inference modelling in infectious disease studies: A systematic review","authors":"Yukiko Ezure ,&nbsp;Mark Chatfield ,&nbsp;David L. Paterson ,&nbsp;Lisa Hall","doi":"10.1016/j.idm.2025.09.006","DOIUrl":"10.1016/j.idm.2025.09.006","url":null,"abstract":"<div><div>Causal inference is increasingly employed in infectious disease (ID) epidemiology. Despite the increasing adoption of causal inference methods in infectious disease research, there has been no comprehensive review of their implementation trends, estimation approaches, and key specifications. A systematic examination of how these methods were being applied in practice could identify both successful strategies and common pitfalls. This systematic review aimed to describe the usage and reporting of causal methods in observational ID studies. The applications of causal methods in the analyses of ID observational data were identified from systematic searches of PubMed, Medline, Web of Science, and Scopus. Our analysis focused on detailing the adoption trends of causal inference methods and assessing the comprehensiveness of their reporting and publication between 2010 and 2023. Of the 172 studies, the majority utilised propensity score-based methods (n = 133, 77 %). We identified only 39 studies that explicitly described the use of causal frameworks and employed variations of causal analyses. The most common reason for using causal methods was to address time-varying variables that are prominent in ID research. Consequently, a common approach used was inverse probability treatment weighting with the marginal structural model; additionally, targeted maximum likelihood estimation has become popular in minimising bias.</div><div>There is substantial variation in reporting causal methods in ID research. Development of reporting guidelines is needed for clear reporting alongside training on how to use and appraise applications of causal inference in observational ID research. This is particularly important for ID modelling, where time-varying factors and complex transmissions and dynamics of treatment often necessitate complex modelling approaches.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 165-184"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221362","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":"Feasibility of eliminating adult hepatitis B in Guangdong by 2030: A modeling study","authors":"Ning Sun ,&nbsp;Xiaoping Shao ,&nbsp;Chen Hou ,&nbsp;Xiaowen Wei ,&nbsp;Weizhao Lin ,&nbsp;Ying Yang ,&nbsp;Liang Chen ,&nbsp;Chitin Hon ,&nbsp;Guanghu Zhu ,&nbsp;Jiufeng Sun ,&nbsp;Limei Sun","doi":"10.1016/j.idm.2025.09.008","DOIUrl":"10.1016/j.idm.2025.09.008","url":null,"abstract":"<div><h3>Objectives</h3><div>Eliminating hepatitis B remains challenging, especially in Guangdong, the region with China's highest burden. Predicting incidence, optimizing vaccination, and reducing illness are essential to meet the WHO goal of a 90 % reduction by 2030.</div></div><div><h3>Methods</h3><div>Based on the HBV surveillance data from 2005 to 2022, disease clustering patterns, correlation between vaccination and incidence were determined. A six-compartment transmission model was established and validated by estimating infectivity using nonlinear least squares and polynomial fitting.</div></div><div><h3>Results</h3><div>From 2005 to 2022, acute HBV cases in Guangdong declined from 7509 to 2,097, while chronic cases in adults aged ≥15 rose from 38,595 to 146,658. High-risk clusters remained in Guangzhou, Foshan, and Shenzhen. Infant vaccination was linked to reduced acute infections but had limited effect on chronic cases. By 2030, acute HBV infectivity is projected to reach 1872 cases, with 100,354 new chronic infections expected in adults. To meet the WHO 2030 elimination target, average recovery time for chronic carriers must be reduced from 40 years to 7.7 years. For full elimination, it should be shortened to 1.85 years.</div></div><div><h3>Conclusions</h3><div>Infant vaccination curbed acute HBV in youth, but chronic cases in adults threaten elimination goals. Scaling therapies to accelerate chronic HBV recovery is urgent.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 191-202"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267450","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":"Optimizing spatiotemporal nonpharmaceutical interventions for influenza: An adaptive reinforcement learning approach for regional heterogeneity","authors":"Yuxing Tian ,&nbsp;Xin Li ,&nbsp;Hualing Wang ,&nbsp;Heng Yuan ,&nbsp;Tao Zhang","doi":"10.1016/j.idm.2025.10.001","DOIUrl":"10.1016/j.idm.2025.10.001","url":null,"abstract":"<div><h3>Background</h3><div>Influenza remains a significant global public health challenge because of its high transmissibility, widespread circulation, and considerable societal impact. Conventional threshold-based nonpharmaceutical interventions (NPIs) provide valuable frameworks for outbreak control; however, these standardized approaches may not fully account for important regional heterogeneity. It remains difficult to weigh regional characteristics and accurately balance infection control and socioeconomic costs.</div></div><div><h3>Methods</h3><div>We propose a susceptible-exposed-infectious-quarantined-removed compartmental model-dueling deep Q-network (SEIQR-Dueling DQN) framework tailored to plains, hilly, and plateau cities. By integrating climatic, demographic, and health care resource data, the model captures regional differences in transmission and recovery dynamics. A multidimensional state space and discrete intervention set allow for the adaptive optimization of NPI strategies across varying epidemic and resource conditions. Model parameters were estimated by sequential Bayesian optimization, and bootstrap resampling was used to quantify uncertainty. In addition, the performance of the SEIQR-Dueling DQN strategy was compared with that of the threshold-based strategy in terms of the reduction in cumulative infections, peak prevalence and length of intervention periods.</div></div><div><h3>Results</h3><div>The threshold-based intervention policy reduced cumulative infections by 3.05 %–3.67 % and peak incidence by 8.26 %–12.58 % but showed limited responsiveness to regional variation, often resulting in either under- or over-control. The SEIQR-Dueling DQN framework dynamically adjusted intervention timing and combinations on the basis of local demographic structures and epidemic trends and reduced cumulative infections by 5.87 %, 5.99 %, and 5.21 % in plains, hilly, and plateau cities, respectively, while achieving peak reductions of 34.92 %, 22.23 %, and 8.12 %, respectively, with a balanced consideration of socioeconomic impact. To assess generalizability, the trained model was applied to cities with differing transmission dynamics and demonstrated consistent performance across settings.</div></div><div><h3>Conclusion</h3><div>The SEIQR-Dueling DQN framework supports tailored interventions across regions and shows promise for broader application in the management of regional heterogeneity and future emerging infectious diseases.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 203-217"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267451","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}