Infectious Disease Modelling最新文献

{"title":"Reinforcement learning-based event-driven optimal prevention control strategy for citrus huanglongbing model","authors":"Yongwei Zhang ,&nbsp;Xiaoling Deng ,&nbsp;Yubin Lan","doi":"10.1016/j.idm.2025.07.007","DOIUrl":"10.1016/j.idm.2025.07.007","url":null,"abstract":"<div><div>Citrus Huanglongbing (HLB) is an infectious disease transmitted by Asian citrus psyllids (ACP), which leads to serious economic losses in the citrus industry. Therefore, it is crucial to investigate the prevention and control strategy of citrus HLB. In this paper, the dynamics of HLB propagation between citrus trees and ACP is considered. By applying reinforcement learning (RL) technique, an event-driven optimal prevention control (EDOPC) strategy is developed to ensure the HLB propagation model state converges to a disease-free equilibrium point. Initially, in order to address the challenge of obtaining precise models in practice, a radial basis function-based event-driven observer is built by adopting system input-output data to obtain the approximate HLB propagation model. Subsequently, an EDOPC strategy is devised, which updates only at triggering times to reduce management costs. Additionally, a single critic network structure is constructed to obtain the solution of the Hamilton-Jacobi-Bellman equation, thereby deriving an approximate EDOPC strategy. To align with real-world scenarios, the weights of the observer and the critic network are updated only at event occurrence times. Moreover, by employing the Lyapunov stability principle, the critic network weight error is proved to be uniformly ultimately bounded under the novel event-driven weight adjusting law. Finally, simulation experiments confirm the efficacy of the present RL-based EDOPC strategy.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1334-1354"},"PeriodicalIF":8.8,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680677","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 discrete SIR epidemic model incorporating media impact, resource limitaions and threshold switching strategies","authors":"Wenjie Qin ,&nbsp;Shan Zhang ,&nbsp;Yi Yang ,&nbsp;Jiamin Zhang","doi":"10.1016/j.idm.2025.07.006","DOIUrl":"10.1016/j.idm.2025.07.006","url":null,"abstract":"<div><div>The paper explores the effects of media influence and limited medical resources on the spread of infectious diseases using mathematical modeling. We construct a switching epidemic model that incorporates a media influence factor, an inoculation function, and a cure function. This model is subsequently discretized and studied via Euler's method. The number of susceptible individuals serves as the switching threshold, determining when media influence and healthcare resources intervene. By conducting an in-depth analysis of the equilibria of two subsystems, we have not only demonstrated the existence and stability conditions of the equilibria but also proposed the flip bifurcation theory for <span><math><msub><mrow><mi>S</mi></mrow><mrow><msub><mrow><mi>G</mi></mrow><mrow><mn>1</mn></mrow></msub></mrow></msub></math></span>. Through single-parameter bifurcation analysis, we identify complex dynamic behaviors such as stability, periodicity, and chaos, and examined the impact of key parameters on these dynamics. We also compared the dynamic behaviors of the discrete and continuous models. Additionally, we delve into the interaction between initial populations of susceptible and infected individuals and its effect on outbreak outcomes, as well as the coexistence of attractors. Our research sheds light on the intricate relationship between media influence, constrained medical resources, and infectious disease propagation, offering recommendations for disease control and intervention approaches.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1270-1290"},"PeriodicalIF":8.8,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623480","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":"Should public health policy exempt cases with low viral load from isolation during an epidemic?: a modelling study","authors":"Jiahao Diao ,&nbsp;Rebecca H. Chisholm ,&nbsp;Nicholas Geard ,&nbsp;James M. McCaw","doi":"10.1016/j.idm.2025.07.003","DOIUrl":"10.1016/j.idm.2025.07.003","url":null,"abstract":"<div><div>As demonstrated during the COVID-19 pandemic, non-pharmaceutical interventions, such as case isolation, are an important element of pandemic response. The overall impact of case isolation on epidemic dynamics depends on a number of factors, including the timing of isolation relative to the onset of contagiousness for each individual instructed to isolate by public health authorities. While there is an extensive literature examining the importance of minimising the delay from exposure to direction to isolate in determining the impact of case isolation policy, less is known about how underlying epidemic dynamics may also contribute to that impact. Empirical observation and modelling studies have shown that, as an epidemic progresses, the distribution of viral loads among cases changes systematically. In principle, this may allow for more targeted and efficient isolation strategies to be implemented. Here, we describe a multi-scale agent-based model developed to investigate how isolation strategies that account for cases viral loads could be incorporated into policy. We compare the impact and efficiency of isolation strategies in which all cases, regardless of their viral load, are required to isolate to strategies in which some cases may be exempt from isolation. Our findings show that, following the epidemic peak, the vast majority of cases identified with a low viral load are in the declining phase of their infection and so contribute less to overall contagiousness. This observation prompts the question about the potential public health value of discontinuing isolation for such individuals. Our numerical investigation of this ‘adaptive’ strategy shows that exempting individuals with low viral loads from isolation following the epidemic peak leads to a modest increase in new infections. Surprisingly, it also leads to a <em>drop</em> in efficiency, as measured by the average number of infections averted per isolated case. Our findings therefore suggest caution in adopting such flexible or adaptive isolation policies. Our multi-scale modelling framework is sufficiently flexible to enable extensive numerical evaluation of more complex isolation strategies that incorporate more disease-specific biological and epidemiological features, supporting the development and evaluation of future public health pandemic response plans.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1307-1321"},"PeriodicalIF":8.8,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634014","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 spatiotemporal transmission simulator for respiratory infectious diseases and its application to COVID-19","authors":"Tao Shi ,&nbsp;Jiaxuan Huan ,&nbsp;Zuo Zhang ,&nbsp;Liqun Fang ,&nbsp;Yong Zhang","doi":"10.1016/j.idm.2025.07.001","DOIUrl":"10.1016/j.idm.2025.07.001","url":null,"abstract":"<div><div>The present study introduces a transmission dynamic simulator for respiratory infectious diseases by incorporating human movement data into a spatiotemporal transmission model. The model spatially divides areas into multiple patches according to administrative regions. The transmission of respiratory pathogens within each patch is depicted using an improved Susceptible-Exposed-Infectious-Removed (SEIR) compartmental framework, which incorporates quarantine and isolation measures. The risk of transmission between patches is determined by a gravity-constrained model that considers passenger volume and the spatial distance between patches. We simulate changes in intervention policies and detection methods by adjusting quarantine and detection rates at different stages of the epidemic, thereby capturing spatial variations in pathogen transmission through altering the transmission rate. Ultimately, we apply this simulator to accurately replicate the spatiotemporal dynamics observed during the initial COVID-19 outbreak across all 31 provinces in the mainland of China, successfully capturing the temporal variations in both case numbers and affected provinces. Additionally, it demonstrates a remarkable level of accuracy in predicting the outbreak of epidemic in each province.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1322-1333"},"PeriodicalIF":8.8,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655457","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":"2025-07-07","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":"2025-07-07","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":"Transmission of respiratory infectious diseases based on real close contact behavior in an emergency room","authors":"Bing Cao,&nbsp;Haochen Zhang,&nbsp;Nan Zhang","doi":"10.1016/j.idm.2025.07.004","DOIUrl":"10.1016/j.idm.2025.07.004","url":null,"abstract":"<div><h3>Background</h3><div>The risk of transmission of respiratory infectious diseases in emergency rooms is high, posing a severe threat to the health of healthcare workers (HCWs).</div></div><div><h3>Methods</h3><div>The study was conducted in an emergency room of a medical school at a university in Hong Kong during a clinical skills competition. A total of 19,246 s of video surveillance data were collected, recording the treatment of three types of patients (P1: infusion patient, P2: critically ill patient, P3: agitated patient). Taking coronavirus disease 2019 (COVID-19) as an example, a multi-route transmission model was established to assess the infection risk for HCWs and the effectiveness of various interventions.</div></div><div><h3>Results</h3><div>The average distances between HCWs and patients during the treatment of P1, P2, and P3 were 0.8 (25–75 percentile: 0.6, 1.1) m, 1.0 (0.8, 1.2) m, and 0.5 (0.4, 0.7) m, respectively. When treating P2, due to intubation procedures, the hourly risk of infection was highest at 43.4 % if no HCWs wore masks, which was 5.1 and 3.1 times higher than it during treatment of P1 (8.5 %) and P3 (13.9 %), respectively. During the treatment, without mask protection, the average hourly infection risk for nurses was 11.0 % (P1), 41.2 % (P2), and 16.8 % (P3), which was 1.8 times (P1), 0.9 times (P2), and 1.5 times (P3) that of doctors. If HCWs wear N95 respirators and surgical masks throughout, the total infection risk can be reduced by 94.7 % and 53.9 %, respectively. Increasing the ventilation rate from 1 ACH to 6 ACH reduced the infection risk through long-range airborne transmission by 43.8 % (P1), 36.1 % (P2), and 31.6 % (P3), with a total infection risk reduction of 2.4 % (P1), 5.6 % (P2), and 1.6 % (P3), respectively.</div></div><div><h3>Conclusions</h3><div>The findings of the study provide a scientific support for the precise prevention and control of respiratory infectious diseases under different treatments in emergency rooms.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1238-1251"},"PeriodicalIF":8.8,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605187","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 Neisseria meningitidis transmission dynamics and the impact of pentavalent vaccination targeting serogroups A, C, W-135, Y, and X in the African meningitis belt","authors":"Nafiu Hussaini ,&nbsp;Abdulrazaq G. Habib ,&nbsp;Iliyasu Garba ,&nbsp;Isa A. Baba ,&nbsp;Andrés Colubri ,&nbsp;Ismail Abdulrashid ,&nbsp;Salihu S. Musa","doi":"10.1016/j.idm.2025.06.008","DOIUrl":"10.1016/j.idm.2025.06.008","url":null,"abstract":"<div><div>The African meningitis belt (AMB) faces recurring epidemics of <em>Neisseria meningitidis</em> (Nm) (a bacterium that causes meningococcal meningitis), posing significant public health challenges. This study develops a Susceptible-Carrier-Infected-Recovered (SCIR)-based dynamic model to investigate Nm transmission dynamics in the AMB region, focussing on the impact of pentavalent meningococcal conjugate vaccines targeting serogroups A, C, W-135, Y, and X. By incoporating vaccination strategies into the model, we provide a comprehensive framework for evaluating vaccine effectiveness and informing outbreak prevention and control efforts. Our model stratifies the population into high-risk individuals (ages 1–29 years), who are the primary targets of vaccination campaigns, and low-risk individuals (all other age groups), capturing differences in susceptibility and vaccine coverage. Our results reveal that the introduction of pentavalent vaccines significantly reduces the prevalence of carriers, particularly among high-risk groups, thereby curbing transmission and mitigating epidemic risks across the AMB region. Key epidemiological parameters, including reproduction numbers (<em>R</em>_<em>0</em>), are derived to support targeted intervention strategies. Further analysis highlights the role of vaccination in lowering Nm transmissibility, especially in densely populated settings where close contact accelerates spread. Moreover, potential drivers of Nm outbreaks, including climate variability, socioeconomic disparities, and population density, are identified, highlighting the need for integrated public health intervention strategies. Further simulations also reveal the effectiveness of pentavalent vaccination among high-risk populations; however, further research is urgently needed to understand disease heterogeneity and vulnerability, particularly in young children and underserved communities. Thus, this study contribute to advancing our understanding of effective and sustainable vaccination strategies and enhancing epidemic preparedness in meningitis-endemic regions.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1355-1383"},"PeriodicalIF":8.8,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144694676","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":"2025-06-30","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":"Development of two-dimension epidemic prediction model","authors":"Jianping Huang ,&nbsp;Wei Yan ,&nbsp;Han Li ,&nbsp;Shujuan Hu ,&nbsp;Zihan Hao ,&nbsp;Licheng Li ,&nbsp;Xinbo Lian ,&nbsp;Danfeng Wang","doi":"10.1016/j.idm.2025.06.009","DOIUrl":"10.1016/j.idm.2025.06.009","url":null,"abstract":"<div><div>Epidemic prediction is a crucial foundation of disease control policy-making. Owing to the high population connectivity of current epidemics, it is essential to capture the spatial transmission of infectious diseases. However, most models currently used in epidemic prediction are single-point models, and they can only capture the time-dynamic increase of cases in limited areas. In this study, we develop a two-dimension epidemic prediction model by introducing diffusion processes, which take spatial transmission epidemics into account. We utilize mathematical theorems to prove a well-posed solution of the model. In addition, we also consider various influencing factors that affect the spread of epidemics, and introduce multiple parameterization schemes. Results suggest that this two-dimension model provides more precise predict the spatial and temporal distribution of confirmed cases. The regional average prediction score of COVID-19 in July 2022 in Lanzhou is 76.5 % and COVID-19 from May 1st to May 31st, 2023 in China is 70.7 %,respectively. Our results offer a scientific foundation for further study on the prediction of spatial epidemics, which contributes to an in-depth understanding of epidemic dynamics and provides valuable reference for the formulation of public health strategies and policies.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1190-1207"},"PeriodicalIF":8.8,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534925","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}