Infectious Disease Modelling最新文献

{"title":"Diphtheria transmission dynamics – Unveiling generation time and reproduction numbers from the 2022–2023 outbreak in Kano state, Nigeria","authors":"Raoul Kamadjeu ,&nbsp;Oyeladun Okunromade ,&nbsp;Bola Biliaminu Lawal ,&nbsp;Muzammil Gadanya ,&nbsp;Salma Ali Suwaid ,&nbsp;Eduardo Celades Blanco ,&nbsp;Ifedayo Adetifa ,&nbsp;Elizabeth A. Kelvin","doi":"10.1016/j.idm.2025.02.007","DOIUrl":"10.1016/j.idm.2025.02.007","url":null,"abstract":"<div><h3>Background</h3><div>Diphtheria, caused by Corynebacterium diphtheriae, remains a serious public health threat in areas with low vaccination coverage, despite global declines due to widespread immunization and improved clinical management. A major outbreak in Nigeria from 2022 to 2023 underscored the persistent risk in regions with inadequate vaccination. This study aims to assess the transmission dynamics of diphtheria in Kano State, the epicenter of the outbreak, by estimating key epidemiological parameters, including the generation time (GT), approximated in our study by serial interval, and effective reproduction number (Rₜ).</div></div><div><h3>Methods</h3><div>We analyzed diphtheria case-based data from Kano State, Nigeria, collected between August 18, 2022, and November 29, 2023. Generation time was approximated using serial intervals in confirmed cases within the same geographical areas. The effective reproduction number (Rₜ) was calculated using four methods: Maximum Likelihood Estimation (MLE), Exponential Growth (EG), Sequential Bayesian (SB), and Time-Dependent (TD), focusing on the period of maximum exponential growth. A sensitivity analysis was conducted to quantify the impact of uncertainties in the GT derived from our data on the estimation of Rₜ.</div></div><div><h3>Results</h3><div>Over the 469-day outbreak period, 13,899 diphtheria cases were reported, with complete data available for 9406 cases. The estimated mean generation time was 2.8 days (SD = 3.48 days), with 97% of cases having a GT of less than 21 days. The Rₜ estimates varied across methods, with the TD method producing the highest reproduction number of 2.21 during the peak growth period. Sensitivity analysis showed that Rₜ estimates increased with longer generation times. The models, except for the SB method, demonstrated a generally strong fit with the outbreak exponential growth period.</div></div><div><h3>Conclusion</h3><div>The ongoing diphtheria outbreak in Nigeria highlights the critical threat posed by declining vaccination coverage. This study provides valuable insights into the transmission dynamics of diphtheria during a prolonged and widespread outbreak, enhancing our understanding of disease spread in this context. While certain limitations may influence the interpretation of our estimates, the findings offer valuable information for future diphtheria outbreak preparedness and response in the African context.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 680-690"},"PeriodicalIF":8.8,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data fitting and optimal control strategies for HBV acute patient cases in the United States","authors":"Xuebing Chen ,&nbsp;Yong Li ,&nbsp;Nurbek Azimaqin ,&nbsp;Yan Wu ,&nbsp;Changlei Tan ,&nbsp;Xuyue Duan ,&nbsp;Yiyi Yuan","doi":"10.1016/j.idm.2025.02.004","DOIUrl":"10.1016/j.idm.2025.02.004","url":null,"abstract":"<div><div>Infection with Hepatitis B Virus (HBV) has been a serious public health issue worldwide. It caused more than one million fatalities per year. The mathematical modelling of the disease allows better understanding of the transmission of the disease and help the government policy makers to choose the best control strategies. With this inspiration, we proposed a novel dynamic model by incorporating infection-age structure to imitate the transmission of HBV, especially the age heterogeneity in horizontal and vertical (mother-to-child) transmission modes. We also discussed its impact on control measures and analyzed the dynamics of waning immunity and reinfection. We conducted sensitivity analysis to evaluate the effectiveness of each control measure. Our research concentrates on HBV acute patient cases in the United States data from Centre for Disease Control and Prevention (CDC). Our findings show that a mixed approach by including vaccination, medication and periodic health assessments can effectively control HBV transmission. Among these measures, we found that early vaccination with a single-dose vaccine of US$50 is the most cost-effective control strategy.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 660-679"},"PeriodicalIF":8.8,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interventions for SARS-CoV-2 prevention among Jailed adults: A network-based modeling analysis","authors":"Isaac Schneider ,&nbsp;Karina Wallrafen-Sam ,&nbsp;Shanika Kennedy ,&nbsp;Matthew J. Akiyama ,&nbsp;Anne C. Spaulding ,&nbsp;Samuel M. Jenness","doi":"10.1016/j.idm.2025.02.001","DOIUrl":"10.1016/j.idm.2025.02.001","url":null,"abstract":"<div><h3>Background</h3><div>Airborne pathogens present challenges in settings like jails or prisons with a high density of contacts. The state of Georgia has the highest percentage of its citizens under correctional supervision in the United States. Yet, it had slow COVID vaccine uptake among jail residents, requiring prevention also using non-pharmaceutical interventions. Using a network-based SARS-CoV-2 transmission model parameterized with data from the Fulton County Jail, this study investigates the impact of three SARS-CoV-2 prevention strategies: vaccination, contact tracing and quarantining, and jail release to reduce jail population density.</div></div><div><h3>Methods</h3><div>Social contact networks were simulated at two different overlapping network layers: cell and block. Cell-level contacts represented shared confined sleeping space, whereas block-level contacts represented shared socialization space. Contact tracing and quarantining were simulated at the cell-level or both cell- and block-levels, hereafter referred to as all-level. A reference scenario and nine intervention scenarios were simulated three hundred times to estimate the median and interquartile range (IQR) of the outcome measures. Each scenario simulated a 185-day period to measure the prolonged effects of the interventions amid a potential COVID outbreak in the jail. The cumulative incidence, number of infections averted (NIA), and percentage of infections averted (PIA) were calculated comparing interventions against a base scenario without them. For the seven scenarios involving contact tracing and quarantining, total quarantines over the simulation and the number of quarantines per day were calculated to determine the quarantine requirements. Sensitivity analyses compared the impact of jointly varying vaccination rates and contact tracing rates.</div></div><div><h3>Results</h3><div>Cell-level contact tracing alone was an ineffective intervention (3.2% PIA), but its impact increased in combination with other interventions (i.e., vaccination or increased jail release rate). The other intervention strategies each produced a PIA over 10%, with the jail release scenario producing a PIA of nearly 20% despite only resulting in a 13% reduction in the jail population. The all-level contact tracing only scenario was effective at both 50% and 100% of contacts traced, but feasibility would be limited without a reduction in the jail population.</div></div><div><h3>Conclusions</h3><div>Implementing a combination intervention approach could substantially reduce the morbidity from COVID-19 and future respiratory viruses in this jail setting while providing secondary protection to the community.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 628-638"},"PeriodicalIF":8.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid aging of influenza epidemics in China from 2005/06 to 2016/17: A population-based study","authors":"Weibo Tang ,&nbsp;Hao Lei ,&nbsp;Nan Zhang ,&nbsp;Yaojing Wang ,&nbsp;Shimeng Cai ,&nbsp;Shuyi Ji ,&nbsp;Lei Yang ,&nbsp;Mengya Yang ,&nbsp;Can Chen ,&nbsp;Shigui Yang ,&nbsp;Dayan Wang ,&nbsp;Yuelong Shu ,&nbsp;RIDPHE Group","doi":"10.1016/j.idm.2025.02.003","DOIUrl":"10.1016/j.idm.2025.02.003","url":null,"abstract":"<div><h3>Background</h3><div>China is an aging society, and the older population is at a higher risk of influenza infection and influenza-related mortality. However, there is limited knowledge regarding the aging of influenza epidemics, which is crucial for estimating the disease burden.</div></div><div><h3>Methods</h3><div>We collected weekly influenza surveillance data from 2005/06 to 2016/17, and quantified the aging of influenza-like illness (ILI) and influenza virus-positive cases in China via the mean age of the influenza cases and the proportion of individuals aged 65 and above among the influenza cases.</div></div><div><h3>Results</h3><div>On average, the mean age of ILI cases and influenza-positive cases increased by 0.52 years and 0.60 years per year, respectively, which is approximately three times the annual increase in the mean age of the population. Additionally, the proportion of individuals aged 65 and above among influenza-positive cases increased from 0.5% to 4.0%. The aging of patients infected with influenza B/Yamagata was the most rapid, with a mean age increase of 0.73 years per year, followed by those infected with influenza A (H1N1) and influenza A (H3N2). Conversely, there was no significant increase in the mean age of patients infected with influenza B/Victoria. The aging rate of influenza epidemics in southern China was significantly higher than in northern China.</div></div><div><h3>Conclusions</h3><div>Based on estimates of excess mortality due to influenza from 2010/11 to 2014/15, by 2050, the annual number of respiratory disease-related deaths associated with influenza is projected to increase 2.5-fold. This finding highlights the importance of influenza vaccination among older individuals in China.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 639-648"},"PeriodicalIF":8.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A mechanistic modeling approach to assessing the sensitivity of outcomes of water, sanitation, and hygiene interventions to local contexts and intervention factors","authors":"Andrew F. Brouwer ,&nbsp;Alicia N.M. Kraay ,&nbsp;Mondal H. Zahid ,&nbsp;Marisa C. Eisenberg ,&nbsp;Matthew C. Freeman ,&nbsp;Joseph N.S. Eisenberg","doi":"10.1016/j.idm.2025.02.002","DOIUrl":"10.1016/j.idm.2025.02.002","url":null,"abstract":"<div><div>Diarrheal disease is a leading cause of morbidity and mortality in young children. Water, sanitation, and hygiene (WASH) improvements have historically been responsible for major public health gains, but many individual interventions have failed to consistently reduce diarrheal disease burden. Analytical tools that can estimate the potential impacts of individual WASH improvements in specific contexts would support program managers and policymakers to set targets that would yield health gains. We developed a disease transmission model to simulate an intervention trial with a single intervention. We accounted for contextual factors, including preexisting WASH conditions and baseline disease prevalence, as well as intervention WASH factors, including community coverage, compliance, efficacy, and the intervenable fraction of transmission. We illustrated the sensitivity of intervention effectiveness to the contextual and intervention factors in each of two plausible disease transmission scenarios with the same disease transmission potential and intervention effectiveness but differing baseline disease burden and contextual/intervention factors. Whether disease elimination could be achieved through a single factor depended on the values of the other factors, so that changes that could achieve disease elimination in one scenario could be ineffective in the other scenario. Community coverage interacted strongly with both the contextual and the intervention factors. For example, the positive impact of increasing intervention community coverage increased non-linearly with increasing intervention compliance. With lower baseline disease prevalence in Scenario 1 (among other differences), our models predicted substantial reductions could be achieved with relatively low coverage. In contrast, in Scenario 2, where baseline disease prevalence was higher, high coverage and compliance were necessary to achieve strong intervention effectiveness. When developing interventions, it is important to account for both contextual conditions and the intervention parameters. Our mechanistic modeling approach can provide guidance for developing locally specific policy recommendations.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 649-659"},"PeriodicalIF":8.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing","authors":"Julia Bicker ,&nbsp;René Schmieding ,&nbsp;Michael Meyer-Hermann ,&nbsp;Martin J. Kühn","doi":"10.1016/j.idm.2024.12.015","DOIUrl":"10.1016/j.idm.2024.12.015","url":null,"abstract":"<div><div>Emerging infectious diseases and climate change are two of the major challenges in 21st century. Although over the past decades, highly-resolved mathematical models have contributed in understanding dynamics of infectious diseases and are of great aid when it comes to finding suitable intervention measures, they may need substantial computational effort and produce significant CO₂ emissions. Two popular modeling approaches for mitigating infectious disease dynamics are agent-based and population-based models. Agent-based models (ABMs) offer a microscopic view and are thus able to capture heterogeneous human contact behavior and mobility patterns. However, insights on individual-level dynamics come with high computational effort that scales with the number of agents. On the other hand, population-based models (PBMs) using e.g. ordinary differential equations (ODEs) are computationally efficient even for large populations due to their complexity being independent of the population size. Yet, population-based models are restricted in their granularity as they assume a (to some extent) homogeneous and well-mixed population. To manage the trade-off between computational complexity and level of detail, we propose spatial- and temporal-hybrid models that use ABMs only in an area or time frame of interest. To account for relevant influences to disease dynamics, e.g., from outside, due to commuting activities, we use population-based models, only adding moderate computational costs. Our hybridization approach demonstrates significant reduction in computational effort by up to 98% – without losing the required depth in information in the focus frame. The hybrid models used in our numerical simulations are based on two recently proposed models, however, any suitable combination of ABM and PBM could be used, too. Concluding, hybrid epidemiological models can provide insights on the individual scale where necessary, using aggregated models where possible, thereby making a contribution to green computing.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 571-590"},"PeriodicalIF":8.8,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143139809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of limited medical resources in an epidemic model with media report and general birth rate","authors":"Yicheng Hao,&nbsp;Yantao Luo,&nbsp;Zhidong Teng","doi":"10.1016/j.idm.2025.01.001","DOIUrl":"10.1016/j.idm.2025.01.001","url":null,"abstract":"<div><div>This paper formulates an SEIRSHM epidemic model with general birth rate, media report and limited medical resources. Firstly, the well-posedness of the solutions and the extinction of the disease are discussed. Then, the existence of the endemic equilibrium is discussed and we find when <em>R</em>∗ &gt; 1 and <em>R</em>₀ = 1, there exhibits a backward bifurcation, if <em>R</em>∗ &lt; 1 and <em>R</em>₀ = 1, there exhibits a forward bifurcation. Finally, numerical simulations are carried out to illustrate the main results and show that media report and limited medical resources have a great impact on disease transmission.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 522-535"},"PeriodicalIF":8.8,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11772943/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HCV transmission model with protection awareness in an SEACTR community","authors":"Liangwei Wang ,&nbsp;Fengying Wei ,&nbsp;Zhen Jin ,&nbsp;Xuerong Mao ,&nbsp;Shaojian Cai ,&nbsp;Guangmin Chen ,&nbsp;Kuicheng Zheng ,&nbsp;Jianfeng Xie","doi":"10.1016/j.idm.2024.12.014","DOIUrl":"10.1016/j.idm.2024.12.014","url":null,"abstract":"<div><h3>Background</h3><div>Hepatitis C virus (HCV) is a bloodborne virus that causes both acute and chronic hepatitis with the severity from a mild illness to liver cirrhosis and cancer. As one of the major infectious diseases in China, the monthly surveillance data from the Fujian Provincial Center for Disease Control and Prevention shows the increasing tendency from 2004 to 2011, the stable tendency from 2012 to 2016, and the declining tendency from 2017 to 2022. The 2004–2022 HCV infection tendency of Fujian Province is affected by nation-wide main control measures of Chinese government, because no control measures for HCV are modified from 2020 to 2022 during the prevalence of COVID-19 in Fujian Province.</div></div><div><h3>Methods</h3><div>The SEACTR (the susceptible, the exposed, the acutely infected, the chronically infected, the treated, the recovered) models with protection awareness are proposed. The next generation matrix method is used to compute basic reproduction number of toy model and dynamic analysis method is used to produce stochastic reproduction number of modified model. The least squares method and toy model are used to perform the optimal fitting against the monthly surveillance data. The positive preserving truncated Euler-Maruyama method is applied in modified model for the positivity of numerical simulations.</div></div><div><h3>Results</h3><div>The optimal fitting is performed using the monthly surveillance data provided by the Fujian Provincial Center for Disease Control and Prevention from 2004 to 2022. The sensitivities of protection efficiency and conversion rate to basic reproduction number and stochastic reproduction number are analyzed. The reproduction numbers and HCV infection scale with measures (single-measure, double-measure, triple-measure, and none-measure) are compared using toy model and modified model. The impacts of protection efficiency and conversion rate on exposed population, acutely infected population, chronically infected population, and treated population are analyzed. The tendency predictions for infected population and treated population in Fujian Province from 2023 to 2035 are conducted.</div></div><div><h3>Conclusions</h3><div>The HCV infection scale mainly depends on both protection efficiency and conversion rate, in which protection efficiency is the most important contributor. The reproduction numbers show the declining tendencies by phases, which indicate that the prevention and control of HCV in Fujian Province has achieved a remarkable achievement. The 2023–2035 tendency predictions of HCV infection scale in Fujian Province grow slowly due to approximately 19–109 monthly infections. The overall HCV growth tendency of Fujian Province is consistent with the nation-wide elimination objective.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 559-570"},"PeriodicalIF":8.8,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Zika's dynamics: A scoping review journey from epidemic to equations through mathematical modelling","authors":"Jhoana P. Romero-Leiton ,&nbsp;Elda K.E. Laison ,&nbsp;Rowin Alfaro ,&nbsp;E. Jane Parmley ,&nbsp;Julien Arino ,&nbsp;Kamal R. Acharya ,&nbsp;Bouchra Nasri","doi":"10.1016/j.idm.2024.12.016","DOIUrl":"10.1016/j.idm.2024.12.016","url":null,"abstract":"<div><div>Zika virus (ZIKV) infection, along with the concurrent circulation of other arboviruses, presents a great public health challenge, reminding the utilization of mathematical modelling as a crucial tool for explaining its intricate dynamics and interactions with co-circulating pathogens. Through a scoping review, we aimed to discern current mathematical models investigating ZIKV dynamics, focusing on its interplay with other pathogens, and to identify underlying assumptions and deficiencies supporting attention, particularly regarding the epidemiological attributes characterizing Zika outbreaks. Following the PRISMA-Sc guidelines, a systematic search across PubMed, Web of Science, and MathSciNet provided 137 pertinent studies from an initial pool of 2446 papers, showing a diversity of modelling approaches, predominantly centered on vector-host compartmental models, with a notable concentration on the epidemiological landscapes of Colombia and Brazil during the 2015–2016 Zika epidemic. While modelling studies have been important in explaining Zika transmission dynamics and their intersections with diseases such as Dengue, Chikungunya, and COVID-19 so far, future Zika models should prioritize robust data integration and rigorous validation against diverse datasets to improve the accuracy and reliability of epidemic prediction. In addition, models could benefit from adaptable frameworks incorporating human behavior, environmental factors, and stochastic parameters, with an emphasis on open-access tools to foster transparency and research collaboration.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 536-558"},"PeriodicalIF":8.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11786632/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143082204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A modelling approach to characterise the interaction between behavioral response and epidemics: A study based on COVID-19","authors":"Xinyu Chen,&nbsp;Suxia Zhang,&nbsp;Jinhu Xu","doi":"10.1016/j.idm.2024.12.013","DOIUrl":"10.1016/j.idm.2024.12.013","url":null,"abstract":"<div><div>During epidemic outbreaks, human behavior is highly influential on the disease transmission and hence affects the course, duration and outcome of the epidemics. In order to examine the feedback effect between the dynamics of the behavioral response and disease outbreak, a simple SIR-<em>β</em> type model is established by introducing the independent variable <em>β</em> of effective contact rate, characterizing how human behavior interacts with disease transmission dynamics and allowing for the feedback changing over time along the progress of epidemic and population's perception of risk. By a particle swarm optimization algorithm in the solution procedures and time series of COVID-19 data with different shapes of infection peaks, we show that the proposed model, together with such behavioral change mechanism, is capable of capturing the trend of the selected data and can give rise to oscillatory prevalence of different magnitude over time, revealing how different levels of behavioral response affect the waves of infection as well as the evolution of the disease.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 477-492"},"PeriodicalIF":8.8,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11750544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143025805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}