Infectious Disease Modelling最新文献

{"title":"Visual preferences for communicating modelling: a global analysis of COVID-19 policy and decision makers","authors":"Liza Hadley ,&nbsp;Caylyn Rich ,&nbsp;Alex Tasker ,&nbsp;Olivier Restif ,&nbsp;Sebastian Funk","doi":"10.1016/j.idm.2025.04.005","DOIUrl":"10.1016/j.idm.2025.04.005","url":null,"abstract":"<div><div>Effective communication of modelling results to policy and decision makers has been a longstanding challenge in times of crises. This communication takes many forms - visualisations, reports, presentations - and requires careful consideration to ensure accurate maintenance of the key scientific messages. Science-to-policy communication is further exacerbated when presenting fundamentally uncertain forms of science such as infectious disease modelling and other types of modelled evidence, something which has been understudied. Here we assess the communication and visualisation of infectious disease modelling results to national COVID-19 policy and decision makers in 13 different countries. We present a synthesis of recommendations on what aspects of visuals, graphs, and plots policymakers found to be most helpful in their COVID-19 response work. This work serves as a first evidence base for developing guidelines on the communication and translation of infectious disease modelling into policy.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 924-934"},"PeriodicalIF":8.8,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888193","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":"Impact of human mobility and weather conditions on Dengue mosquito abundance during the COVID-19 pandemic in Hong Kong","authors":"Yufan Zheng ,&nbsp;Keqi Yue ,&nbsp;Eric W.M. Wong ,&nbsp;Hsiang-Yu Yuan","doi":"10.1016/j.idm.2025.04.002","DOIUrl":"10.1016/j.idm.2025.04.002","url":null,"abstract":"<div><h3>Background</h3><div>While <em>Aedes</em> mosquitoes, the Dengue vectors, are expected to expand due to climate change, the impact of human mobility on them is largely unclear. Changes in human mobility, such as staying at home during the pandemic, likely affect mosquito abundance.</div></div><div><h3>Objectives</h3><div>We aimed to assess the influence of human mobility on the abundance and extensiveness of <em>Aedes albopictus</em>, taking account of the nonlinear lagged effects of weather, during the COVID-19 pandemic in Hong Kong.</div></div><div><h3>Methods</h3><div>Google human mobility indices (including residential, parks, and workplaces) and weather conditions (total rainfall and mean temperature) along with <em>Aedes albopictus</em> abundance and extensiveness, monitored using Gravidtrap were collected between April 2020 and August 2022. Distributed lag non-linear models with mixed-effects models were used to explore their influence in three areas of Hong Kong.</div></div><div><h3>Results</h3><div>Time spent at home (i.e., residential mobility) was negatively associated with mosquito abundance. The model projected that if residential mobility in 2022 was returned to the pre-pandemic level, the mosquito abundance would increase by an average of 80.49 % compared to actual observation. The relative risk (RR) of mosquito abundance was associated with low rainfall (&lt;50 mm) after 4.5 months, peaking at 1.73, compared with 300 mm. Heavy rainfall (&gt;500 mm) within 3 months was also associated with a peak RR of 1.41. Warm conditions (21–30 °C, compared with 20 °C) were associated with a higher RR of 1.47 after half a month.</div></div><div><h3>Discussion</h3><div>Human mobility is a critical factor along with weather conditions in mosquito prediction, and a stay-at-home policy may be an effective intervention to control <em>Aedes albopictus</em>.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 840-849"},"PeriodicalIF":8.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830098","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 the SEIR mean-field model in dynamic networks under intervention","authors":"Jiangmin Li ,&nbsp;Zhen Jin ,&nbsp;Ming Tang","doi":"10.1016/j.idm.2025.03.002","DOIUrl":"10.1016/j.idm.2025.03.002","url":null,"abstract":"<div><div>For emerging respiratory infectious diseases like COVID-19, non-pharmaceutical interventions such as isolation are crucial for controlling the spread. From the perspective of network transmission, non-pharmaceutical interventions like isolation alter the degree distribution and other topological structures of the network, thereby controlling the spread of the infectious disease. In this paper, we establish a SEIR mean-field propagation dynamics model for the synchronous evolution of dynamic networks caused by propagation and tracing isolation. We employ the reducing-dimension method to convert the mean-field model in networks into an equivalent and simpler low-dimension model, and then calculate the exact expression of the final size. In addition, we get the differential equations of the degree distribution over time in dynamic networks under tracing isolation and the relationships between the first and second moment of the dynamic network. While the degree of a node remains constant regardless of its state in many previous studies, this paper takes into account that the degree of each node changes over time whatever its state under the disease spread and intervention measures.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 850-874"},"PeriodicalIF":8.8,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839216","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":"Evolution into chaos – Implications of the trade-off between transmissibility and immune evasion","authors":"Golsa Sayyar ,&nbsp;Ábel Garab ,&nbsp;Gergely Röst","doi":"10.1016/j.idm.2025.04.003","DOIUrl":"10.1016/j.idm.2025.04.003","url":null,"abstract":"<div><div>Predicting viral evolution presents a significant challenge and is a critical public health priority. In response to this challenge, we develop a novel model for viral evolution that considers a trade-off between immunity evasion and transmissibility. The model selects for a new strain with the highest invasion fitness, taking into account this trade-off. When the dominant strain of the pathogen is highly transmissible, evolution tends to favor immune evasion, whereas for less contagious strains the direction of evolution leads toward increasing transmissibility. Assuming a linear functional form of this trade-off, we can express the long-term evolutionary patterns following the emergence of subsequent strains by a non-linear difference equation. We provide sufficient criteria for when evolution converges, and successive strains exhibit similar transmissibility. We also identify scenarios characterized by a two-periodic pattern in upcoming strains, indicating a situation where a highly transmissible but not immune-evasive strain is replaced by a less transmissible but highly immune-evasive strain, and vice versa, creating a cyclic pattern. Finally, we show that under certain conditions, viral evolution becomes chaotic and thus future transmissibilites become unpredictable in the long run. Visualization via bifurcation diagrams elucidates our analytical findings, revealing complex dynamic behaviors that include the presence of multiple periodic solutions and extend to chaotic regimes. Our analysis provides valuable insights into the complexities of viral evolution in the light of the trade-off between immune evasion and transmissibility.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 909-923"},"PeriodicalIF":8.8,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851474","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":"Invariant set theory for predicting potential failure of antibiotic cycling","authors":"Alejandro Anderson ,&nbsp;Matthew W. Kinahan ,&nbsp;Alejandro H. Gonzalez ,&nbsp;Klas Udekwu ,&nbsp;Esteban A. Hernandez-Vargas","doi":"10.1016/j.idm.2025.04.001","DOIUrl":"10.1016/j.idm.2025.04.001","url":null,"abstract":"<div><div>Collateral sensitivity, where resistance to one drug confers heightened sensitivity to another, offers a promising strategy for combating antimicrobial resistance, yet predicting resultant evolutionary dynamics remains a significant challenge. We propose here a mathematical model that integrates fitness trade-offs and adaptive landscapes to predict the evolution of collateral sensitivity pathways, providing insights into optimizing sequential drug therapies.</div><div>Our approach embeds collateral information into a network of switched systems, allowing us to abstract the effects of sequential antibiotic exposure on antimicrobial resistance. We analyze the system stability at disease-free equilibrium and employ set-control theory to tailor therapeutic windows. Consequently, we propose a computational algorithm to identify effective sequential therapies to counter antibiotic resistance. By leveraging our theory with data on collateral sensivity interactions, we predict scenarios that may prevent bacterial escape for chronic <em>Pseudomonas aeruginosa</em> infections.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 897-908"},"PeriodicalIF":8.8,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839190","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 SIRS models on networks: mean and variance of infection","authors":"Tingting Chen ,&nbsp;Guirong Liu ,&nbsp;Zhen Jin","doi":"10.1016/j.idm.2025.03.008","DOIUrl":"10.1016/j.idm.2025.03.008","url":null,"abstract":"<div><div>Due to the heterogeneity of contact structure, it is more reasonable to model on networks for epidemics. Because of the stochastic nature of events and the discrete number of individuals, the spread of epidemics is more appropriately viewed as a Markov chain. Therefore, we establish stochastic SIRS models with vaccination on networks to study the mean and variance of the number of susceptible and infected individuals for large-scale populations. Using van Kampen's system-size expansion, we derive a high-dimensional deterministic system which describes the mean behaviour and a Fokker-Planck equation which characterizes the variance around deterministic trajectories. Utilizing the qualitative analysis technique and Lyapunov function, we demonstrate that the disease-free equilibrium of the deterministic system is globally asymptotically stable if the basic reproduction number <em>R</em>₀ &lt; 1; and the endemic equilibrium is globally asymptotically stable if <em>R</em>₀ &gt; 1. Through the analysis of the Fokker-Planck equation, we obtain the asymptotic expression for the variance of the number of susceptible and infected individuals around the endemic equilibrium, which can be approximated by the elements of principal diagonal of the solution of the corresponding Lyapunov equation. Here, the solution of Lyapunov equation is expressed by vectorization operator of matrices and Kronecker product. Finally, numerical simulations illustrate that vaccination can reduce infections and increase fluctuations of the number of infected individuals and show that individuals with greater degree are more easily infected.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 875-896"},"PeriodicalIF":8.8,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844306","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":"Dynamics of an epidemic controlled by isolation and quarantine: A probability-based deterministic model","authors":"David V. Kalbaugh","doi":"10.1016/j.idm.2025.03.007","DOIUrl":"10.1016/j.idm.2025.03.007","url":null,"abstract":"<div><div>Assuming a homogeneous population, we employ a deterministic model based on first principles of probability to explore dynamics of an epidemic controlled by isolation alone, quarantine alone, and the two together. We develop explicit closed-form equations for key metrics of control performance: cumulative fraction of population infected over the course of the epidemic (final size), maximum fraction infected at any one time, and epidemic duration. We derive an analytical solution for final size of an epidemic controlled by isolation, when final size is small, and develop empirical relations for the other cases. We frame equations in terms of reproduction numbers, measures of intervention effort and initial conditions. We model both strength and speed of interventions, assume second order gamma distributions for intervention waiting times and employ non-time-invariant equations for quarantine. We also account for quarantine of unexposed, susceptible individuals and for imperfect intervention.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 813-839"},"PeriodicalIF":8.8,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820778","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":"Epidemiological indices with multiple circulating pathogen strains","authors":"Cristiano Trevisin ,&nbsp;Lorenzo Mari ,&nbsp;Marino Gatto ,&nbsp;Vittoria Colizza ,&nbsp;Andrea Rinaldo","doi":"10.1016/j.idm.2025.03.006","DOIUrl":"10.1016/j.idm.2025.03.006","url":null,"abstract":"<div><div>Epidemiological indicators (e.g. reproduction numbers and epidemicity indices) describe long- and short-term behaviour of ongoing epidemics. Their evolving values provide context for designing control measures because maintaining both indices below suitable thresholds warrants waning infection numbers. However, current models for the computation of epidemiological metrics do not consider the stratification of the pathogen into variants endowed with different infectivity and epidemiological severity. This is the case, in particular, with SARS-CoV-2 infections. Failing to account for the variety of epidemiological features of emerging variants prevents epidemiological indices from spotting the possible onset of uncontrolled growth of specific variants, thus significantly limiting the prognostic value of the indicators. Here, we expand an existing framework for the computation of spatially explicit reproduction numbers and epidemicity indices to account for arising variants. By analysing the data of the COVID-19 pandemic in Italy, we show that embedding additional layers of complexity in the mathematical descriptions of unfolding epidemics reveals new angles. In particular, we find epidemiological metrics significantly exceeding their thresholds at the emergence of new variants. Such values foresee a recrudescence in new infections that only becomes evident after emerging new variants have effectively replaced the previous active strains. The demography of the variant composition flags the presence of specific strains growing more rapidly than the total number of infections generated by all variants combined. Variant-aware epidemiological indicators thus allow to engineer better control measures tailored to the shifting patterns of severity and evolving features of infectious disease epidemics.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 802-812"},"PeriodicalIF":8.8,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686190","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":"Assessing the effectiveness of test-trace-isolate interventions using a multi-layered temporal network","authors":"Yunyi Cai ,&nbsp;Weiyi Wang ,&nbsp;Lanlan Yu ,&nbsp;Ruixiao Wang ,&nbsp;Gui-Quan Sun ,&nbsp;Allisandra G. Kummer ,&nbsp;Paulo C. Ventura ,&nbsp;Jiancheng Lv ,&nbsp;Marco Ajelli ,&nbsp;Quan-Hui Liu","doi":"10.1016/j.idm.2025.03.005","DOIUrl":"10.1016/j.idm.2025.03.005","url":null,"abstract":"<div><div>In the early stage of an infectious disease outbreak, public health strategies tend to gravitate towards non-pharmaceutical interventions (NPIs) given the time required to develop targeted treatments and vaccines. One of the most common NPIs is Test-Trace-Isolate (TTI). One of the factors determining the effectiveness of TTI is the ability to identify contacts of infected individuals. In this study, we propose a multi-layer temporal contact network to model transmission dynamics and assess the impact of different TTI implementations, using SARS-CoV-2 as a case study. The model was used to evaluate TTI effectiveness both in containing an outbreak and mitigating the impact of an epidemic. We estimated that a TTI strategy based on home isolation and testing of both primary and secondary contacts can contain outbreaks only when the reproduction number is up to 1.3, at which the epidemic prevention potential is 88.2% (95% CI: 87.9%–88.5%). On the other hand, for higher value of the reproduction number, TTI is estimated to noticeably mitigate disease burden but at high social costs (e.g., over a month in isolation/quarantine per person for reproduction numbers of 1.7 or higher). We estimated that strategies considering quarantine of contacts have a larger epidemic prevention potential than strategies that either avoid tracing contacts or require contacts to be tested before isolation. Combining TTI with other social distancing measures can improve the likelihood of successfully containing an outbreak but the estimated epidemic prevention potential remains lower than 50% for reproduction numbers higher than 2.1. In conclusion, our model-based evaluation highlights the challenges of relying on TTIs to contain an outbreak of a novel pathogen with characteristics similar to SARS-CoV-2, and that the estimated effectiveness of TTI depends on the way contact patterns are modeled, supporting the relevance of obtaining comprehensive data on human social interactions to improve preparedness.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 775-786"},"PeriodicalIF":8.8,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654522","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 refractory density approach to a multi-scale SEIRS epidemic model","authors":"Anton Chizhov ,&nbsp;Laurent Pujo-Menjouet ,&nbsp;Tilo Schwalger ,&nbsp;Mattia Sensi","doi":"10.1016/j.idm.2025.03.004","DOIUrl":"10.1016/j.idm.2025.03.004","url":null,"abstract":"<div><div>We propose a novel multi-scale modeling framework for infectious disease spreading, borrowing ideas and modeling tools from the so-called Refractory Density (RD) approach. We introduce a microscopic model that describes the probability of infection for a single individual and the evolution of the disease within their body. From the individual-level description, we then present the corresponding population-level model of epidemic spreading on the mesoscopic and macroscopic scale. We conclude with numerical illustrations, taking into account either a white Gaussian noise or an escape noise to showcase the potential of our approach in producing both transient and asymptotic complex dynamics as well as finite-size fluctuations consistently across multiple scales. A comparison with the epidemiology of coronaviruses is also given to corroborate the qualitative relevance of our new approach.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 787-801"},"PeriodicalIF":8.8,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686191","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}