Infectious Disease Modelling最新文献

{"title":"Comparative assessment of airborne infection risk tools in enclosed spaces: Implications for disease control","authors":"Amar Aganovic ,&nbsp;Giorgio Buonanno ,&nbsp;Guangyu Cao ,&nbsp;Christian Delmaar ,&nbsp;Jarek Kurnitski ,&nbsp;Alex Mikszewski ,&nbsp;Lidia Morawska ,&nbsp;Lucie C. Vermeulen ,&nbsp;Pawel Wargocki","doi":"10.1016/j.idm.2024.11.003","DOIUrl":"10.1016/j.idm.2024.11.003","url":null,"abstract":"<div><div>The COVID-19 pandemic, caused by SARS-CoV-2, highlighted the importance of understanding transmission modes and implementing effective mitigation strategies. Recognizing airborne transmission as a primary route has reshaped public health measures, emphasizing the need to optimize indoor environments to reduce risks. Numerous tools have emerged to assess airborne infection risks in enclosed spaces, providing valuable resources for public health authorities, researchers, and the general public.</div><div>However, comparing the outputs of these tools is challenging because of variations in assumptions, mathematical models, and data sources. We conducted a comprehensive review, comparing digital airborne infection risk calculators using standardized building-specific input parameters. These tools generally produce similar and consistent outputs with identical inputs. Variations mainly stem from model selection and the handling of unsteady viral load conditions. Differences in source term calculations, including particle emission concentrations and respiratory activity, also contribute to disparities. These differences are minor compared to the inherent uncertainties in risk assessment. Consistency in results increases with higher ventilation rates, showing a robust trend across models. However, inconsistencies arose in the inclusion of face masks, often due to the lack of detailed efficiency values. Despite some differences, the overall consistency underscores the value of these tools in public health strategy and infectious disease control.</div><div>We also compared some of the model's efforts to conduct retrospective assessments against reported transmission events by assuming input parameters to the models so that the calculated risk would closely fit the original outbreak infection rate. Thus, validating these models against past outbreaks remains challenging because of the lack of essential input information from observed events. This comparative analysis demonstrates the importance of transparent data sources and justifiable model assumptions to enhance the reliability and precision of risk assessments.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 338-352"},"PeriodicalIF":8.8,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655680/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142866368","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":"Evaluation of wastewater percent positive for assessing epidemic trends - A case study of COVID-19 in Shangrao, China","authors":"Jing Wang ,&nbsp;Haifeng Zhou ,&nbsp;Wentao Song ,&nbsp;Lingzhen Xu ,&nbsp;Yaoying Zheng ,&nbsp;Chen You ,&nbsp;Xiangyou Zhang ,&nbsp;Yeshan Peng ,&nbsp;Xiaolan Wang ,&nbsp;Tianmu Chen","doi":"10.1016/j.idm.2024.11.001","DOIUrl":"10.1016/j.idm.2024.11.001","url":null,"abstract":"<div><h3>Objective</h3><div>This study aims to assess the feasibility of evaluating the COVID-19 epidemic trend through monitoring the positive percentage of SARS-CoV-19 RNA in wastewater.</div></div><div><h3>Method</h3><div>The study collected data from January to August 2023, including the number of reported cases, the positive ratio of nucleic acid samples in sentinel hospitals, the incidence rate of influenza-like symptoms in students, and the positive ratio of wastewater samples in different counties and districts in Shangrao City. Wastewater samples were obtained through grabbing and laboratory testing was completed within 24 h. The data were then normalized using Z-score normalization and analyzed for lag time and correlation using the xcorr function and Spearman correlation coefficient.</div></div><div><h3>Results</h3><div>A total of 2797 wastewater samples were collected. The wastewater monitoring study, based on sampling point distribution, was divided into two phases. Wuyuan County consistently showed high levels of positive ratio in wastewater samples in both phases, reaching peak values of 91.67% and 100% respectively. The lag time analysis results indicated that the peak positive ratio in all wastewater samples in Shangrao City appeared around 2 weeks later compared to the other three indicators. The correlation analysis revealed a strong linear correlation across all four types of data, with Spearman correlation coefficients ranging from 0.783 to 0.977, all of which were statistically significant.</div></div><div><h3>Conclusion</h3><div>The positive ratio of all wastewater samples in Shangrao City accurately reflected the COVID-19 epidemic trend from January to August 2023. This study confirmed the lag effect of wastewater percent positive and its strong correlation with the reported incidence rate and the positive ratio of nucleic acid samples in sentinel hospitals, supporting the use of wastewater percent positive monitoring as a supplementary tool for infectious disease surveillance in the regions with limited resources.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 325-337"},"PeriodicalIF":8.8,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706607","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":"Behavioural Change Piecewise Constant Spatial Epidemic Models","authors":"Chinmoy Roy Rahul ,&nbsp;Rob Deardon","doi":"10.1016/j.idm.2024.10.006","DOIUrl":"10.1016/j.idm.2024.10.006","url":null,"abstract":"<div><div>Human behaviour significantly affects the dynamics of infectious disease transmission as people adjust their behavior in response to outbreak intensity, thereby impacting disease spread and control efforts. In recent years, there have been efforts to incorporate behavioural change into spatio-temporal individual-level models within a Bayesian MCMC framework. In this past work, parametric spatial risk functions were employed, depending on strong underlying assumptions regarding disease transmission mechanisms within the population. However, selecting appropriate parametric functions can be challenging in real-world scenarios, and incorrect assumptions may lead to erroneous conclusions. As an alternative, non-parametric approaches offer greater flexibility. The goal of this study is to investigate the utilization of semi-parametric spatial models for infectious disease transmission, integrating an “alarm function” to account for behavioural change based on infection prevalence over time within a Bayesian MCMC framework. In this paper, we discuss findings from both simulated and real-life epidemics, focusing on constant piecewise distance functions with fixed change points. We also demonstrate the selection of the change points using the Deviance Information Criteria (DIC).</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 302-324"},"PeriodicalIF":8.8,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656418","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":"Application of multiple linear regression model and long short-term memory with compartmental model to forecast dengue cases in Selangor, Malaysia based on climate variables","authors":"Xinyi Lu ,&nbsp;Su Yean Teh ,&nbsp;Chai Jian Tay ,&nbsp;Nur Faeza Abu Kassim ,&nbsp;Pei Shan Fam ,&nbsp;Edy Soewono","doi":"10.1016/j.idm.2024.10.007","DOIUrl":"10.1016/j.idm.2024.10.007","url":null,"abstract":"<div><div>Despite the implementation of various initiatives, dengue remains a significant public health concern in Malaysia. Given that dengue has no specific treatment, dengue prediction remains a useful early warning mechanism for timely and effective deployment of public health preventative measures. This study aims to develop a comprehensive approach for forecasting dengue cases in Selangor, Malaysia by incorporating climate variables. An ensemble of Multiple Linear Regression (MLR) model, Long Short-Term Memory (LSTM), and Susceptible-Infected mosquito vectors, Susceptible-Infected-Recovered human hosts (SI-SIR) model were used to establish a relation between climate variables (temperature, humidity, precipitation) and mosquito biting rate. Dengue incidence subject to climate variability can then be projected by SI-SIR model using the forecasted mosquito biting rate. The proposed approach outperformed three alternative approaches and expanded the temporal horizon of dengue prediction for Selangor with the ability to forecast approximately 60 weeks ahead with a Mean Absolute Percentage Error (MAPE) of 13.97 for the chosen prediction window before the implementation of the Movement Control Order (MCO) in Malaysia. Extended validation across subsequent periods also indicates relatively satisfactory forecasting performance (with MAPE ranging from 13.12 to 17.09). This research contributed to the field by introducing a novel framework for the prediction of dengue cases over an extended temporal range.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 240-256"},"PeriodicalIF":8.8,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579046","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":"Conditional logistic individual-level models of spatial infectious disease dynamics","authors":"Tahmina Akter ,&nbsp;Rob Deardon","doi":"10.1016/j.idm.2024.10.008","DOIUrl":"10.1016/j.idm.2024.10.008","url":null,"abstract":"<div><div>Here, we introduce a novel framework for modelling the spatiotemporal dynamics of disease spread known as conditional logistic individual-level models (CL-ILM's). This framework alleviates much of the computational burden associated with traditional spatiotemporal individual-level models for epidemics, and facilitates the use of standard software for fitting logistic models when analysing spatiotemporal disease patterns. The models can be fitted in either a frequentist or Bayesian framework. Here, we apply the new spatial CL-ILM to simulated data, semi-real data from the UK 2001 foot-and-mouth disease epidemic, and real data from a greenhouse experiment on the spread of tomato spotted wilt virus.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 268-286"},"PeriodicalIF":8.8,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656483","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":"Information-guided adaptive learning approach for active surveillance of infectious diseases","authors":"Qi Tan ,&nbsp;Chenyang Zhang ,&nbsp;Jiwen Xia ,&nbsp;Ruiqi Wang ,&nbsp;Lian Zhou ,&nbsp;Zhanwei Du ,&nbsp;Benyun Shi","doi":"10.1016/j.idm.2024.10.005","DOIUrl":"10.1016/j.idm.2024.10.005","url":null,"abstract":"<div><div>The infectious disease surveillance system is a key support tool for public health decision making. Current research concentrates on optimizing static sentinel deployment to address the problem of incomplete data due to the lack of sufficient surveillance resources. In this study, we introduce an information-guided adaptive learning strategy for the dynamic surveillance of infectious diseases. The goal is to improve monitoring effectiveness in situations where it is possible to adjust the focus of surveillance, such as serial surveys and allocation of testing tools. Specifically, we develop a probabilistic neural network model to learn spatio-temporal correlations among the numbers of infections. Based on a probabilistic model, we evaluate the information gain of monitoring a spatio-temporal target and design a greedy selection algorithm for monitoring targets selection. Moreover, we integrate two major surveillance objectives, i.e., informativeness and coverage, in the monitoring target selection. The experimental results on the synthetic dataset and two real-world datasets demonstrate the effectiveness of our approach, showcasing the promise of further exploration and application of dynamic adaptive active surveillance.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 257-267"},"PeriodicalIF":8.8,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656482","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":"Network-based virus dynamic simulation: Evaluating the fomite disinfection effectiveness on SARS-CoV-2 transmission in indoor environment","authors":"Syun-suke Kadoya ,&nbsp;Sewwandi Bandara ,&nbsp;Masayuki Ogata ,&nbsp;Takayuki Miura ,&nbsp;Michiko Bando ,&nbsp;Daisuke Sano","doi":"10.1016/j.idm.2024.10.004","DOIUrl":"10.1016/j.idm.2024.10.004","url":null,"abstract":"<div><div>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is involved in aerosol particles and droplets excreted from a coronavirus disease 2019 (COVID-19) patient. Such aerosol particles or droplets including infectious virions can be attached on fomite, so fomite is not a negligible route for SARS-CoV-2 transmission within a community, especially in indoor environment. This necessarily evokes a need of fomite disinfection to remove virions, but the extent to which fomite disinfection breaks off virus transmission chain in indoor environment is still elusive. In this study, we evaluated the fomite disinfection effectiveness on COVID-19 case number using network analysis that reproduced the reported indoor outbreaks. In the established network, virus can move around not only human but also air and fomite while growing in human and decaying in air and on fomite, and infection success was determined based on the exposed virus amount and the equation of probability of infection. The simulation results have demonstrated that infectious virions on fomite should be kept less than a hundred to sufficiently reduce COVID-19 case, and every-hour disinfection was required to avoid stochastic increase in the infection case. This study gives us a practical disinfection manner for fomite to control SARS-CoV-2 transmission in indoor environment.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 229-239"},"PeriodicalIF":8.8,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539544","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":"Stronger binding affinities of gp120/CD4 in Catarrhini provide insights into HIV/host interactions","authors":"Vladimir Li ,&nbsp;Chul Lee ,&nbsp;TaeHyun Park ,&nbsp;Erich D. Jarvis ,&nbsp;Heebal Kim","doi":"10.1016/j.idm.2024.10.003","DOIUrl":"10.1016/j.idm.2024.10.003","url":null,"abstract":"<div><div>Human immunodeficiency virus-1 (HIV-1) exploits the viral <em>gp120</em> protein and host <em>CD4</em>/<em>CCR5</em> receptors for the pandemic infection to humans. The host co-receptors of not only humans but also several primates and HIV-model mice can interact with the HIV receptor. However, the molecular mechanisms of these interactions remain unclear. Using Shaik et al. (2019)'s <em>gp120/CD4/CCR5</em> structure of HIV-1B and human, here, we investigate the molecular dynamics between HIV sub-lineages (B, C, N, and O) and potential hosts in <em>Euarchontoglires</em> (primates and rodents). Although both host genes show similar protein structures conserved in all animals, <em>CD4</em> gene demonstrates significantly stronger binding affinities in <em>Catarrhini</em> (apes and Old-World monkeys). Its known candidate residues interacted with gp120 fail to explain these affinity variations. Therefore, we identified novel candidate sites under positive selection on the <em>Catarrhini</em> lineage. Among four positively selected sites, residue R58 in humans is located within an antigen-antibody binding domain, exhibiting apomorphic amino acid substitutions as Arginine (R) in <em>Catarrhini</em>, which are mutually exclusive to the other animals where Lysine (K) is prevalent. Applying for artificial mutation test, we validated that K to R substitutions can lead stronger binding affinities of <em>Catarrhini</em>. Ecologically, these dynamics may relate to shared equatorial habitats in Africa and Asia. Our findings suggest a new candidate site R58 driven by the lineage-specific evolution as a molecular foundation on HIV infection.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 287-301"},"PeriodicalIF":8.8,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656417","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":"Dynamics of an SVEIR transmission model with protection awareness and two strains","authors":"Kaijing Chen ,&nbsp;Fengying Wei ,&nbsp;Xinyan Zhang ,&nbsp;Hao Jin ,&nbsp;Ruiyang Zhou ,&nbsp;Yue Zuo ,&nbsp;Kai Fan","doi":"10.1016/j.idm.2024.10.001","DOIUrl":"10.1016/j.idm.2024.10.001","url":null,"abstract":"<div><div>As of May 2024, the main strains of COVID-19 caused hundreds of millions of infection cases and millions of deaths worldwide. In this study, we consider the COVID-19 epidemics with the main strains in the Chinese mainland. We study complex interactions among hosts, non-pharmaceutical interventions, and vaccinations for the main strains by a differential equation model called SVEIR. The disease transmission model incorporates two strains and protection awareness of the susceptible population. Results of this study show that the protection awareness plays a crucial role against infection of the population, and that the vaccines are effective against the circulation of the earlier strains, but ineffective for emerging strains. By using the next generation matrix method, the basic reproduction number of the SVEIR model is firstly obtained. Our analysis by Hurwitz criterion and LaSalle's invariance principle shows that the disease free-equilibrium point is locally and globally asymptotically stable when the threshold value is below one. The existences of endemic equilibrium points are also established, and the global asymptotic stabilities are analyzed using the Lyapunov function method. Further, the SVEIR model is confirmed to satisfy the principle of competitive exclusion, of which the strain with the larger value of the basic reproduction number is dominant. Numerically, the surveillance data with the Omicron strain and the XBB strain are split by the cubic spline interpolation method. The fitting curves against the surveillance data are plotted using the least-squares method from MATLAB. The results indicate that the XBB strain dominates in this study. Moreover, a global sensitivity analysis of the key parameters is performed by using of PRCC. The numerical simulations imply that combination control strategy positively impacts on the infection scale than what separate control strategy does, and that the earlier time producing protection awareness for the public creates less infection scale, further that the increment of protection awareness also reduces the infection scale. Therefore, the policymakers of the local government are suggested to concern the changes of protection awareness of the public.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 207-228"},"PeriodicalIF":8.8,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445086","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 tentative exploration for the association between influenza virus infection and SARS-CoV-2 infection in Shihezi, China: A test-negative study","authors":"Songsong Xie ,&nbsp;Yinxia Su ,&nbsp;Yanji Zhao ,&nbsp;Yaling Du ,&nbsp;Zihao Guo ,&nbsp;Xiu Gu ,&nbsp;Jie Sun ,&nbsp;Mohammad Javanbakht ,&nbsp;Daihai He ,&nbsp;Jiazhen Zhang ,&nbsp;Yan Zhang ,&nbsp;Kai Wang ,&nbsp;Shi Zhao","doi":"10.1016/j.idm.2024.10.002","DOIUrl":"10.1016/j.idm.2024.10.002","url":null,"abstract":"<div><div>The outbreak of respiratory diseases, such as COVID-19 and influenza, has drawn global attention. However, it remains unclear whether the risk of influenza A infection may be affected by the history of SARS-CoV-2 infection. In this study, we conducted a test-negative case-control study, and utilized a logistic regression model to analyze the relationship between SARS-CoV-2 and influenza A infections. Among 258 eligible patient samples with influenza-like illness (ILI), we did not detect a statistically significant association between the history of SARS-CoV-2 infection and the risk of influenza A infection. These findings might indicate that antibodies against COVID-19 acquired through vaccination or natural immunity have not protected against influenza.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 201-206"},"PeriodicalIF":8.8,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142428652","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}