Infectious Disease Modelling最新文献

Evaluation of wastewater percent positive for assessing epidemic trends - A case study of COVID-19 in Shangrao, China 评估疫情趋势的废水阳性率 - 中国上饶 COVID-19 案例研究

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-11-16 DOI: 10.1016/j.idm.2024.11.001

Jing Wang , Haifeng Zhou , Wentao Song , Lingzhen Xu , Yaoying Zheng , Chen You , Xiangyou Zhang , Yeshan Peng , Xiaolan Wang , Tianmu Chen

Objective

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.

Method

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.

Results

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.

Conclusion

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.

方法收集 2023 年 1 月至 8 月上饶市各县区报告病例数、定点医院核酸样本阳性率、学生流感样症状发病率、废水样本阳性率等数据。通过抓取方式获得废水样本，并在 24 小时内完成实验室检测。然后使用 Z 值归一化法对数据进行归一化处理，并使用 xcorr 函数和 Spearman 相关系数对滞后时间和相关性进行分析。根据采样点分布，废水监测研究分为两个阶段。婺源县在两个阶段的废水样本中均显示出较高的阳性比例，峰值分别达到 91.67% 和 100%。滞后时间分析结果表明，上饶市所有废水样本的阳性比值峰值出现的时间比其他三项指标晚两周左右。相关性分析表明，四类数据均存在较强的线性相关关系，斯皮尔曼相关系数在 0.783 至 0.977 之间，均具有统计学意义。本研究证实了废水阳性率的滞后效应及其与报告发病率和哨点医院核酸样本阳性率的强相关性，支持将废水阳性率监测作为资源有限地区传染病监测的辅助工具。

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引用次数: 0

Behavioural Change Piecewise Constant Spatial Epidemic Models 行为变化片断常数空间流行病模型

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-11-12 DOI: 10.1016/j.idm.2024.10.006

Chinmoy Roy Rahul , Rob Deardon

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).

人类行为会极大地影响传染病的传播动态，因为人们会根据疫情强度调整自己的行为，从而影响疾病的传播和控制工作。近年来，人们一直致力于在贝叶斯 MCMC 框架内将行为变化纳入时空个体级模型。在过去的工作中，根据对人口中疾病传播机制的基本假设，采用了参数空间风险函数。然而，在现实世界中，选择适当的参数函数可能具有挑战性，不正确的假设可能会导致错误的结论。作为一种替代方法，非参数方法具有更大的灵活性。本研究的目标是调查半参数空间模型在传染病传播中的应用，在贝叶斯 MCMC 框架内整合 "报警函数"，以解释基于感染率随时间变化的行为变化。在本文中，我们讨论了模拟和现实生活中流行病的研究结果，重点是具有固定变化点的恒定片断距离函数。我们还演示了如何使用偏差信息准则（DIC）选择变化点。

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引用次数: 0

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 基于气候变量的多元线性回归模型和长短期记忆分区模型在马来西亚雪兰莪州登革热病例预测中的应用

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-10-28 DOI: 10.1016/j.idm.2024.10.007

Xinyi Lu , Su Yean Teh , Chai Jian Tay , Nur Faeza Abu Kassim , Pei Shan Fam , Edy Soewono

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.

尽管采取了各种措施，登革热仍然是马来西亚的一个重大公共卫生问题。鉴于登革热没有特效治疗方法，登革热预测仍然是一种有用的早期预警机制，有助于及时有效地部署公共卫生预防措施。本研究旨在结合气候变量，开发一种预测马来西亚雪兰莪州登革热病例的综合方法。研究采用了多重线性回归（MLR）模型、长短期记忆（LSTM）和易感-受感染蚊媒、易感-受感染-已恢复人类宿主（SI-SIR）模型的组合，以建立气候变量（温度、湿度、降水量）与蚊虫叮咬率之间的关系。然后，SI-SIR 模型可利用预测的蚊虫叮咬率预测受气候变异影响的登革热发病率。所提出的方法优于其他三种方法，并扩大了雪兰莪州登革热预测的时间范围，能够提前约 60 周进行预测，在马来西亚实施移动控制令（MCO）之前，所选预测窗口的平均绝对百分比误差（MAPE）为 13.97。对后续时段的扩展验证也显示出相对令人满意的预测性能（MAPE 在 13.12 到 17.09 之间）。这项研究通过引入一个新的框架来预测更大时间范围内的登革热病例，为该领域做出了贡献。

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引用次数: 0

Conditional logistic individual-level models of spatial infectious disease dynamics 空间传染病动态的条件逻辑个体水平模型

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-10-28 DOI: 10.1016/j.idm.2024.10.008

Tahmina Akter , Rob Deardon

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.

在此，我们介绍一种用于模拟疾病传播时空动态的新型框架，即条件逻辑个体水平模型（CL-ILM）。该框架减轻了传统流行病时空个体水平模型的大部分计算负担，便于在分析时空疾病模式时使用标准软件拟合逻辑模型。这些模型可以在频数主义或贝叶斯框架内拟合。在此，我们将新的空间 CL-ILM 应用于模拟数据、英国 2001 年口蹄疫疫情的半真实数据以及番茄斑萎病毒传播温室实验的真实数据。

引用次数: 0

Information-guided adaptive learning approach for active surveillance of infectious diseases 传染病主动监测的信息引导自适应学习方法

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-10-26 DOI: 10.1016/j.idm.2024.10.005

Qi Tan , Chenyang Zhang , Jiwen Xia , Ruiqi Wang , Lian Zhou , Zhanwei Du , Benyun Shi

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.

传染病监测系统是公共卫生决策的重要支持工具。目前的研究主要集中于优化静态哨点部署，以解决因缺乏足够监测资源而导致的数据不完整问题。在本研究中，我们为传染病的动态监测引入了一种信息指导下的自适应学习策略。其目的是在可以调整监测重点的情况下提高监测效果，如连续调查和检测工具的分配。具体来说，我们开发了一个概率神经网络模型，用于学习感染数量之间的时空相关性。基于概率模型，我们评估了监测时空目标的信息增益，并设计了一种用于监测目标选择的贪婪选择算法。此外，我们在监测目标选择中整合了两个主要监测目标，即信息量和覆盖率。在合成数据集和两个真实世界数据集上的实验结果证明了我们方法的有效性，展示了进一步探索和应用动态自适应主动监控的前景。

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引用次数: 0

Network-based virus dynamic simulation: Evaluating the fomite disinfection effectiveness on SARS-CoV-2 transmission in indoor environment 基于网络的病毒动态模拟：评估室内环境中飞沫消毒对 SARS-CoV-2 传播的有效性

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-10-22 DOI: 10.1016/j.idm.2024.10.004

Syun-suke Kadoya , Sewwandi Bandara , Masayuki Ogata , Takayuki Miura , Michiko Bando , Daisuke Sano

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.

严重急性呼吸系统综合征冠状病毒 2（SARS-CoV-2）与 2019 年冠状病毒病（COVID-19）患者排出的气溶胶颗粒和飞沫有关。这些气溶胶粒子或飞沫包括传染性病毒，可以附着在飞沫上，因此飞沫是社区内，尤其是室内环境中传播 SARS-CoV-2 的一个不可忽视的途径。这就必然要求对吸附物进行消毒以清除病毒，但吸附物消毒能在多大程度上切断病毒在室内环境中的传播链仍是一个未知数。在本研究中，我们利用网络分析再现了已报道的室内疫情，评估了对 COVID-19 病例数的烟灶消毒效果。在已建立的网络中，病毒不仅可以在人体内移动，还可以在空气和酵母中移动，同时在人体内生长，并在空气和酵母中腐烂。模拟结果表明，要充分减少 COVID-19 病例，应将 fomite 上的传染性病毒数量控制在 100 个以下，并且需要每小时消毒一次，以避免感染病例的随机增加。这项研究为控制 SARS-CoV-2 在室内环境中的传播提供了一种实用的烟具消毒方式。

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引用次数: 0

Stronger binding affinities of gp120/CD4 in Catarrhini provide insights into HIV/host interactions 猫科动物体内 gp120/CD4 更强的结合亲和力有助于深入了解艾滋病毒与宿主的相互作用

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-10-19 DOI: 10.1016/j.idm.2024.10.003

Vladimir Li , Chul Lee , TaeHyun Park , Erich D. Jarvis , Heebal Kim

Human immunodeficiency virus-1 (HIV-1) exploits the viral gp120 protein and host CD4/CCR5 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 gp120/CD4/CCR5 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 Euarchontoglires (primates and rodents). Although both host genes show similar protein structures conserved in all animals, CD4 gene demonstrates significantly stronger binding affinities in Catarrhini (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 Catarrhini 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 Catarrhini, 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 Catarrhini. 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.

人类免疫缺陷病毒-1（HIV-1）利用病毒 gp120 蛋白和宿主 CD4/CCR5 受体对人类进行大流行感染。不仅人类，一些灵长类动物和艾滋病毒模型小鼠的宿主共受体也能与艾滋病毒受体相互作用。然而，这些相互作用的分子机制仍不清楚。利用 Shaik 等人（2019 年）的 HIV-1B 和人类 gp120/CD4/CCR5 结构，我们在此研究了 HIV 亚系（B、C、N 和 O）与欧亚动物（灵长类和啮齿类）潜在宿主之间的分子动态。虽然两种宿主基因都显示出在所有动物中都保留的类似蛋白质结构，但 CD4 基因在鼬科动物（猿和旧世界猴）中显示出明显更强的结合亲和力。其与 gp120 相互作用的已知候选残基无法解释这些亲和力变化。因此，我们在猫科动物中发现了正向选择的新候选位点。在四个正选择位点中，人类的残基 R58 位于抗原-抗体结合域内，在猫科动物中表现为精氨酸（R）的非形态氨基酸取代，这与其他动物中赖氨酸（K）的普遍存在相互排斥。通过人工突变测试，我们验证了 K 到 R 的置换可导致 Catarrhini 更强的结合亲和力。从生态学角度看，这些动态可能与非洲和亚洲共同的赤道栖息地有关。我们的研究结果表明，一个新的候选位点 R58 是由血统特异性进化驱动的，是 HIV 感染的分子基础。

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引用次数: 0

Dynamics of an SVEIR transmission model with protection awareness and two strains 具有保护意识和两种菌株的 SVEIR 传播模型的动态变化

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-10-10 DOI: 10.1016/j.idm.2024.10.001

Kaijing Chen , Fengying Wei , Xinyan Zhang , Hao Jin , Ruiyang Zhou , Yue Zuo , Kai Fan

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.

截至 2024 年 5 月，COVID-19 的主要毒株在全球造成了数亿感染病例和数百万人死亡。在本研究中，我们考虑了 COVID-19 主要菌株在中国大陆的流行情况。我们通过一个名为 SVEIR 的微分方程模型，研究了宿主、非药物干预措施和主要菌株疫苗接种之间复杂的相互作用。该疾病传播模型包含两种菌株和易感人群的保护意识。研究结果表明，保护意识对人群感染起着关键作用，疫苗对早期毒株的传播有效，但对新出现的毒株无效。通过使用下一代矩阵法，首先得到了 SVEIR 模型的基本繁殖数。根据赫维茨准则和拉萨尔不变性原理的分析表明，当阈值小于 1 时，疾病自由平衡点在局部和全局上都是渐近稳定的。同时还确定了地方病平衡点的存在，并利用 Lyapunov 函数方法分析了全局渐近稳定性。此外，还证实了 SVEIR 模型符合竞争排斥原理，其中基本繁殖数值较大的菌株占优势。在数值上，用三次样条插值法分割了 Omicron 菌株和 XBB 菌株的监测数据。使用 MATLAB 中的最小二乘法绘制了与监测数据相对应的拟合曲线。结果表明，XBB 应变在本研究中占主导地位。此外，还利用 PRCC 对关键参数进行了全局敏感性分析。数值模拟结果表明，与单独的控制策略相比，组合控制策略对感染规模有积极影响，而且越早让公众产生防护意识，感染规模就越小，而防护意识的提高也会降低感染规模。因此，建议地方政府决策者关注公众防护意识的变化。

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引用次数: 0

A tentative exploration for the association between influenza virus infection and SARS-CoV-2 infection in Shihezi, China: A test-negative study 中国石河子市流感病毒感染与 SARS-CoV-2 感染关系的初步探索：一项检测阴性的研究

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-10-09 DOI: 10.1016/j.idm.2024.10.002

Songsong Xie , Yinxia Su , Yanji Zhao , Yaling Du , Zihao Guo , Xiu Gu , Jie Sun , Mohammad Javanbakht , Daihai He , Jiazhen Zhang , Yan Zhang , Kai Wang , Shi Zhao

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.

COVID-19 和流感等呼吸道疾病的爆发引起了全球关注。然而，感染甲型流感的风险是否会受到 SARS-CoV-2 感染史的影响仍不清楚。在本研究中，我们进行了一项检测阴性的病例对照研究，并利用逻辑回归模型分析了 SARS-CoV-2 与甲型流感感染之间的关系。在 258 个符合条件的流感样病症（ILI）患者样本中，我们没有发现 SARS-CoV-2 感染史与甲型流感感染风险之间存在统计学意义上的显著关联。这些发现可能表明，通过接种疫苗或自然免疫获得的 COVID-19 抗体并不能预防流感。

引用次数: 0

Modelling and investigating memory immune responses in infectious disease. Application to influenza a virus and sars-cov-2 reinfections 模拟和研究传染病中的记忆免疫反应。应用于甲型流感病毒和 sars-cov-2 再感染

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling

Pub Date : 2024-10-08 DOI: 10.1016/j.idm.2024.09.009

Mathilde Massard , Bruno Saussereau , Catherine Chirouze , Quentin Lepiller , Raluca Eftimie , Antoine Perasso

Understanding effector and memory immune responses against influenza A virus (IAV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and re-infections is extremely important, given that they are now endemic in the community. The goal of this study is to investigate the role of memory cells and antibodies in the immune responses against IAV and SARS-CoV-2 re-infections. To this end, we adapt a previously-published within-host mathematical model (Sadria & Layton, 2021) for the primary immune response against SARS-CoV-2 infections, by including two types of memory immune cells, i.e., memory CD8⁺ T-cells and memory B-cells, and by parametrising the new model with values specific to the two viruses. We first investigate the long-term dynamics of the model by identifying the virus-free steady states and studying the conditions that ensure the stability of these states. Then, we investigate the transient dynamics of this in-host model by simulating different viral reinfection times: 20 days, 60 days and 400 days after the first encounter with the pathogen. This allows us to highlight which memory immune components have the greatest impact on the viral elimination depending on the time of reinfection. Our results suggest that memory immune responses have a greater impact in the case of IAV infections compared to SARS-CoV-2 infections. Moreover, we observe that the immune response after a secondary infection is more efficient when the reinfection occurs at a shorter time.

鉴于甲型流感病毒（IAV）和严重急性呼吸系统综合症冠状病毒 2（SARS-CoV-2）感染和再感染目前已在社区流行，了解针对它们的效应和记忆免疫反应极为重要。本研究的目的是调查记忆细胞和抗体在针对 IAV 和 SARS-CoV-2 再感染的免疫反应中的作用。为此，我们调整了以前发表的针对 SARS-CoV-2 感染的初级免疫反应的宿主内数学模型（Sadria & Layton, 2021），将两种记忆性免疫细胞（即记忆性 CD8+ T 细胞和记忆性 B 细胞）包括在内，并用两种病毒的特定值对新模型进行参数化。我们首先通过确定无病毒稳定状态和研究确保这些状态稳定的条件来研究模型的长期动力学。然后，我们通过模拟不同的病毒再感染时间（与病原体首次接触后 20 天、60 天和 400 天）来研究这种宿主内模型的瞬时动态。这样，我们就能根据再感染的时间来确定哪些记忆免疫成分对病毒的清除影响最大。我们的研究结果表明，与 SARS-CoV-2 感染相比，记忆性免疫反应对 IAV 感染的影响更大。此外，我们还观察到，当再次感染发生的时间较短时，二次感染后的免疫反应更为有效。

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引用次数: 0