Relevant bibliographies by topics / Modèle Susceptible-Infected-Recovered (SIR)

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Modèle Susceptible-Infected-Recovered (SIR)'

Author: Grafiati
Published: 8 June 2024
Last updated: 31 July 2025

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Journal articles on the topic "Modèle Susceptible-Infected-Recovered (SIR)"

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Klement, Rainer J., and Harald Walach. "Mathematical models, Pandemic Complexity and the Over-Estimation of Lives Saved by Covid-19 Vaccinations." Futures 148 (September 14, 2022): 103119. https://doi.org/10.5281/zenodo.7079330.

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In a recent modeling study Watson et al. (Lancet Infect Dis 2022;3099:1–10) claim that Covid-19 vaccinations have helped to prevent roughly 14-20 million deaths in 2021. This conclusion is based on an epidemiological susceptible-exposed-infectious-recovered-susceptible (SEIRS) model trained on partially simulated data and extrapolated to a hypothetical scenario in which no vaccinations would have occurred. We point out several caveats of this model and caution against believing in its implications. In particular, the model was calibrated on uncertain data, leading to a potentially false
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Muhammad, Achirul Nanda, Faricha Anifatul, Maghfirotul Ulyah Siti, et al. "The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2900–2910. https://doi.org/10.11591/ijece.v12i3.pp2900-2910.

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The coronavirus (COVID-19) epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the spread of the COVID-19 is understanding its epidemiology through mathematical modeling intervention. Knowledge of epidemic dynamics patterns is an important part of making timely decisions and preparing hospitals for the outbreak peak. In this study, we developed the susceptible-infected-recovered-dead (SIRD) model, which incorporates the key epidemiological parameters to model and estimate the long-term spread of the COVID-19. The prop
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Nguyen, Hoang-Sy, Thu-Ngan T. Phan, and Cong-Danh Huynh. "Deep learning application for real-time prediction of COVID-19 outbreak with susceptible-infected-recovered-deceased model." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 1 (2022): 567–76. https://doi.org/10.11591/ijeecs.v28.i1.pp567-576.

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Due to the complex nature of a pandemic such as COVID-19, forecasting how it would behave is difficult, but it is indeed of utmost necessity. Furthermore, adapting predictive models to different data sets obtained from different countries and areas is necessary, as it can provide a wider view of the global pandemic situation and more information on how models can be improved. Therefore, we combine here the long-short-term memory (LSTM) model and the traditional susceptible-infected-recovered-deceased (SIRD) model for the COVID-19 prediction task in Ho Chi Minh City, Vietnam. In particular, LST
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Marline, Ilha da Silva, Chaves Marques Joice, Otazu Conza Adelaida, De Cezaro Adriano, and Carla Ferreira Nicola Gomes Ana. "The Stiffness Phenomena for the Epidemiological SIR Model: a Numerical Approach." Latin-American Journal of Computing 10, no. 2 (2023): 32–45. https://doi.org/10.5281/zenodo.8067335.

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Mathematical models are among the most successful strategies for predicting the dynamics of a disease spreading in a population. Among them, the so-called compartmental models, where the total population is proportionally divided into compartments, are widely used. The SIR model (Susceptible-Infected-Recovered) is one of them, where the dynamics between the compartments follows a system of nonlinear differential equations. As a result of the non-linearity of the dynamics, it has no analytical solution. Therefore, some numerical methods must be used to obtain an approximate solution. In this co
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Suryo, Widodo, Agus Sulistyono Bambang, and Katminingsih Yuni. "Numerical Simulation of Infectious Disease Spread Using the SIR Model: an Application of Euler's Method." International Journal of Mathematics and Computer Research 13, no. 02 (2025): 4894–98. https://doi.org/10.5281/zenodo.14929055.

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The spread of infectious diseases is a very complex phenomenon and requires mathematical modeling to understand the dynamics of the spread. One of the common approaches used to model the spread of diseases is the SIR (Susceptible-Infected-Recovered) model. This study aims to implement numerical methods, especially the Euler method, to simulate the spread of infectious diseases using the SIR model. This study focuses on the application of Euler's Method to solve differential equations that describe the changes in infected, susceptible, and recovered populations in a finite system. The Euler met
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ElMoussaoui, Ali, Mohamad Hamieh, Hassan Ayoub, Hicham Aboudaya, and Zeinab Hamie. "Impact of Social Behavior on the Dynamic Spread Sars-Cov-2 in Lebanon According to the SIR Model." Euroasia Journal of Mathematics, Engineering, Natural & Medical Sciences 9, no. 24 (2022): 1–18. https://doi.org/10.5281/zenodo.7364583.

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Analyzing the dynamics of Sars-Cov-2 spread in the Lebanese society is what this article mainly aspires and points to, where the study was predicated on a compartmental model, namely SIR, the widely known model in epidemiology. SIR. (Susceptible-Infected-Recovered) materializes a basic conceptional structure for theoretically investigating the virus spread and its dynamics within a community, through focusing on the interaction and communication between infected and recovered people. Consequently, providing the necessary attempts to overcome the epidemic, and diminishes its expansion to rescue
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Madge, Jennifer Y., and Jhelly R. Pérez. "Analysis and simulation of an extended SEIR mathematical model with vaccination for the spread of SARS-COV-2." Selecciones Matemáticas 9, no. 01 (2022): 121–36. http://dx.doi.org/10.17268/sel.mat.2022.02.09.

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This article analyzes the dynamic of an extended SEIR model for the spread of COVID-19 considering a system of 7 differential equations whose stages are susceptible, exposed, infected, quarantined, recovered, dead and vaccinated. The necessary and sufficient conditions are determined for non-negativity, delimitation, existence and uniqueness of the solution of the model, local stability of the equilibrium points and the next generation matrix method. The simulations made in Python complement the qualitative analysis of the mathematical model to conclude the behavior of the virus spread over ti
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Moisés, Filiberto Mora Murillo, Alfredo Mora Murillo Walter, and Pandey Digvijay. "Efficient Prediction and Analysis of the possible evolution of the SARS-CoV-2 in COVID-19 applying the SEIR model in Santo Domingo de los Tsáchilas, Ecuador." Enfoque UTE 11, no. 4 (2020): 101–15. https://doi.org/10.29019/enfoqueute.v11n4.678.

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In Ecuador, in the Santo Domingo de los Tsáchilas province, a Special Operations Committee (SOC) was created to take containment measures against severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). This research deals with an analysis of the possible spread of the SARS-COV-2 virus causing the infectious disease caused by new coronavirus (2019-nCoV) using the Susceptible, Exposed, Infected and Recovered (SEIR) model as a prediction method according to the rigor of the containment measures evaluated. with the acceptability of people through a survey (95 %, CI) in which three par
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Vargas-Pichón, Humberto B., Edson A. Coayla-Teran, and Edgar Tejada-Vásquez. "The SIRD epidemiological model applied to study the spread of the COVID-19 in the Peruvian region of Tacna." Selecciones Matemáticas 9, no. 01 (2022): 137–44. http://dx.doi.org/10.17268/sel.mat.2022.01.10.

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In the present paper, the SIR epidemiological model was used to study the behavior of the spread of the COVID-19 Pandemic in the Tacna Region. To determine the parameters of the model, the information published through social networks by the Regional Health Directorate of the Tacna Region of Peru was used, which was systematized in an EXCEL matrix and then exported to process the information in the System of Scientific Computing Mathematica. As a result, the graphs corresponding to the model referred to the Susceptible, Infected, Recovered and Deceased individuals from the COVID-19 Pandemic in
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Senad, Orhani. "Use of Mathematical Models in Epidemiology to Predict Infectious." Partners Universal Multidisciplinary Research Journal (PUMRJ) 01, no. 04 (2024): 96–111. https://doi.org/10.5281/zenodo.14208781.

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Mathematical models play a key role in epidemiology, providing a powerful tool for predicting and controlling the spread of infectious diseases. This paper examines the use of mathematical models to analyze the dynamics of infectious diseases, assess the impact of health interventions, and predict future outbreaks. Initially, the structure of basic models such as SIR (Susceptible, Infected, Recovered) and their modifications to take into account factors such as population heterogeneity, social networks, and seasonal changes will be discussed. Next, model parameterization and calibration techni
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Dissertations / Theses on the topic "Modèle Susceptible-Infected-Recovered (SIR)"

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Lindamulage, de Silva Olivier. "On the Efficiency of Decentralized Epidemic Management and Competitive Viral Marketing." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0145.

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Cette thèse explore la prise de décision décentralisée dans les dynamiques épidémiques et de marketing viral en utilisant la théorie des jeux afin d'évaluer son efficacité. La thèse commence par une revue des outils mathématiques, mettant l'accent sur la théorie des graphes/jeux. Dans la suite de ce manuscrit, l'analyse de jeu épidémiologique et de compétition en marketing viral est établie. Notamment, dans le chapitre 2 où il est présenté un jeu épidémique en réseau dans lequel chaque joueur (région ou pays) cherche à trouver un compromis entre les pertes socio-économiques et sanitaires, tout
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Gerardi, Davi de Oliveira. "Previsão de séries temporais epidemiológicas usando autômatos celulares e algoritmos genéticos." Universidade Presbiteriana Mackenzie, 2010. http://tede.mackenzie.br/jspui/handle/tede/1386.

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Made available in DSpace on 2016-03-15T19:37:27Z (GMT). No. of bitstreams: 1 Davi de Oliveira Gerardi.pdf: 2216694 bytes, checksum: 5c92a695124c5b7d9e20de8329020701 (MD5) Previous issue date: 2010-08-02<br>SIS (susceptible-infected-susceptible) and SIR (susceptible-infectedremoved) epidemiological models based on probabilistic cellular automaton (PCA) are used in order to simulate the temporal evolution of the number of people infected by dengue in the city of Rio de Janeiro in 2007, and to predict the cases of infection in 2008. In the PCA, three different sizes of lattices and two kinds of
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Kandhway, Kundan. "Optimal Control of Information Epidemics in Homogeneously And Heterogeneously Mixed Populations." Thesis, 2016. http://etd.iisc.ac.in/handle/2005/2670.

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Social networks play an important role in disseminating a piece of information in a population. Companies advertising a newly launched product, movie promotion, political campaigns, social awareness campaigns by governments, charity campaigns by NGOs and crowd funding campaigns by entrepreneurs are a few examples where an entity is interested in disseminating a piece of information in a target population, possibly under resource constraints. In this thesis we model information diffusion in a population using various epidemic models and study optimal campaigning strategies to maximize the reach
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Kandhway, Kundan. "Optimal Control of Information Epidemics in Homogeneously And Heterogeneously Mixed Populations." Thesis, 2016. http://etd.iisc.ernet.in/handle/2005/2670.

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Social networks play an important role in disseminating a piece of information in a population. Companies advertising a newly launched product, movie promotion, political campaigns, social awareness campaigns by governments, charity campaigns by NGOs and crowd funding campaigns by entrepreneurs are a few examples where an entity is interested in disseminating a piece of information in a target population, possibly under resource constraints. In this thesis we model information diffusion in a population using various epidemic models and study optimal campaigning strategies to maximize the reach
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Book chapters on the topic "Modèle Susceptible-Infected-Recovered (SIR)"

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Kalachev, Leonid, Erin L. Landguth, and Jonathan Graham. "Data-Driven Approach to Analysis of SIR (Susceptible-Infected-Removed/ Recovered)-Type Models: The Principle of Parsimony Applied to Epidemics Modeling in the Age of COVID-19." In Handbook of Visual, Experimental and Computational Mathematics. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-93954-0_1-1.

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Arora, Geeta, Tashi Lhamo, and Sarabjit Singh. "A Comprehensive Exploration of Mathematical Models and Machine Learning Techniques for COVID-19." In Advances in Bioinformatics and Biomedical Engineering. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2655-8.ch001.

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Mathematical modeling has proved to be useful in predicting the spread of infectious diseases and assessing the dynamical behavior of contagious diseases, including COVID-19. Various models aid in forecasting COVID-19 spread, such as SEIR (Susceptible – Exposed – Infected – Recovered), SIR (Susceptible – Infected – Recovered), SIRD (Susceptible – Infected – Recovered – Death), and SIRVD (Susceptible – Infected – Recovered – Vaccinated – Death). With recent technological advancements, forecasting of COVID-19 can also be done using machine learning techniques such as SVM (support vector machine)
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Zimeras, Stelios. "Advancements in Epidemiological Modelling and Control Strategies for Infectious Diseases." In Advances in Healthcare Information Systems and Administration. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3260-3.ch002.

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The chapter argues that communicable diseases are typically spread from one person to another through contact with blood and body fluids, breathing in an airborne virus, or being bitten by a carrier of the virus. An epidemiological mathematical model is a model that describes epidemics. When a pandemic occurs, mathematical models play an important role in comparing, planning, implementing, evaluating, and optimizing various methods of detection, prevention, treatment, and control programs, contributing significantly to the fight against the spread and control of infectious diseases. Therefore,
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Huang Weipeng and Provan Gregory. "An Improved State Filter Algorithm for SIR Epidemic Forecasting." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-672-9-524.

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In epidemic modeling, state filtering is an excellent tool for enhancing the performance of traditional epidemic models. We introduce a novel state filter algorithm to further improve the performance of state-of-the-art approaches based on Susceptible-Infected-Recovered (SIR) models. The proposed algorithm merges two techniques, which are typically used separately: linear correction, as seen in the Ensemble Kalman Filter (EnKF), and resampling, as used in the Particle Filter (PF). We compare the inferential accuracy of our approach against the EnKF and the Ensemble Adjustment Kalman Filter (EA
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Schmid-Hempel, Paul. "Between-host dynamics (Epidemiology)." In Evolutionary Parasitology. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198832140.003.0011.

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Epidemiology is the population dynamics of host–parasite systems. The spread of an infective disease is analysed with several tools. The SIR model (susceptible, infected, recovered hosts) is a standard model, with the basic reproductive number (R <sub>0</sub>) as a characteristic. Diseases, in general, spread if R <sub>0</sub> &gt; 1, which suggests a threshold size for host populations, and also for endemic maintenance or periodic outbreaks. Furthermore, spatial heterogeneity or the distribution of infections among hosts affects an epidemic. Individual-based models can follow the fate of infe
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Schramm, Wendelin, David Buchmann, and Hanni Hille. "Can Pandemic Preparedness Benefit from Health-Economic Modelling? The Case for Nipah Virus." In Studies in Health Technology and Informatics. IOS Press, 2025. https://doi.org/10.3233/shti250784.

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Global pandemic preparedness efforts rely on epidemiological models like the SEIR framework (Susceptible, Exposed, Infected, Recovered). However, SEIR models alone may not fully support healthcare decision-making, especially concerning resource allocation and economic impacts. This study integrates health economic (HE) modeling into SEIR to assess the cost-effectiveness of treatments for potential future pandemics, using Nipah virus as a case study. Methods: A structured literature review informed the development of a SEIR-based HE model incorporating cost-effectiveness analysis. The model, bu
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Tudela, Carlos Andres Reyna Vera, and Silvana Martins Ferreira. "BASIC EPIDEMIOLOGICAL MODELS IN A PROPOSAL FOR THE TEMPORAL EVOLUTION OF AIDS." In Health Sciences in Practice: Real-World Applications and Challenges. Seven Editora, 2025. https://doi.org/10.56238/sevened2024.042-008.

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Since the 1980s, there has been great progress in research into the diagnosis, treatment and control of AIDS, but this disease still affects the Brazilian population intensely. The HIV virus acts on the immune system, leading to the emergence of opportunistic diseases. Antiretroviral therapies have allowed patients to maintain a healthy life for a long time. However, some recent research has shown that this virus can be responsible for premature aging in infected people, causing the degenerative nature of the disease to be widely discussed. Just as health scholars have been researching how to
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Conference papers on the topic "Modèle Susceptible-Infected-Recovered (SIR)"

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Padarev, N. I. "FORECASTING THE SPREAD OF BIOLOGICALLY HAZARDOUS AGENTS USING MATHEMATICAL MODELS IN MATLAB." In РАДИАЦИОННАТА БЕЗОПАСНОСТ В СЪВРЕМЕННИЯ СВЯТ. Crossref, 2025. https://doi.org/10.34660/inf.2025.73.66.049.

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This study focuses on forecasting the spread of biologically hazardous agents using mathematical models implemented in MATLAB. By applying the SEIR (Susceptible, Exposed, Infected, Recovered) model and other epidemiological models, the research aims to simulate and predict the dynamics of biological threats in different scenarios. The model allows for the analysis of various factors, such as transmission rates and recovery rates, to assess the potential impact on public health. MATLAB is used as a tool for numerical simulations, providing valuable insights into the effectiveness of preventive
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Arotaritei, Dragos, George Constantin, and Calin Corciova. "MATHEMATICAL MODELS OF MEASLES BY DIFFERENTIAL EQUATIONS IN VIRTUAL EDUCATION." In eLSE 2018. Carol I National Defence University Publishing House, 2018. http://dx.doi.org/10.12753/2066-026x-18-197.

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Compartmental models have proven to be useful in various forms of epidemics: Ebola, dengue fever, swine fever, flu, avian flu, etc. Such models have experienced a great development especially because of the multitude of practical applications, but also due to the many possibilities of software implementation. Although there are a few software tools, for example, EpiModel, they have limitations in modelling and use of language employed in the simulation. Measles can be described as a model with 4 compartments, SEIR, but for a better knowledge of all geographic implications in terms of vaccinati
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