20 papers · ranked by Valyu relevance
Liliana Perez, Suzana Dragicevic
Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a…
Neveen Ali Eshtewy, Ali Forootani, Zahra Ahangari Sisi
Mathematical modeling has become an indispensable tool for understanding, predicting, and controlling the spread of infectious diseases. Over the years, a wide variety of models have been developed to analyze disease dynamics and forecast epidemic trajectories. Deterministic and stochastic frameworks provide…
Carlos Rodríguez Lucatero
Many models of virus propagation in Computer Networks inspired by SIS,SIR, SEIR, etc. epidemic disease propagation mathematical models that can be found in the epidemiology field have been proposed in the last two decades. The purpose of these models has been to determine the conditions under which a virus becomes…
Yunhan Huang, Quanyan Zhu
This review presents and reviews various solved and open problems in developing, analyzing, and mitigating epidemic spreading processes under human decision-making. We provide a review of a range of epidemic models and explain the pros and cons of different epidemic models. We exhibit the art of coupling epidemic…
Sitabhra Sinha
The COronaVIrus Disease 2019 (COVID-19) pandemic that has had the world in its grip from the beginning of 2020, has resulted in an unprecedented level of public interest and media attention focusing on the field of mathematical epidemiology. Ever since the disease came to worldwide attention, numerous models with…
Agniva Datta, Muktish Acharyya
Mathematical modelling of the spread of epidemics has been an interesting challenge in the field of epidemiology. The SIR Model proposed by Kermack and McKendrick in 1927 is a prototypical model of epidemiology. However, it has its limitations. In this paper, we show two independent ways of generalizing this model, the…
Tânia Tomé, Mário J. de Oliveira
We present an analysis of six deterministic models for epidemic spreading. The evolution of the number of individuals of each class is given by ordinary differential equations of the first order in time, which are set up by using the laws of mass action providing the rates of the several processes that define each…
Israël Tankam Chedjou
In plant-disease surveillance, timely and accurate estimation of transmission parameters is critical for informed decision-making. Here, I present a sequential Monte Carlo method that incrementally updates key parameters of a stochastic compartmental epidemic model as new incidence data are collected daily. My approach…
Tom Britton, Désiré Ouédraogo
An SEIRS epidemic with disease fatalities is introduced in a growing population (modelled as a super-critical linear birth and death process). The study of the initial phase of the epidemic is stochastic, while the analysis of the major outbreaks is deterministic. Depending on the values of the parameters, the…
Fred Brauer
A brief description of the importance of communicable diseases in history and the development of mathematical modelling of disease transmission is given. This includes reasons for mathematical modelling, the history of mathematical modelling from the foundations laid in the late nineteenth century to the present, some…
Wayne M. Getz, Richard Salter, Oliver Muellerklein, Hyun S. Yoon + 1 more
Epidemiological models are dominated by SEIR (Susceptible, Exposed, Infected and Removed) dynamical systems formulations and their elaborations. These formulations can be continuous or discrete, deterministic or stochastic, or spatially homogeneous or heterogeneous, the latter often embracing a network formulation.…
Dylan Smith, Kristin Lauro, Dymond Kelly, Joel Fish + 6 more
A physical chemistry lab for undergraduate students described in this report is about applying kinetic models to analyze the spread of COVID-19 in the United States and obtain the reproduction numbers. The susceptible-infectious-recovery (SIR) model and the SIR-vaccinated (SIRV) model are explained to the students and…
Siva Nanthini Shanmugam, Haewon Byeon
The challenge of developing comprehensive mathematical models for guiding public health initiatives in disease control is varied. Creating complex models is essential to understanding the mechanics of the spread of infectious diseases. We reviewed papers that synthesized various mathematical models and analytical…
Carlos Óscar S. Sorzano
This article explores mathematical models for understanding the evolution of contagious diseases. The most widely known set of models are the compartmental ones, which are based on a set of differential equations. But these are not the only models. This review visits many different families of models: deterministic…
Mai Anh T. Bui, Nick Papoulias, Serge Stinckwich, Mikal Ziane + 1 more
Mathematical and computational models are widely used for examining transmission, pathogenicity and propagation of infectious diseases. Software implementation of such models and their accompanied modelling tools do not adhere to well established software engineering principles. These principles include both modularity…
Victoria Chebotaeva, Anish Srinivasan, Paula A. Vasquez
This manuscript introduces a new Erlang-distributed SEIR model. The model incorporates asymptomatic spread through a subdivided exposed class, distinguishing between asymptomatic ( $\hbox{E}_a$) and symptomatic ( $\hbox{E}_s$) cases. The model identifies two key parameters: relative infectiousness, $\beta _{{SA}}$, and…
Scott Greenhalgh, Carly Rozins
For decades, mathematical models of disease transmission have provided researchers and public health officials with critical insights into the progression, control, and prevention of disease spread. Of these models, one of most fundamental is the SIR differential equation model. However, this ubiquitous model has one…
Subhash Kumar Yadav, Yusuf Akhter
In this review, we have discussed the different statistical modeling and prediction techniques for various infectious diseases including the recent pandemic of COVID-19. The distribution fitting, time series modeling along with predictive monitoring approaches, and epidemiological modeling are illustrated. When the…
W.S. Hart, L.F.R. Hochfilzer, N.J. Cunniffe, H. Lee + 2 more
Epidemiological models are routinely used to predict the effects of interventions aimed at reducing the impacts of Ebola epidemics. Most models of interventions targeting symptomatic hosts, such as isolation or treatment, assume that all symptomatic hosts are equally likely to be detected. In other words, following an…
Muhammad Farman, Muhammad Farhan Tabassum, Muhammad Saeed, Nazir Ahmad Chaudhry
Hepatitis B is the main public health problem of the whole world. In epidemiology, mathematical models perform a key role in understanding the dynamics of infectious diseases. This paper proposes Padé approximation (Pa) with Differential Evolution (DE) for obtaining solution of Hepatitis-B model which is nonlinear…