scholarly journals Facilitating Understanding, Modeling and Simulation of Infectious Disease Epidemics in the Age of COVID-19

2021 ◽  
Vol 9 ◽  
Author(s):  
David M. Rubin ◽  
Shamin Achari ◽  
Craig S. Carlson ◽  
Robyn F. R. Letts ◽  
Adam Pantanowitz ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Differential Equations ◽  
System Dynamics ◽  
Epidemic Modeling ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Complex Models ◽  
Flow Diagrams ◽  
Stock Flow ◽  
Disease Epidemics

Interest in the mathematical modeling of infectious diseases has increased due to the COVID-19 pandemic. However, many medical students do not have the required background in coding or mathematics to engage optimally in this approach. System dynamics is a methodology for implementing mathematical models as easy-to-understand stock-flow diagrams. Remarkably, creating stock-flow diagrams is the same process as creating the equivalent differential equations. Yet, its visual nature makes the process simple and intuitive. We demonstrate the simplicity of system dynamics by applying it to epidemic models including a model of COVID-19 mutation. We then discuss the ease with which far more complex models can be produced by implementing a model comprising eight differential equations of a Chikungunya epidemic from the literature. Finally, we discuss the learning environment in which the teaching of the epidemic modeling occurs. We advocate the widespread use of system dynamics to empower those who are engaged in infectious disease epidemiology, regardless of their mathematical background.

scholarly journals Threshold parameters for a model of epidemic spread among households and workplaces

2009 ◽  
Vol 6 (40) ◽  
pp. 979-987 ◽  
Author(s):  
L. Pellis ◽  
N. M. Ferguson ◽  
C. Fraser
Keyword(s):  
Infectious Disease ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Model Parameters ◽  
Epidemic Spread ◽  
Threshold Parameter ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Complex Models ◽  
The Basic Reproduction Number

The basic reproduction number R 0 is one of the most important concepts in modern infectious disease epidemiology. However, for more realistic and more complex models than those assuming homogeneous mixing in the population, other threshold quantities can be defined that are sometimes more useful and easily derived in terms of model parameters. In this paper, we present a model for the spread of a permanently immunizing infection in a population socially structured into households and workplaces/schools, and we propose and discuss a new household-to-household reproduction number R H for it. We show how R H overcomes some of the limitations of a previously proposed threshold parameter, and we highlight its relationship with the effort required to control an epidemic when interventions are targeted at randomly selected households.

scholarly journals Epidemic Modelling by Ripple-Spreading Network and Genetic Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jian-Qin Liao ◽  
Xiao-Bing Hu ◽  
Ming Wang ◽  
Mark S. Leeson
Keyword(s):  
Infectious Disease ◽  
Genetic Algorithm ◽  
Disease Transmission ◽  
Epidemic Modeling ◽  
Infectious Disease Transmission ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Temporal Features ◽  
Historic Data ◽  
Good Potential

Mathematical analysis and modelling is central to infectious disease epidemiology. This paper, inspired by the natural ripple-spreading phenomenon, proposes a novel ripple-spreading network model for the study of infectious disease transmission. The new epidemic model naturally has good potential for capturing many spatial and temporal features observed in the outbreak of plagues. In particular, using a stochastic ripple-spreading process simulates the effect of random contacts and movements of individuals on the probability of infection well, which is usually a challenging issue in epidemic modeling. Some ripple-spreading related parameters such as threshold and amplifying factor of nodes are ideal to describe the importance of individuals’ physical fitness and immunity. The new model is rich in parameters to incorporate many real factors such as public health service and policies, and it is highly flexible to modifications. A genetic algorithm is used to tune the parameters of the model by referring to historic data of an epidemic. The well-tuned model can then be used for analyzing and forecasting purposes. The effectiveness of the proposed method is illustrated by simulation results.

scholarly journals Mathematical Modelling and Prediction in Infectious Disease Epidemiology

2019 ◽  
Vol 23 (3) ◽  
pp. 328-334
Author(s):  
E. Ya. Yanchevskaya ◽  
O. A. Mesnyankina
Keyword(s):  
Mathematical Modeling ◽  
Infectious Disease ◽  
Mathematical Modelling ◽  
Mathematical Models ◽  
Modern World ◽  
Urgent Problem ◽  
Stages Of Development ◽  
Historical Aspects ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology

Mathematical modeling of diseases is an urgent problem in the modern world. More and more researchers are turning to mathematical models to predict a particular disease, as they help the most correct and accurate study of changes in certain processes occurring in society. Mathematical modeling is indispensable in certain areas of medicine, where real experiments are impossible or difficult, for example, in epidemiology. The article is devoted to the historical aspects of studying the possibilities of mathematical modeling in medicine. The review demonstrates the main stages of development, achievements and prospects of this direction.

Infectious Disease Epidemiology

2005 ◽  
pp. 1327-1362
Author(s):  
Susanne Straif-Bourgeois ◽  
Raoult Ratard
Keyword(s):  
Infectious Disease ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology
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