scholarly journals A stochastic model explains the periodicity phenomenon of influenza on network

2021 ◽  
Author(s):  
Hong Yang ◽  
Zhen Jin
Keyword(s):  
Infectious Disease ◽  
Infection Rate ◽  
Disease Model ◽  
Expansion Method ◽  
Spectral Density Function ◽  
Practical Significance ◽  
Related Factors ◽  
Population Number ◽  
Infection Period ◽  
Infectious Disease Model

Abstract Influenza is an infectious disease with obvious periodic changes over time. It is of great practical significance to explore the non-environment-related factors that cause this regularity for influenza control and individual protection. In this paper, based on the randomness of population number and the heterogeneity of population contact, we have established a stochastic infectious disease model about influenza based on the degree of the network, and obtained the power spectral density function by using the van Kampen expansion method of the master equation. The relevant parameters are obtained by fitting the influenza data of sentinel hospitals. The results of the numerical analysis show that: (1) for the infected, the infection period of patients who go to the sentinel hospitals is particularly different from the others who do not; (2) for all the infected, there is an obvious nonlinear relationship between their infection period and the visiting rate of the influenza sentinel hospitals, the infection rate and the degree. Among them, only the infection period of patients who do not go to the sentinel hospitals decreased monotonously with the infection rate (increased monotonously with the visiting rate), while the rest had a non-monotonic relationship.

scholarly journals Obesity as an "infectious" disease

2021 ◽  
Vol 11 (9) ◽  
pp. 534-537
Author(s):  
Daria Żuraw ◽  
Paulina Oleksa ◽  
Mateusz Sobczyk
Keyword(s):  
Infectious Disease ◽  
Disease Model ◽  
Living Environment ◽  
Social Contagion ◽  
Social Discrimination ◽  
Obese People ◽  
Obesity Epidemic ◽  
Global Epidemic ◽  
Infectious Disease Model ◽  
The One

Introduction: Obesity has been recognized as a global epidemic by the WHO, followed by a wealth of empirical evidence supporting its contagiousness. However, the dynamics of the spread of obesity between individuals are rarely studied.  A distinguishing feature of the obesity epidemic is that it is driven by a process of social contagion that cannot be perfectly described by the infectious disease model. There is also social discrimination in the obesity epidemic. Social discrimination against obese people plays quite different roles in two cases: on the one hand, when obesity cannot be eliminated, social discrimination can reduce the number of obese people; on the other hand, when obesity is eradicable, social discrimination can cause it to explode.(1)   Materiał and methods: A literature analysis on obesity epidemic was carried out within the Pubmed, Google scholar and Research Gate platform. The following keywords were used in serach: obesity, epidemy, children, body max index.    Purpose of the work: The aim of the following analysis is to present an obesity as an infectious disease. The steadily increasing percentage of obese people, including children, shows that there is an obesity epidemic. This is the phenomenon of social contagion, which partially explains the concept of homophily, which involves the grouping of people with similar characteristics. Potential explanations are also provided by sharing a living environment with similar access to certain foods and similar opportunities for physical activity, which defines the occurrence of analogous health habits

Improving Computational Models and Practices

2012 ◽  
pp. 432-455
Author(s):  
Iain Barrass ◽  
Joanna Leng
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Computational Models ◽  
Disease Model ◽  
Significant Risk ◽  
Epidemiological Studies ◽  
Health Interventions ◽  
Computational Steering ◽  
Infectious Disease Model

Since infectious diseases pose a significant risk to human health many countries aim to control their spread. Public health bodies faced with a disease threat must understand the disease’s progression and its transmission process. From this understanding it is possible to evaluate public health interventions intended to decrease impacts on the population. Commonly, contingency planning has been achieved through epidemiological studies and the use of relatively simple models. However, computational methods increasingly allow more complex, and potentially more realistic, simulations of various scenarios of the control of the spread of disease. However, understanding computational results from more sophisticated models can pose considerable challenges. A case study of a system combining a complex infectious disease model with interactive visualization and computational steering tools shows some of the opportunities this approach offers to infectious disease control.

scholarly journals Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

BMC Medicine ◽  
2011 ◽  
Vol 9 (1) ◽  
Author(s):  
Juliette Stehlé ◽  
Nicolas Voirin ◽  
Alain Barrat ◽  
Ciro Cattuto ◽  
Vittoria Colizza ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Model ◽  
Dynamic Contact ◽  
Contact Network ◽  
Infectious Disease Model
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