Infectious Disease infectious disease basic reproductive number Modeling infectious disease modeling

2012 ◽  
pp. 5347-5357 ◽  
Author(s):  
Angela R. McLean
Keyword(s):  
Infectious Disease ◽  
Disease Modeling ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Infectious Disease Modeling

scholarly journals Huanglongbing Model under the Control Strategy of Discontinuous Removal of Infected Trees

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1164
Author(s):  
Weiwei Ling ◽  
Pinxia Wu ◽  
Xiumei Li ◽  
Liangjin Xie
Keyword(s):  
Infectious Disease ◽  
Global Stability ◽  
Control Strategy ◽  
Theoretical Basis ◽  
Dynamic Properties ◽  
Transmission Mechanism ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Vector Borne ◽  
Citrus Trees

By using differential equations with discontinuous right-hand sides, a dynamic model for vector-borne infectious disease under the discontinuous removal of infected trees was established after understanding the transmission mechanism of Huanglongbing (HLB) disease in citrus trees. Through calculation, the basic reproductive number of the model can be attained and the properties of the model are discussed. On this basis, the existence and global stability of the calculated equilibria are verified. Moreover, it was found that different I0 in the control strategy cannot change the dynamic properties of HLB disease. However, the lower the value of I0, the fewer HLB-infected citrus trees, which provides a theoretical basis for controlling HLB disease and reducing expenditure.

scholarly journals Translation of Real-Time Infectious Disease Modeling into Routine Public Health Practice

2017 ◽  
Vol 23 (5) ◽  
Author(s):  
David J. Muscatello ◽  
Abrar A. Chughtai ◽  
Anita Heywood ◽  
Lauren M. Gardner ◽  
David J. Heslop ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Real Time ◽  
Disease Modeling ◽  
Public Health Practice ◽  
Health Practice ◽  
Infectious Disease Modeling

AN EPIDEMIOLOGICAL MODEL WITH MULTIPLE ENDEMIC STATES

2015 ◽  
Vol 23 (supp01) ◽  
pp. S17-S31
Author(s):  
GEISER VILLAVICENCIO-PULIDO ◽  
IGNACIO BARRADAS ◽  
LUNA BEATRIZ
Keyword(s):  
Infectious Disease ◽  
Backward Bifurcation ◽  
Epidemiological Model ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Force Of Infection

We present a model describing the dynamics of an infectious disease for which the force of infection is diminished through a reaction of the susceptible to the number of infected individuals. We show that, even though the structure of the model is a simple one, different kinds of backward bifurcation can appear for values of the basic reproductive number bigger than one. Under some conditions on the parameters, multiple endemic equilibria may appear for values of the basic reproductive number less or greater than one.

scholarly journals An artificially simulated outbreak of a respiratory infectious disease

2020 ◽  
Author(s):  
Zuiyuan Guo ◽  
Shuang Xu ◽  
Libo Tong ◽  
Botao Dai ◽  
Yuandong Liu ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Attack Rate ◽  
General Pattern ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Developmental Trend ◽  
Collision Model ◽  
Military Camp ◽  
Epidemiological Characteristics

Abstract Background Outbreaks of respiratory infectious diseases often occur in crowded places. To understand the pattern of spread of an outbreak of a respiratory infectious disease and provide a theoretical basis for targeted implementation of scientific prevention and control, we attempted to establish a stochastic model to simulate an outbreak of a respiratory infectious disease at a military camp. This model fits the general pattern of disease transmission and further enriches theories on the transmission dynamics of infectious diseases. Methods We established an enclosed system of 500 people exposed to adenovirus type 7 (ADV 7) in a military camp. During the infection period, the patients transmitted the virus randomly to susceptible people. The spread of the epidemic under militarized management mode was simulated using a computer model named “the random collision model”, and the effects of factors such as the basic reproductive number ( R 0 ), time of isolation of the patients (TOI), interval between onset and isolation (IOI), and immunization rates (IR) on the developmental trend of the epidemic were quantitatively analysed. Results Once the R 0 exceeded 1.5, the median attack rate increased sharply; when R 0 =3, with a delay in the TOI, the attack rate increased gradually and eventually remained stable. When the IOI exceeded 2.3 days, the median attack rate also increased dramatically. When the IR exceeded 0.5, the median attack rate approached zero. The median generation time was 8.26 days, (95% confidence interval [CI]: 7.84-8.69 days). The partial rank correlation coefficients between the attack rate of the epidemic and R 0 , TOI, IOI, and IR were 0.61, 0.17, 0.45, and -0.27, respectively. Conclusions The random collision model not only simulates how an epidemic spreads with superior precision but also allows greater flexibility in setting the activities of the exposure population and different types of infectious diseases, which is conducive to furthering exploration of the epidemiological characteristics of epidemic outbreaks.

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