scholarly journals sPop: Age-structured discrete-time population dynamics model in C, Python, and R

F1000Research ◽  
2020 ◽  
Vol 7 ◽  
pp. 1220
Author(s):  
Kamil Erguler
Keyword(s):  
Population Dynamics ◽  
Discrete Time ◽  
Uniform Design ◽  
Disease Spread ◽  
Dependent Manner ◽  
Dynamics Model ◽  
Fixed Rate ◽  
Animal Populations ◽  
Population Dynamics Model ◽  
Age Structured

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-dependent epidemiological processes.

scholarly journals sPop: Age-structured discrete-time population dynamics model in C, Python, and R

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1220 ◽  
Author(s):  
Kamil Erguler
Keyword(s):  
Population Dynamics ◽  
Discrete Time ◽  
Uniform Design ◽  
Disease Spread ◽  
Dependent Manner ◽  
Dynamics Model ◽  
Fixed Rate ◽  
Animal Populations ◽  
Population Dynamics Model ◽  
Age Structured

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed-rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-delayed epidemiological processes.

scholarly journals sPop: Age-structured discrete-time population dynamics model in C, Python, and R

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1220
Author(s):  
Kamil Erguler
Keyword(s):  
Population Dynamics ◽  
Discrete Time ◽  
Uniform Design ◽  
Disease Spread ◽  
Dependent Manner ◽  
Dynamics Model ◽  
Fixed Rate ◽  
Animal Populations ◽  
Population Dynamics Model ◽  
Age Structured

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed-rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-dependent epidemiological processes.

scholarly journals Null Controllability of a Four Stage and Age-Structured Population Dynamics Model

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Amidou Traoré ◽  
Bedr’Eddine Ainseba ◽  
Oumar Traoré
Keyword(s):  
Population Dynamics ◽  
Nonlocal Boundary ◽  
Nonlocal Boundary Conditions ◽  
Null Controllability ◽  
Dynamics Model ◽  
Female Population ◽  
Structured Population ◽  
Population Dynamics Model ◽  
Structured Population Dynamics ◽  
Age Structured

This paper is devoted to study the null controllability properties of a population dynamics model with age structuring and nonlocal boundary conditions. More precisely, we consider a four-stage model with a second derivative with respect to the age variable. The null controllability is related to the extinction of eggs, larvae, and female population. Thus, we estimate a time T to bring eggs, larvae, and female subpopulation density to zero. Our method combines fixed point theorem and Carleman estimate. We end this work with numerical illustrations.

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