sPop: Age-structured discrete-time population dynamics model in C, Python, and R [version 1; referees: 2 approved]
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 develop...
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doaj-2520a7f0682f41e196ce3334ccd88b502020-11-25T03:06:26ZengF1000 Research LtdF1000Research2046-14022018-08-01710.12688/f1000research.15824.117272sPop: Age-structured discrete-time population dynamics model in C, Python, and R [version 1; referees: 2 approved]Kamil Erguler0Energy, Environment and Water Research Center, The Cyprus Institute, Nicosia, 2121, CyprusThis 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.https://f1000research.com/articles/7-1220/v1 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kamil Erguler |
spellingShingle |
Kamil Erguler sPop: Age-structured discrete-time population dynamics model in C, Python, and R [version 1; referees: 2 approved] F1000Research |
author_facet |
Kamil Erguler |
author_sort |
Kamil Erguler |
title |
sPop: Age-structured discrete-time population dynamics model in C, Python, and R [version 1; referees: 2 approved] |
title_short |
sPop: Age-structured discrete-time population dynamics model in C, Python, and R [version 1; referees: 2 approved] |
title_full |
sPop: Age-structured discrete-time population dynamics model in C, Python, and R [version 1; referees: 2 approved] |
title_fullStr |
sPop: Age-structured discrete-time population dynamics model in C, Python, and R [version 1; referees: 2 approved] |
title_full_unstemmed |
sPop: Age-structured discrete-time population dynamics model in C, Python, and R [version 1; referees: 2 approved] |
title_sort |
spop: age-structured discrete-time population dynamics model in c, python, and r [version 1; referees: 2 approved] |
publisher |
F1000 Research Ltd |
series |
F1000Research |
issn |
2046-1402 |
publishDate |
2018-08-01 |
description |
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. |
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https://f1000research.com/articles/7-1220/v1 |
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AT kamilerguler spopagestructureddiscretetimepopulationdynamicsmodelincpythonandrversion1referees2approved |
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