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

F1000Res. 2018 Aug 8:7:1220. doi: 10.12688/f1000research.15824.3. eCollection 2018.

Abstract

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.

Keywords: C; Python; R; age-specific; deterministic; development; difference equations; dynamic; model; population; stochastic; survival; vector.

Associated data

  • figshare/10.6084/m9.figshare.12957665

Grants and funding

The author(s) declared that no grants were involved in supporting this work.