Identifiability analysis and parameter estimation of a chikungunya model in a spatially continuous domain
Abstract
We investigate the identifiability and estimation of parameters of a chikungunya epidemic transmission model. As a novelty, this model incorporates the spatial mobility of humans described as Brownian random motion. Indeed, it is a factor that has influenced the re-emergence of several epidemic diseases. The displacement of mosquitoes is omitted since it is limited to a few meters. This model couples a mosquito dynamics model and a transmission virus model between humans and mosquitoes populations. The mosquito larvae and the human population are supposed to be observed. The complete model is then composed of a reaction–diffusion system coupled with ordinary differential equations (ODEs). The diffusion is assumed to be local. For such a model, the identifiability analysis is studied at first to ensure that the parameters can be uniquely identified. From the identifiability study, we propose a numerical procedure for obtaining a first estimate of the parameters of the transmission virus model without any knowledge of them.
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BibTeX
@article{zhu2026identifiability,
title = {{Identifiability analysis and parameter estimation of a chikungunya model in a spatially continuous domain}},
author = {Shousheng Zhu and Nathalie Verdière and Lilianne Denis-Vidal and Djalil Kateb},
journal = {Ecological Complexity},
year = {2026},
month = sep,
doi = {10.1016/j.ecocom.2017.12.004},
url = {https://hal.science/hal-02305310v1},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Identifiability analysis and parameter estimation of a chikungunya model in a spatially continuous domain
AU - Shousheng Zhu
AU - Nathalie Verdière
AU - Lilianne Denis-Vidal
AU - Djalil Kateb
PY - 2026
DA - 2026/09/09
JO - Ecological Complexity
DO - 10.1016/j.ecocom.2017.12.004
UR - https://hal.science/hal-02305310v1
AB - We investigate the identifiability and estimation of parameters of a chikungunya epidemic transmission model. As a novelty, this model incorporates the spatial mobility of humans described as Brownian random motion. Indeed, it is a factor that has influenced the re-emergence of several epidemic diseases. The displacement of mosquitoes is omitted since it is limited to a few meters. This model couples a mosquito dynamics model and a transmission virus model between humans and mosquitoes populations. The mosquito larvae and the human population are supposed to be observed. The complete model is then composed of a reaction–diffusion system coupled with ordinary differential equations (ODEs). The diffusion is assumed to be local. For such a model, the identifiability analysis is studied at first to ensure that the parameters can be uniquely identified. From the identifiability study, we propose a numerical procedure for obtaining a first estimate of the parameters of the transmission virus model without any knowledge of them.
SN - 1476-945X
ER -