Dynamic modelling and optimal control analysis of a fractional order chikungunya disease model with temperature effects
| dc.contributor.author | Lusekelo, Eva | |
| dc.contributor.author | Helikumi, Mlyashimbi | |
| dc.contributor.author | Kuznetsov, Dmitry | |
| dc.contributor.author | Mushayabasa, Steady | |
| dc.date.accessioned | 2023-03-02T08:28:31Z | |
| dc.date.available | 2023-03-02T08:28:31Z | |
| dc.date.issued | 2023-01-19 | |
| dc.description | This research article published by Elsevier, 2023 | en_US |
| dc.description.abstract | Approximately 1.3 billion inhabitants in 94 countries are estimated to be at risk of chikungunya virus infection. A mechanistic compartmental model based on fractional calculus, the Caputo derivative has been proposed to evaluate the effects of temperature and multiple disease control measures (larvicides use, insecticides and physical barriers) during an outbreak. The proposed model was calibrated based on data from literature and validated with daily chikungunya fever cases reported at Kadmat primary health centre, India. The transmission potential of the disease was examined. Sensitive analyses were conducted through computing partial rank correlation coefficients. Memory effects which are often neglected when mechanistic models are used to model the transmission dynamics of infectious diseases, were found to have a significant effect on the dynamics of chikungunya. | en_US |
| dc.identifier.uri | https://doi.org/10.1016/j.rico.2023.100206 | |
| dc.identifier.uri | https://dspace.nm-aist.ac.tz/handle/20.500.12479/1818 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | Chikungunya fever | en_US |
| dc.subject | Mathematical model | en_US |
| dc.subject | Memory effects | en_US |
| dc.subject | Temperature | en_US |
| dc.subject | Control strategies | en_US |
| dc.title | Dynamic modelling and optimal control analysis of a fractional order chikungunya disease model with temperature effects | en_US |
| dc.type | Article | en_US |