A Generic Model for Transmission of Mosquito-Borne Diseases Based On Reaction-Diffusion Equations
| dc.contributor.author | Cynthia Kon Mui Lian | |
| dc.date.accessioned | 2026-10-15T02:06:06Z | |
| dc.date.issued | 2018 | |
| dc.description | Simple epidemic models are disease-specific and assume individuals interact in homogeneous environment. In reality, individuals move around in space and they engage with each other and the environment. Geographical spread of infectious diseases is related to movement of individuals and spatial heterogeneity in environment. Mosquito-borne diseases are infections transmitted by the bite of an infectious mosquito, such as malaria, West Nile virus, chikungunya, dengue and Zika virus. One way to incorporate the random movement of mosquito and human population through space in disease modeling is to assume a large-scale form of Brownian motion, leading to reaction-diffusion equations. To address this issue, a spatio-temporal model based on reaction-diffusion equations for transmission of different types of mosquito-borne epidemics is formulated. The intention of this study is to explore the ability of the reaction-diffusion generic model to reproduce literature and published secondary data of actual cases of some mosquito-borne diseases. A system of partial differential equations is formulated. It is discretized and solved using finitedifference method. The generic model is found to be able to reproduce numerical results from literature reaction-diffusion malaria and dengue model. In order to gain general insights, threshold dynamics, basic reproduction number 𝑅, endemic and disease free equilibrium points of the spatio-temporal generic model are analysed and defined. From numerical analysis, it is established that increment in human random movement lowers the disease risk and urbanization aggravates disease risk. In addition, the spatio-temporal generic model can be transformed to a temporal model by setting diffusion rates as zero. The temporal generic model is found to be able to reproduce numerical results from literature deterministic ordinary differential equations malaria and dengue model. Furthermore, the existence of traveling wave solution is explored numerically and the minimum spread speed v for a simulation is determined. In numerical analysis of the generic model, spatial heterogeneity in disease transmission is found to heighten the spread of infection. Moreover, the recruitment rate of mosquito is determined to be a vital parameter because when it is low enough, disease will cease to exist in the population. Finally, the temporal and spatiotemporal generic model is validated by examining its reliability to reproduce actual observed data for malaria, dengue and Zika virus. The performance measure used in this study is Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). In malaria validation, for the temporal model, the best fit values for mosquito death rate M d in the four locations differ suggesting that mosquito longevity is distinct in different locations. In dengue cases validation, it is reported that the recovery rate is different in the studied locations indicating different genotypes. In the Zika virus cases validation, it is determined from the best fit curve that the period an infectious person is capable of transmitting the virus is 1.2 weeks. The overall percentage accuracy of the generic model for all the validation comparison cases is 88%. To conclude, the proposed reaction-diffusion generic model for mosquito-borne diseases can be a platform for software developers to create a useful predictive tool for policymakers, public health and medical officials. | |
| dc.identifier.uri | https://scholarhub.unimas.my/handle/123456789/3082 | |
| dc.language.iso | English | |
| dc.publisher | UNIVERSITI MALAYSIA SARAWAK | |
| dc.relation.ispartofseries | Faculty of Computer Science and Information Technology | |
| dc.subject | Reaction-diffusion model, transmission, mosquito-borne, generic | |
| dc.title | A Generic Model for Transmission of Mosquito-Borne Diseases Based On Reaction-Diffusion Equations | |
| dc.type | PhD |