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- Title
A Mathematical Model for Transmission of Taeniasis and Neurocysticercosis.
- Authors
Rwabona, Gideon Eustace; Masanja, Verdiana Grace; Mfinanga, Sayoki; Degoot, Abdoelnaser; Mirau, Silas
- Abstract
In this study, we present a mathematical model for the codynamics of taeniasis and neurocysticercosis and rigorously analyze it. To understand the underlying dynamics of the proposed model, basic system properties such as the positivity and boundedness of solutions are investigated through the completing differential process. The basic reproduction number was calculated using the next-generation matrix method, and the analysis showed that when R 0 < 1 , the disease in the community eventually dies out, and when R 0 > 1 , the diseases persist. Local stability of the equilibria was analyzed using the Jacobian matrix, and Lyapunov function techniques were used to determine the global analysis, which showed that the endemic equilibrium point was globally stable when R 0 > 1. On the other hand, the disease-free equilibrium was determined to be globally stable when R 0 < 1. To identify the most influential parameters of the proposed model, partial correlation coefficient techniques were used. The numerical results depict that the model aligns well with the transmission dynamics, which goes through two populations: humans and pigs, whereby the model system stabilizes after some time, showing the validity of the proposed model. Furthermore, the simulations of the proposed model revealed that the shedding habit of infected humans with taeniasis and the bad cooking habit or eating of raw or undercooked pork products have a higher impact on the spread of neurocysticercosis and taeniasis in the community. Hence, this study proposes that in order to control taeniasis and neurocysticercosis, effective disease control measures should primarily prioritize hygienic behaviour and proper cooking of pork meat to the required temperature.
- Subjects
NEUROCYSTICERCOSIS; TAENIASIS; EPIDEMIOLOGICAL models; HYGIENE; PORK
- Publication
Computational & Mathematical Methods, 2024, Vol 2024, p1
- ISSN
2577-7408
- Publication type
Article
- DOI
10.1155/2024/2550598