TY - JOUR
T1 - On the mathematical modeling of schistosomiasis transmission dynamics with heterogeneous intermediate host
AU - Madubueze, Chinwendu E.
AU - Chazuka, Z.
AU - Onwubuya, I. O.
AU - Fatimawati, F.
AU - Chukwu, C. W.
N1 - Publisher Copyright:
Copyright © 2022 Madubueze, Chazuka, Onwubuya, Fatimawati and Chukwu.
PY - 2022/10/13
Y1 - 2022/10/13
N2 - Schistosomiasis is a neglected disease affecting almost every region of the world, with its endemicity mainly experience in sub-Saharan Africa. It remains difficult to eradicate due to heterogeneity associated with its transmission mode. A mathematical model of Schistosomiasis integrating heterogeneous host transmission pathways is thus formulated and analyzed to investigate the impact of the disease in the human population. Mathematical analyses are presented, including establishing the existence and uniqueness of solutions, computation of the model equilibria, and the basic reproduction number (R0). Stability analyses of the model equilibrium states show that disease-free and endemic equilibrium points are locally and globally asymptotically stable whenever R0 < 1 and R0>1, respectively. Additionally, bifurcation analysis is carried out to establish the existence of a forward bifurcation around R0 = 1. Using Latin-hypercube sampling, global sensitivity analysis was performed to examine and investigate the most significant model parameters in R0 which drives the infection. The sensitivity analysis result indicates that the snail's natural death rate, cercariae, and miracidia decay rates are the most influential parameters. Furthermore, numerical simulations of the model were done to show time series plots, phase portraits, and 3-D representations of the model and also to visualize the impact of the most sensitive parameters on the disease dynamics. Our numerical findings suggest that reducing the snail population will directly reduce Schistosomiasis transmission within the human population and thus lead to its eradication.
AB - Schistosomiasis is a neglected disease affecting almost every region of the world, with its endemicity mainly experience in sub-Saharan Africa. It remains difficult to eradicate due to heterogeneity associated with its transmission mode. A mathematical model of Schistosomiasis integrating heterogeneous host transmission pathways is thus formulated and analyzed to investigate the impact of the disease in the human population. Mathematical analyses are presented, including establishing the existence and uniqueness of solutions, computation of the model equilibria, and the basic reproduction number (R0). Stability analyses of the model equilibrium states show that disease-free and endemic equilibrium points are locally and globally asymptotically stable whenever R0 < 1 and R0>1, respectively. Additionally, bifurcation analysis is carried out to establish the existence of a forward bifurcation around R0 = 1. Using Latin-hypercube sampling, global sensitivity analysis was performed to examine and investigate the most significant model parameters in R0 which drives the infection. The sensitivity analysis result indicates that the snail's natural death rate, cercariae, and miracidia decay rates are the most influential parameters. Furthermore, numerical simulations of the model were done to show time series plots, phase portraits, and 3-D representations of the model and also to visualize the impact of the most sensitive parameters on the disease dynamics. Our numerical findings suggest that reducing the snail population will directly reduce Schistosomiasis transmission within the human population and thus lead to its eradication.
KW - global stability
KW - heterogeneous host
KW - mathematical analysis
KW - schistosomiasis
KW - sensitivity analysis
UR - https://www.scopus.com/pages/publications/85140927626
UR - https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2022.1020161/full
U2 - 10.3389/fams.2022.1020161
DO - 10.3389/fams.2022.1020161
M3 - Article
AN - SCOPUS:85140927626
SN - 2297-4687
VL - 8
JO - Frontiers in Applied Mathematics and Statistics
JF - Frontiers in Applied Mathematics and Statistics
M1 - 1020161
ER -