Bifurcation, sensitivity, and optimal control analysis of onchocerciasis disease transmission model with two groups of infectives and saturated treatment function

被引:7
作者
Ogunmiloro, Oluwatayo Michael [1 ]
Idowu, Amos Sesan [2 ]
机构
[1] Ekiti State Univ, Fac Sci, Dept Math, Ado Iworoko Rd,PMB 5363, Ado Ekiti 360101, Ekiti, Nigeria
[2] Univ Ilorin, Fac Phys Sci, Dept Math, Ilorin, Nigeria
关键词
basic reproduction number R-oc; optimality system; Pontryagin maximum principle (PMP); POPULATION BIOLOGY; DYNAMICS; PSORIASIS;
D O I
10.1002/mma.8317
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A model depicting the transmission of onchocerciasis disease in human host community with two distinct groups of infected humans exhibiting low and high microfilariae (mf) output with saturated treatment function is developed and analyzed. The model equilibrium solutions are obtained, and it is found that the model exhibits forward bifurcation and the effective basic reproduction number (R-oc) governing the spread of the disease is computed by the use of the next generation matrix method. The sensitivity results of model parameters reveal that the rates describing the recruitment of humans, blackflies, onchocerciasis disease transmission, and the biting rate of blackflies are positively sensitive to R-oc, which necessitate the need for controls to be implemented in order to curtail the infectious contact between humans and blackflies in the host environment. To this effect, the model is further transformed into an optimal control problem by applying control strategies of personal protection of using treated bednets and wearing of permethrin-treated cloths c(1), surgical care for humans with body deformation and impaired vision c(2), education campaign c(3), and the use of insecticide c(4), respectively. The existence and uniqueness of the optimal control model are established, and the Pontryagin maximum principle (PMP) is employed to characterize the controls. The optimal control model is solved using the Runge-Kutta numerical scheme via MATI,AB, and the simulations under different control combinations show that each of the controls have its own effect in minimizing onchocerciasis transmission, but the combined effects of the four control strategies proved to be more beneficial towards the elimination of the disease in human and blackfly host community. Also, the simulations of the control profiles reveal that each of these controls are sustained at maximum until 3 months before gradually declining to zero in terminal time (T-*) of 12 months.
引用
收藏
页码:3387 / 3411
页数:25
相关论文
共 58 条
  • [41] Modelling the impact of larviciding on the population dynamics and biting rates of Simulium damnosum (s.l.): implications for vector control as a complementary strategy for onchocerciasis elimination in Africa
    Routledge, Isobel
    Walker, Martin
    Cheke, Robert A.
    Bhatt, Samir
    Nkot, Pierre Baleguel
    Matthews, Graham A.
    Baleguel, Didier
    Dobson, Hans M.
    Wiles, Terry L.
    Basanez, Maria-Gloria
    [J]. PARASITES & VECTORS, 2018, 11
  • [42] Routledge I, 2017, AM J TROP MED HYG, V97, P7
  • [43] A control-based mathematical study on psoriasis dynamics with special emphasis on IL-21 and IFN-γ interaction network
    Roy, Amit Kumar
    Nelson, Mark
    Roy, Priti Kumar
    [J]. MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2021, 44 (17) : 13403 - 13420
  • [44] Roy AK, 2018, MATH BIOSCI ENG, V15, P717, DOI [10.3934/mbe.2018032, 10.3994/mbe.2018032]
  • [45] A MODEL OF THE OPTIMAL IMMUNOTHERAPY OF PSORIASIS BY INTRODUCING IL-10 AND IL-22 INHIBITORS
    Roy, Priti Kumar
    Roy, Amit Kumar
    Khailov, Evgenii N.
    Al Basir, Fahad
    Grigorieva, Ellina, V
    [J]. JOURNAL OF BIOLOGICAL SYSTEMS, 2020, 28 (03) : 609 - 639
  • [46] Analysis of a host-vector dynamics of a dengue disease model with optimal vector control strategy
    Saha, Sangeeta
    Samanta, Guruprasad
    [J]. MATHEMATICS AND COMPUTERS IN SIMULATION, 2022, 195 : 31 - 55
  • [47] Sana M., 2015, SCI INT LABORE, V27, P839
  • [48] Numerical optimal control applied to an epidemiological model
    Schreppel, Christina
    Chudej, Kurt
    [J]. IFAC PAPERSONLINE, 2018, 51 (02): : 1 - 6
  • [49] Sharma S., 2018, International Journal of Dynamics and Control, V6, P1351, DOI [DOI 10.1007/S40435-017-0379-6, 10.1007/s40435-017-0379-6]
  • [50] Optimal control in epidemiology
    Sharomi, Oluwaseun
    Malik, Tufail
    [J]. ANNALS OF OPERATIONS RESEARCH, 2017, 251 (1-2) : 55 - 71