Effective Control Strategies for Sex-Structured Transmission Dynamics of Visceral Leishmaniasis
Abstract
1. Introduction
2. Methods
- 1.
- Preventive mechanisms through the use of ITNs.The WHO-recommended VL preventive strategies include the use of insecticide-treated sandfly nets [25]. In order to curb the spread of VL, in a study by [26], a breakthrough in reducing the spread of VL was achieved after the introduction of ITNs. Due to its practical applicability, we are considering the use of ITNs as one of the control strategies. Using ITNs reduces the probability of humans being bitten. Furthermore, since the nets are treated with insecticides, they kill vectors. Therefore, we used the following two assumptions formulated in [20,27].
- (a)
- The mathematical expression for the use of ITNs in reducing the human–vector contact rate is described by the following relation:
- (b)
- Since bed nets are treated with insecticides, they have the capacity to kill vectors that land on the net. Hence, if the natural death rate of vectors is , ITNs usage increases the sandfly death rate by . This is mathematically represented by
- 2.
- Vector control: The incidence rate of VL is increasing in some endemic regions of the world, including Kenya, Ethiopia, and Sudan [28], as a result of the serious side effects of current VL medications and the lack of an effective vaccination. Programs to eradicate leishmaniasis, therefore, mainly rely on vector control using insecticides and environmental management. The goal of environmental management is to eliminate or make places undesirable for sandflies to nest and rest, as well as to kill the pre-adult stage of vectors. Tree stump clearance, soil and crack filling, the routine cleaning of the per-domicile area and animal shelters, and trash removal are common vector control methods in environmental management [29]. Additionally, the most effective method of controlling sandflies is the use of chemical interventions such as indoor residual spraying (IRS), which is associated with a decrease in the lifespan of sandflies, leading to a subsequent decline in their population [12,30,31]. By reducing the lifespan of sandflies, the vector is less likely to survive long enough to acquire infection and to infect a host again. As the death rate of vectors increases, they spend less time in an infected state. Taking this into account, we incorporate a time-dependent control that represents an additional vector control effort through the use of environmental management and indoor residual spraying into the VL model. If the current natural mortality rate of vectors is , then the number of additional deaths of non-adult sandflies after the use of vector control interventions will be , where represents the effectiveness of insecticide spraying in killing sandflies. This implies that of Equation (4) will be updated by an additional term, , such thatFurthermore, the recruitment rate of vectors () will decrease by , as the application of insecticides is expected to destroy the breeding sites and kills the non-adult-stage sandflies. Hence, is updated by , where . Note here that and must satisfy the condition that
- 3.
- Treating infected individuals: Treatment is an important method to recover from the disease. Treatment has an effective role in preventing and controlling the spreading of the disease. Proper and timely treatment can reduce the total prevalence of the disease. However, treatment alone will not be enough to truly halt the transmission of VL [32,33]. The efficacy of VL drugs varies from one endemic area to another. We assume that the efficacy of VL drug is . If and are the recovery rates of male and female human host, then the mathematical expression for the formulation of controls with an additional treatment effort () is given by: and . Where represents the natural recovery rate of the male human host, represents the natural recovery of female human hosts, and is a modification parameter, as stated before, with for every time .
- 4.
- Culling infected animals: Dogs are the most important reservoirs of VL infection in domestic settings, while other animals can serve as a source of VL infection [24]. As a result, it is believed that having infected dogs increases the risk of VL in people in endemic areas. Culling leishmania-seropositive reservoirs such as dogs has been recommended as a control measure in many VL endemic countries [34]. It is indicated in [17,20] that the culling of infected animals is a cost-effective VL control strategy, together with other interventions. Hence, we consider the culling of infected dogs as a control strategy. Given and , which represent the natural and disease-induced mortality rates of infected dogs, provides the mathematical expression for the rate at which infected dogs diminish as a result of further culling effort , where for every time .
2.1. Model Analysis
2.1.1. Boundedness and Positivity of Solutions with Constant Control Parameters
2.1.2. Disease-Free Equilibrium Point (DFE)
2.1.3. Basic Reproduction Number with Constant Controls
- 1.
- The quantity is associated with the contribution of infected reservoirs;
- 2.
- The quantity is associated with the contribution of infected male humans;
- 3.
- The quantity is associated with the contribution of infected female humans in the spread of the disease at its initial stage.
2.2. Optimal Control
2.2.1. Definition of Cost Function
2.2.2. Existence and Characterization of Optimal Control Solution
- A.
- The set of all solutions to the system (6) with corresponding control functions in is non-empty.
- B.
- The state system can be written as a linear function of the control variables with coefficients dependent on time and the state variables.
- C.
- The integrand L in (12) from objective functional with is convex on and satisfies where and .In order to establish condition A, we refer to Picard–Lindelöf’s theorem from [38]. If the solutions to the state equations are bounded, and the state equations are continuous and Lipschitz with respect to the state variables, then there exists a unique solution to the system for every admissible control . The total male human population is bounded between and , while the female human, reservoir, and sandfly populations are bounded above , , and , respectively, with lower bounds , , and . With these bounds, the state system is continuous, bounded, and Lipschitz with respect to the state variables, proving condition A holds. Condition B is verified by observing the linear dependence of the state equations on controls , , and . Finally, to verify condition C by definition from [39,40] any constant, linear and quadratic functions are convex. So , ,, and are convex on . Since linear combination of convex functions are also convex, the integrand is convex on .To prove the bound on the L, we adopted the method in [41]. We note that, by the definition of , we have
2.2.3. Characterization of Optimal Control Solution
- 1.
- Optimality Conditions: The minimization of the Hamiltonian H, with respect to the control variables , is the first condition that we will examine from the Pontryagin’s Maximum principle. Since the cost function is convex, if the optimal control occurs in the interior region, we must have for . Therefore
- (i)
- For the control , we must have
- (ii)
- For the control , we must have
- (iii)
- For the control , we must have
- (iv)
- For the control , we must have
Furthermore, therefore, the optimal controls on the given bounded intervals are given by - 2.
- The adjoint (co-state) equations: According to the second condition of Pontryagin’s Maximum Principle, we need to have the optimal controls for each . As a result, we must compute and resolve the system,
- 3.
- The transversality conditions
2.3. Numerical Methods
Algorithm 1: Forward–Backward–Sweep Algorithm |
Para. | Description | Unit | Value | Source |
---|---|---|---|---|
recruitment rate of human male population | persons week−1 | [21] | ||
recruitment rate of human female population | persons week−1 | [21] | ||
natural mortality rate of human | week−1 | [21] | ||
natural mortality rate of reservoirs(dog) | week−1 | [21] | ||
natural mortality rate of sandflies | week−1 | [49] | ||
progression rate of human male from to | proportion | 0.147 | [26] | |
progression rate of human female from to | proportion | 0.147 | [26] | |
recovery rate of human male from asymptomatic stage | week−1 | 0.027525 | [26] | |
recovery rate of human female from asymptomatic stage | week−1 | 0.020094 | [26] | |
recovery rate of human male from symptomatic stage | week−1 | 0.028902 | [26] | |
recovery rate of human female from symptomatic stage | week−1 | 0.021098 | [26] | |
rate of losing immunity of human males | week−1 | 0.001527 | [26] | |
rate of losing immunity of females | week−1 | 0.002077 | [26] | |
rate of losing immunity of reservoirs | week−1 | 0.055556 | [50] | |
inverse of incubation period of human population | week−1 | 0.0625 | [1] | |
recruitment rate of reservoir (animal) population | reservoirs week−1 | 491.04294 | [21] | |
recruitment rate of vector (sandfly) population | vectors week−1 | 691.95421 | [21] | |
p | proportion of exposed human male who join Am from Em | proportion | 0.64033 | [21] |
q | proportion of exposed human female who join Am from Em | proportion | 0.16619 | [21] |
the probability that becomes infected by a single bite | proportion | 0.01311 | [21] | |
the probability that becomes infected by a single bite | proportion | 0.15080 | [21] | |
the probability of becomes infected from human | proportion | 0.16093 | [21] | |
the probability of becomes infected from reservoir | proportion | 0.05090 | [21] | |
the number of bites in which a reservoir hosts receive | per head week−1 | 4.93540 | [21] | |
the number of times a single vector feeds on a reservoir | per head week−1 | 1.06446 | [21] | |
modification parameter | proportion | 1.07488 | [21] | |
modification parameter | proportion | 1.24648 | [21] | |
modification parameter | proportion | 4.93806 | [21] | |
disease-induced death rate of human male | proportion | 0.000035 | [21] | |
disease-induced death rate of human female | proportion | 0.00264 | [21] | |
recovery rate of reservoirs | week−1 | 0.00516 | [21] | |
disease-induced death rate of reservoir | proportion | 0.00031 | [21] | |
capability of ITNs to kill sandflies | proportion | 0.25 | Assumed | |
effectiveness of insecticide spraying in killing sandflies | proportion | 0.55 | Assumed | |
efficacy of VL drugs | proportion | Assumed | ||
modification parameter | proportion | Assumed | ||
modification parameter | proportion | Assumed |
3. Results and Discussion
3.1. Various Interventions/Control Strategies
3.1.1. Strategy A (All Controls, i.e., the Combination of the Use of Treated Bed Nets, Vector Control, the Treatment of Infected Individuals, and the Culling of Infected Reservoir Animals)
3.1.2. Strategy B (the Combination of the Use of Medical Treatment for Infected Individuals and Animal Culling Without Using Insecticide-Treated Bed Nets or Vector Controls ( and ))
3.1.3. Strategy C (the Combination of the Use of Insecticide-Treated Bed Nets and Vector Control Without the Use of Medical Treatment and Animal Culling ( and ))
3.1.4. Strategy D (the Combination of Use of Vector Control and Animal Culling Without Insecticide-Treated Bed Nets or Medical Treatment ( and ))
3.1.5. Strategy E (the Combination of the Use of Insecticide-Treated Bed Nets, Medical Treatment, and Animal Culling Without the Use of Vector Control ())
3.1.6. Strategy F (the Combination of the Use of Insecticide-Treated Bed Nets, Vector Control, and Medical Treatment Without the Use of Animal Culling ())
3.1.7. Cost-Effectiveness Analysis of the Proposed Strategies
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Parameters | Description of Parameters |
---|---|
recruitment rate of male and female human population | |
recruitment rate of reservoir (animal), vector (sandfly) population | |
life expectancy of human, vector (sandfly), reservoir population | |
force of infection for human, sandfly, and reservoir population | |
progression rate from asymptomatic to symptomatic | |
disease-induced death rates of human male, human female, and reservoir population | |
recovery rate of male and female human population from asymptomatic | |
recovery rate of male and female human population from symptomatic | |
inverse of incubation period in human population | |
lose of immunity rate of human male, human female, and reservoir population | |
recovery rate of reservoirs | |
p | the proportion of exposed human males who join the class from the class |
q | the proportion of exposed human females who join the class from the class |
, | the probability that susceptible humans and reservoirs become infected |
through a single bite from infected sandflies, respectively | |
, | the probability that a susceptible sandfly becomes infected when |
feeding on an infected human or an infected reservoir, respectively | |
the number of bites that a reservoir host receives per week | |
the number of times a single vector feeds on a reservoir host | |
modification parameters | |
the capability of insecticide-treated bed nets and insecticide spraying to kill sandflies | |
modification parameters |
Strategies | Total Infection Averted | Cost (USD) |
---|---|---|
D | 33,743 | |
B | 123,876.3 | |
C | 153,269.1 | |
E | 163,154.8 | |
F | 163,299.81 | |
A | 163,340.15 |
Strategies | Total Infection Averted | Cost (USD) | ICER |
---|---|---|---|
D | 33,743 | 56,574.69 | |
B | 123,876.3 | ||
C | 153,269.1 | −68,393.28 | |
E | 163,154.8 | ||
F | 163,299.81 | −120,626.16 | |
A | 163,340.15 |
Strategies | Total Infection Averted | Cost (USD) | ICER |
---|---|---|---|
B | 123,876.3 | ||
C | 153,269.1 | −31,785.68 | |
E | 163,154.8 | ||
F | 163,299.81 | −120,626.16 | |
A | 163,340.15 | −27,416.96 |
Strategies | Total Infection Averted | Cost (USD) | ICER |
---|---|---|---|
C | 153,269.1 | ||
E | 163,154.8 | ||
F | 163,299.81 | −120,626.16 | |
A | 163,340.15 | −27,416.96 |
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Awoke, T.D.; Kassa, S.M.; Morupisi, K.S.; Tsidu, G.M. Effective Control Strategies for Sex-Structured Transmission Dynamics of Visceral Leishmaniasis. Mathematics 2025, 13, 1929. https://doi.org/10.3390/math13121929
Awoke TD, Kassa SM, Morupisi KS, Tsidu GM. Effective Control Strategies for Sex-Structured Transmission Dynamics of Visceral Leishmaniasis. Mathematics. 2025; 13(12):1929. https://doi.org/10.3390/math13121929
Chicago/Turabian StyleAwoke, Temesgen Debas, Semu Mitiku Kassa, Kgomotso Susan Morupisi, and Gizaw Mengistu Tsidu. 2025. "Effective Control Strategies for Sex-Structured Transmission Dynamics of Visceral Leishmaniasis" Mathematics 13, no. 12: 1929. https://doi.org/10.3390/math13121929
APA StyleAwoke, T. D., Kassa, S. M., Morupisi, K. S., & Tsidu, G. M. (2025). Effective Control Strategies for Sex-Structured Transmission Dynamics of Visceral Leishmaniasis. Mathematics, 13(12), 1929. https://doi.org/10.3390/math13121929