Optimizing MDA and antimalarial treatment in the presence of drug resistance for effective malaria control

Manuela M. Nimpa; Hyacinthe N. Teytsa; Joseph Mbang; Charles S. Wondji; Ramsès Djidjou-Demasse; Manuela M. Nimpa; Hyacinthe N. Teytsa; Joseph Mbang; Charles S. Wondji; Ramsès Djidjou-Demasse

doi:10.3934/mbe.2025069

Mathematical Biosciences and Engineering

2025, Volume 22, Issue 8: 1898-1930. doi: 10.3934/mbe.2025069

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Optimizing MDA and antimalarial treatment in the presence of drug resistance for effective malaria control

1.
Centre for Research in Infectious Diseases, Yaoundé, Cameroon
2.
Department of Mathematics, Faculty of Sciences, University of Yaoundé I, Yaoundé, Cameroon
3.
Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, UK
4.
MIVEGEC, Univ. Montpellier, CNRS, IRD, Montpellier, France
5.
École Polytechnique de Thiès, Thiès, Sénégal

Received: 17 January 2025 Revised: 27 May 2025 Accepted: 05 June 2025 Published: 18 June 2025

Antimalarial drugs are critical for controlling malaria, but the emergence of drug resistance poses a significant challenge to global eradication efforts. This study explores strategies to minimize resistance prevalence and improve malaria control, particularly through the use of mass drug administration (MDA) in combination with antimalarial drugs. We develop a compartmental mathematical model that incorporates asymptomatic, paucisymptomatic, and clinical states of infection and evaluates the impact of resistance mutations on transmission dynamics. The model includes both treated and untreated states among infected and recovered individuals, with a focus on optimizing control strategies through MDA and antimalarial treatment. A global sensitivity analysis identifies the critical factors that influence malaria dynamics, including MDA coverage, treatment access for different infection states, the probability of mutation from treated sensitive human infections, to treated resistant human infections and the initial prevalence of resistance. The model is extended to include optimal control strategies that provide time-dependent control interventions for treatment and MDA. Intuitively, when the mutation rate is relatively low, the optimal strategy combines the use of antimalarial drugs and MDA, with a gradual decrease in antimalarial drug use over time, ensuring sustainable malaria control. In contrast, at higher mutation rates, the strategy prioritizes broader deployment of MDA while significantly reducing reliance on antimalarial to minimize the risk of resistance developing. Numerical simulations of the optimal control problem reinforce the importance of strategic intervention in mitigating drug resistance. This study contributes to understanding the role of MDA and treatment strategies in the control of malaria, with implications for optimizing malaria control programs in endemic regions.
- nonlinear dynamical systems,
- malaria,
- drug resistance,
- mass drug administration,
- optimal control
Citation: Manuela M. Nimpa, Hyacinthe N. Teytsa, Joseph Mbang, Charles S. Wondji, Ramsès Djidjou-Demasse. Optimizing MDA and antimalarial treatment in the presence of drug resistance for effective malaria control[J]. Mathematical Biosciences and Engineering, 2025, 22(8): 1898-1930. doi: 10.3934/mbe.2025069

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Abstract

Antimalarial drugs are critical for controlling malaria, but the emergence of drug resistance poses a significant challenge to global eradication efforts. This study explores strategies to minimize resistance prevalence and improve malaria control, particularly through the use of mass drug administration (MDA) in combination with antimalarial drugs. We develop a compartmental mathematical model that incorporates asymptomatic, paucisymptomatic, and clinical states of infection and evaluates the impact of resistance mutations on transmission dynamics. The model includes both treated and untreated states among infected and recovered individuals, with a focus on optimizing control strategies through MDA and antimalarial treatment. A global sensitivity analysis identifies the critical factors that influence malaria dynamics, including MDA coverage, treatment access for different infection states, the probability of mutation from treated sensitive human infections, to treated resistant human infections and the initial prevalence of resistance. The model is extended to include optimal control strategies that provide time-dependent control interventions for treatment and MDA. Intuitively, when the mutation rate is relatively low, the optimal strategy combines the use of antimalarial drugs and MDA, with a gradual decrease in antimalarial drug use over time, ensuring sustainable malaria control. In contrast, at higher mutation rates, the strategy prioritizes broader deployment of MDA while significantly reducing reliance on antimalarial to minimize the risk of resistance developing. Numerical simulations of the optimal control problem reinforce the importance of strategic intervention in mitigating drug resistance. This study contributes to understanding the role of MDA and treatment strategies in the control of malaria, with implications for optimizing malaria control programs in endemic regions.

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