A Novel Cost-Effective Approach for Malaria Control: An Intermittent Preventive Treatment Program
DOI:
https://doi.org/10.5890/JAND.2027.03.006Abstract
Malaria is a significant global health issue, particularly impacting infants and contributing to high mortality rates. The WHO report revealed that malaria control efforts in 2023 suffered from a $4 billion funding shortfall, receiving less than half of the $8.3 billion needed to meet global targets. An intermittent preventive treatment (IPT) program effectively prevents malaria, but no optimal cost-control approach has yet been studied with an IPT program. So, we present an optimal control model for malaria control that incorporates four key control parameters: preventing vertical transmission, an IPT program, treatment, and vector control. We categorize interventions into four groups to evaluate the effectiveness of malaria control: Group 1: single control; Group 2: two controls combined; Group 3: three controls combined; and Group 4: all four controls combined. We obtain that the IPT is the most effective and most cost-effective intervention in Group 1. In Group 2, the combination of IPT and vector control is the most effective, while the combination of vertical transmission prevention and IPT is the most cost-effective. In Group 3, the most effective strategy is the combination of IPT, treatment, and vector control, whereas the most cost-effective strategy is the combination of prevention of vertical transmission, IPT, and treatment. When all four controls are implemented together, we get the highest efficacy index of 97.32%. We obtain that the IPT program is the core control parameter in the most effective and economical policy among all four groups. This research aims to assist policymakers in developing effective malaria control strategies and to allocate resources efficiently for maximum impact.References
[1] World Health Organization (WHO) (2024), World malaria report 2024, World Health Organization (WHO). https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2024.
[2] Rogerson, S.J., Desai, M., Mayor, A., Sicuri, E., Taylor, S.M., and van Eijk, A.M. (2018), Burden, pathology, and costs of malaria in pregnancy: new developments for an old problem, The Lancet Infectious Diseases, 18(4), e107-e118. https://doi.org/10.1016/S1473-3099(18)30066-5.
[3] Kushavaha, S.K. and Sinha, A.K. (2024), Modeling the vertical and horizontal transmission of malaria with intermittent preventive treatment in pregnancy, SeMA Journal, 81(1), 1-27. https://doi.org/10.1007/s40324-024-00370-8.
[4] Figueroa-Romero, A., Pons-Duran, C., and Gonzalez, R. (2022), Drugs for intermittent preventive treatment of malaria in pregnancy: current knowledge and way forward, Tropical Medicine and Infectious Disease, 7(8), 152. https://doi.org/10.3390/tropicalmed7080152.
[5] Abdullah, A., Seadawy, A., and Wang, J. (2018), New mathematical model of vertical transmission and cure of vector-borne diseases and its numerical simulation, Advances in Difference Equations, 2018, 1-15. https://doi.org/10.1186/s13662-018-1516-z.
[6] Desai, M., Ter Kuile, F.O., Nosten, F., McGready, R., Asamoa, K., Brabin, B., and Newman, R.D. (2007), Epidemiology and burden of malaria in pregnancy, The Lancet Infectious Diseases, 7(2), 93-104. https://doi.org/10.1016/S1473-3099(07)70021-X.
[7] World Health Organization (WHO) (2004), A strategic framework for malaria prevention and control during pregnancy in the African region, World Health Organization (WHO).
[8] Bowman, C., Gumel, A.B., Van den Driessche, P., Wu, J., and Zhu, H. (2005), A mathematical model for assessing control strategies against West Nile virus, Bulletin of Mathematical Biology, 67(5), 1107-1133. https://doi.org/10.1016/j.bulm.2005.01.002.
[9] Lashari, A.A. and Zaman, G. (2011), Global dynamics of vector-borne diseases with horizontal transmission in host population, Computers & Mathematics with Applications, 61(4), 745-754. https://doi.org/10.1016/ j.camwa.2010.12.018.
[10] Jain, H. and Sinha, A.K. (2023), Modeling the effect of Wolbachia to control malaria transmission, Expert Systems with Applications, 233, 119769. https://doi.org/10.1016/j.eswa.2023.119769.
[11] Quentin, R., Marc, C., Thierry, L., and Djidjou-Demasse, R. (2022), Human-vector malaria transmission model structured by age, time since infection and waning immunity, Nonlinear Analysis: Real World Applications, 63, 103393. https://doi.org/10.1016/j.nonrwa.2021.103393.
[12] Ross, R. (1910), The Prevention of Malaria, John Murray.
[13] Macdonald, G. (1952), The analysis of equilibrium in malaria, Tropical Diseases Bulletin, 49(9), 813-829.
[14] Patouillard, E., Griffin, J., Bhatt, S., Ghani, A., and Cibulskis, R. (2017), Global investment targets for malaria control and elimination between 2016 and 2030, BMJ Global Health, 2(2), e000176. https://doi.org/10.1136/bmjgh-2016-000176.
[15] Pontryagin, L.S. (2018), Mathematical Theory of Optimal Processes, Routledge. https://doi.org/10.1201/ 9780203749319.
[16] Biswas, S., Mollah, S., and Tiwari, P.K. (2024), Optimal control analysis of thalassemia: modeling the impact of awareness, The European Physical Journal Plus, 139(2), 128. https://doi.org/10.1140/epjp/s13360-024-04926-5.
[17] Rao, C., Wong, K.A., and Athanasiou, T. (2011), An introduction to cost-effectiveness analysis, Evidence Synthesis in Healthcare: A Practical Handbook for Clinicians, Springer London, 141-153. https://doi.org/ 10.1007/978-0-85729-206-3_6.
[18] Olaniyi, S., Falowo, O.D., Okosun, K.O., Mukamuri, M., Obabiyi, O.S., and Adepoju, O.A. (2022), Effect of saturated treatment on malaria spread with optimal intervention, Alexandria Engineering Journal, 65, 443-459. https://doi.org/10.1016/j.aej.2022.09.024.
[19] Olaniyi, S., Abimbade, S.F., Ajala, O.A., and Chuma, F.M. (2024), Efficiency and economic analysis of intervention strategies for recurrent malaria transmission, Quality & Quantity, 58(1), 627-645. https://doi.org/ 10.1007/s11135-023-01664-1.
[20] Khoda, P., Bajiya, V.P., and Prasad, S.N. (2025), Effective strategies toward controlling tuberculosis: optimal control and cost-effectiveness analysis, The European Physical Journal Plus, 140(1), 1-23. https://doi.org/10.1140/epjp/s13360-025-05978-x.
[21] Al Basir, F., Nieto, J.J., Raezah, A.A., and Abraha, T. (2025), Impact of local and global awareness campaigns on malaria transmission: a mathematical model with protected human class and optimal control approach, The European Physical Journal Plus, 140(3), 262. https://doi.org/10.1140/epjp/s13360-025-06206-2.
[22] Bakare, E.A. and Hoskova-Mayerova, S. (2023), Numerical treatment of optimal control theory applied to malaria transmission dynamic model, Quality & Quantity, 57(3), 409-431. https://doi.org/10.1007/s11135-020-01092-5.
[23] Okosun, K.O., Ouifki, R., and Marcus, N. (2013), Optimal control strategies and cost-effectiveness analysis of a malaria model, BioSystems, 111(2), 83-101. http://dx.doi.org/10.1016/j.biosystems.2012.09.008.
[24] Ndii, M.Z. and Adi, Y.A. (2021), Understanding the effects of individual awareness and vector controls on malaria transmission dynamics using multiple optimal control, Chaos, Solitons & Fractals, 153, 111476. https://doi.org/10.1016/j.chaos.2021.111476.
[25] Conteh, L., Shuford, K., Agboraw, E., Kont, M., Kolaczinski, J., and Patouillard, E. (2021), Costs and cost-effectiveness of malaria control interventions: a systematic literature review, Value in Health, 24(8), 1213-1222. https://doi.org/10.1016/j.jval.2021.01.013.
[26] White, M.T., Conteh, L., Cibulskis, R., and Ghani, A.C. (2011), Costs and cost-effectiveness of malaria control interventions: a systematic review, Malaria Journal, 10, 1-14. http://www.malariajournal.com/ content/10/1/337.
[27] Chiyaka, C., Garira, W., and Dube, S. (2009), Effects of treatment and drug resistance on the transmission dynamics of malaria in endemic areas, Theoretical Population Biology, 75(1), 14-29. https://doi.org/ 10.1016/j.tpb.2008.10.002.
[28] Mlugu, E.M., Minzi, O., Kamuhabwa, A.A.R., and Aklillu, E. (2021), Effectiveness of intermittent preventive treatment with dihydroartemisinin-piperaquine against malaria in pregnancy in Tanzania: a randomized controlled trial, Clinical Pharmacology & Therapeutics, 110(6), 1478-1489. https://doi.org/10.1002/cpt.2273.
[29] Akanni, J.O., Fatmawati, Ajao, S., Asamoah, J.K.K., and Abimbade, S.F. (2024), Mathematical model of COVID-19 dynamics in the presence of multiple controls, Quality & Quantity. https://doi.org/10.1007/ s11135-024-01975-x.
[30] Oguntolu, F.A., Peter, O.J., Omede, B.I., Balogun, G.B., and Ayoola, T.A. (2024), Mathematical model on the transmission dynamics of leptospirosis in human and animal population with optimal control strategies using real statistical data, Quality & Quantity, 1-40. https://doi.org/10.1007/s11135-024-02016-3.
[31] Abioye, A.I., Peter, O.J., Addai, E., Oguntolu, F.A., and Ayoola, T.A. (2024), Modeling the impact of control strategies on malaria and COVID-19 coinfection: insights and implications for integrated public health interventions, Quality & Quantity, 58(4), 3475-3495. https://doi.org/10.1007/s11135-023-01813-6.
[32] Bashier, E.B.M. (2022), Development of optimal strategy for controlling transmission dynamics of HBV epidemic model, Journal of Applied Nonlinear Dynamics, 11(2), 415-425. https://doi.org/10.5890/ JAND.2022.06.011.
[33] Barman, S., Jana, S., Majee, S., Das, D.K., and Kar, T.K. (2024), Complex dynamics of a fractional-order epidemic model with saturated media effect, Nonlinear Dynamics, 112(20), 18611-18637. https://doi.org/ 10.1007/s11071-024-09932-x.
[34] Ayele, T.K., Doungmo Goufo, E.F., and Mugisha, S. (2021), Mathematical modeling of HIV/AIDS with optimal control: a case study in Ethiopia, Results in Physics, 26, 104263. https://doi.org/10.1016/ j.rinp.2021.104263.
[35] Melese, A.S., Obsu, L.L., and Gurmu, E.D. (2024), Modelling of HIV pathogens' impact on the AIDS disease transmission with optimal control analysis, Journal of Applied Nonlinear Dynamics, 13(3), 571-582. https://doi.org/10.5890/JAND.2024.09.012.
[36] Fleming, W.H. and Rishel, R.W. (2012), Deterministic and Stochastic Optimal Control (Vol. 1), Springer Science & Business Media. https://doi.org/10.1007/978-1-4612-6380-7.
[37] Coddington, E.A. and Levinson, N. (1955), Theory of Ordinary Differential Equations, McGraw-Hill, New York.
[38] Grass, D., Caulkins, J.P., Feichtinger, G., Tragler, G., and Behrens, D.A. (2008), Optimal Control of Nonlinear Processes, Berlin: Springer. https://doi.org/10.1007/978-3-540-77647-5.
[39] Coddington, E.A. (2012), An Introduction to Ordinary Differential Equations, Courier Corporation.
[40] Niculescu, C.P. and Persson, L.E. (2018), Convex Functions and Their Applications: A Contemporary Approach, Springer, Cham. https://doi.org/10.1007/978-3-319-78337-6.
[41] Dhara, A. and Dutta, J. (2012), Optimality Conditions in Convex Optimization: A Finite-Dimensional View, CRC Press. https://doi.org/10.1007/978-94-007-2247-7.
[42] Melese, A.S., Makinde, O.D., and Obsu, L.L. (2022), Modelling and analysis of pathogens impact on the plant disease transmission with optimal control, Journal of Applied Nonlinear Dynamics, 11(3), 499-521. https://doi.org/10.5890/JAND.2022.09.001.
[43] Falowo, O.D., Olaniyi, S., and Oladipo, A.T. (2023), Optimal control assessment of Rift Valley fever model with vaccination and environmental sanitation in the presence of treatment delay, Modeling Earth Systems and Environment, 9(1), 457-471. https://doi.org/10.1007/s40808-022-01508-1.
[44] Olaniyi, S., Akanni, J.O., and Adepoju, O.A. (2023), Optimal control and cost-effectiveness analysis of an illicit drug use population dynamics, Journal of Applied Nonlinear Dynamics, 12(1), 133-146. https://doi.org/ 10.5890/JAND.2023.03.010.
[45] Ghosh, M., Olaniyi, S., and Obabiyi, O.S. (2020), Mathematical analysis of reinfection and relapse in malaria dynamics, Applied Mathematics and Computation, 373, 125044. https://doi.org/10.1016/j.amc.2020.125044.
[46] Asamoah, J.K.K., Okyere, E., Abidemi, A., Moore, S.E., Sun, G.-Q., Jin, Z., Acheampong, E., and Gordon, J.F. (2022), Optimal control and comprehensive cost-effectiveness analysis for COVID-19, Results in Physics, 33, 105177. https://doi.org/10.1016/j.rinp.2022.105177.
[47] Cantor, S.B. and Ganiats, T.G. (1999), Incremental cost-effectiveness analysis: the optimal strategy depends on the strategy set, Journal of Clinical Epidemiology, 52(6), 517-522. https://doi.org/10.1016/S0895-4356(99)00021-9.
[48] Rahmayani, S.A., Aldila, D., and Handari, B.D. (2021), Cost-effectiveness analysis on measles transmission with vaccination and treatment intervention, AIMS Mathematics, 6(11), 12491-12527. https://doi.org/ 10.3934/math.2021721.
[49] Gervas, H.E. and Hugo, A.K. (2021), Modelling African trypanosomiasis in humans with optimal control and cost-effectiveness analysis, Journal of Applied Mathematics & Informatics, 39(5_6), 895-918. https://doi.org/10.14317/jami.2021.895.
[50] Ambika and Sinha, A.K. (2025), Modeling the impact of double dose vaccination and vertical transmission on hepatitis B with saturated incidence and optimal control, Franklin Open, 12, 100379. https://doi.org/10.1016/ j.fraope.2025.100379.
Article Metrics
Usage tracked since September 1, 2026.