On Models of Malaria with Natural Recovery

Main Article Content

Adamu A. K
Bulus S. M
Williams B
Yavalah D

Abstract

This study presents a mathematical model for malaria transmission dynamics, incorporating natural recovery and public awareness/sensitization within the human population. The model evaluates the impact of sensitization alongside conventional control strategies in mitigating malaria spread. Through qualitative analysis, the basic reproduction number was determined to be less than unity, suggesting the feasibility of disease control. Additionally, stability analysis confirmed that the disease-free equilibrium is locally and asymptotically stable. Our findings indicate that, with a combination of natural recovery, public sensitization, and conventional interventions, malaria can be successfully eradicated from the population.

Downloads

Download data is not yet available.

Scopus Citation Data

Data source Crossref
0
citations
Check Secondary Documents in Scopus
Open this article in Scopus, then check the Secondary documents tab. Use Manual Citation Fallback only for counts you have verified manually.
Open in Scopus
Similar Scopus Articles
Scopus
  1. Mirzahosseini M. (2027)
    A Review of Constitutive Modeling of Unsaturated Soils
    Iranian Journal of Geophysics, 20(3), 81-128
  2. Achilova S.S. (2027)
    Activation of the mineralized mass of Central Kyzylkum using acidic wastewater from the oil and fat industry: Freundlich-based adsorption kinetics for fluorine release
    Kompleksnoe Ispolzovanie Mineralnogo Syra, 342(3), 65-79
  3. Berenjian K. (2027)
    Impact of Mild Traumatic Brain Injury (mTBI) on CYP2D6 Activity and the Restorative Effects of Melatonin and Vitamin C Supplementation
    Iranian Journal of Pharmaceutical Research, 26(1)

Article Details

How to Cite
K, A. A., M, B. S., B, W., & D, Y. (2025). On Models of Malaria with Natural Recovery. Asian Journal of Science, Technology, Engineering, and Art, 3(2), 349-363. https://doi.org/10.58578/ajstea.v3i2.5020

References

Adamu, A. K. and Kimbir, A. R. (2013). Modeling the Epidemiology of Malaria and Control with Estimate of the Basic Reproduction Number, Pure and Applied Mathematics Journal. Vol.2, pp. 42-50.

Adamu, A. K., Ochigbo, J., Williams, B and Okorie, C. (2017), Local Stability Analysis of a Susceptible Protected Infected Treated Recovered (SPITR) Mathematical Model for Malaria Disase Dynamics. FUW Trends in Science & Technology Journal, www.ftstjournal.com e-ISSN: 24085162; p-ISSN: 20485170: Vol. 2 No. 1A, pp. 169-174.

Chitnis N., (2005). Using Mathematical Models in Controlling the Spread of Malaria, Ph.D. thesis, Program in Applied Mathematics, University of Arizona, Tucson, AZ

Diekmann, O. and Heesterbeek J. A. P. (2000). Mathematical Epidemiology of Infectious Diseases: “Application of Matrix Theory to Model Building, Analysis and Interpretation” JAMA 271(9): 698-702

Doolan, D. L., Dobano, C., & Baird, J. K. (2009). Acquired immunity to malaria. Clinical Microbiology Reviews, 22(1), 13-36.

Goni, A. N., (2016), Mathematical Model for the Control of Malaria using Education-Based Intervention, M.Sc. Research Project, Modibbo Adama University of Technology Yola

Langhorne, J., Ndungu, F. M., Sponaas, A. M., & Marsh, K. (2008). Immunity to malaria: More questions than answers. Nature Immunology, 9(7), 725-732.

Marsh, K., & Kinyanjui, S. (2006). Immune effector mechanisms in malaria. Parasite Immunology, 28(1-2), 51-60.

Miller, L. H., Baruch, D. I., Marsh, K., & Doumbo, O. K. (2002). The pathogenic basis of malaria. Nature, 415(6872), 673-679.

Brian M. Greenwood, David A. Fidock, Dennis E. Kyle, Stefan H. I. Kappe, Pedro L. Alonso, Frank H. Collins, Patrick E. Duffy. (2008). Malaria: Progress, perils, and prospects for eradication. Journal of Clinical Investigation, 118(4), 1266-1276.

Musa S. and Goni A. N., (2018). Modelling the Effect of Education-Based Intervention in the Control of Malaria, Science World Journal Vol. 13 (No. 4), pp. 1-7; www.scienceworldjournal.org

Olaniyi S., and Obabiyi O. S. (2013). Mathematical Model for Malaria Transmission Dynamics In Human and Mosquito Populations with Nonlinear Forces of Infection, International Journal of Pure and Applied Mathematics, Volume 88 No. 1, 125-156. ISSN: 1314-3395 (on-line version), url: http://www.ijpam.eu

Olliaro, P. (2001). Mode of action and mechanisms of resistance for antimalarial drugs. Pharmacology & Therapeutics, 89(2), 207-219.

Peter, M. M. M., (2010), Modelling the Effects of Multi-Intervention Campaigns for the Malaria Epidemic in Malawi, M.Sc. Thesis, University of Da res Salaam

Schofield, L., & Grau, G. E. (2005). Immunological processes in malaria pathogenesis. Nature Reviews Immunology, 5(9), 722-735.

Smith R. J. and Hove-Musekwa D. S. (2008), Determining effective spraying periods to control malaria via indoor residual spraying in Sub-Saharan Africa. Apllied Maths and Deci Sc. doi:10, Volume 1155. No.74563, Pp 1-19

WHO (2018). World Malaria Report 2018. World Health Organization.

Greenwood, B. M., Fidock, D. A., Kyle, D. E., Kappe, S. H., Alonso, P. L., & Collins, F. H. (2014). Malaria. The Lancet, 383(9918), 723-735.

Williams, T. N. (2006). Human red blood cell polymorphisms and malaria. Current Opinion in Microbiology, 9(4), 388-394.

World Health Organization (2016). Fact Sheet on Malaria. Electronic, www.who.int/mediacentre/factsheets/fs094/en/

World Health Organization (2018), World malaria report, WHO Press, Switzerland. http//www.who.int/malaria

Yang H. M., (2000). Malaria transmission model for different levels of acquired immunity and temperature-dependent parameters (vector), Revista de SatudePublica, 34, pp. 223{231.


Explore Our Journals
Find the most suitable journal for your research. If this journal does not fully align with the scope of your manuscript, we invite you to explore our wider portfolio of journals covering diverse fields of study. Please select one of the journals below to identify the most appropriate publication platform for your work.