Modelling and Sensitivity Analysis of Insecticide Susceptibility Status of Anopheles-gambiae Mosquitoes and Community Awareness of Malaria

Auteurs

  • Adamu, Gambo Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria Auteur
  • Ibrahim I. Adamu Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria Auteur
  • Holy-Heavy M. Balami Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria Auteur
  • Ahmed. K. Dotia Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria Auteur
  • Alhaji M. Usman Department of Environmental Health Sciences, Federal University of Health Science Azare, Bauchi Auteur
  • Abdulmumini Husseini Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria Auteur
  • Amidu A. Oyebanjo Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria Auteur

DOI:

https://doi.org/10.62054/ijdm/0203.04

Samenvatting

This study investigates the susceptibility of Anopheles-gambiae mosquitoes to various insecticides and assesses community awareness of malaria. Using modelling and sensitivity analysis, the paper evaluates the effectiveness of different insecticide treatments on mosquito populations. The study also evaluated community awareness and knowledge regarding malaria prevention and control measures. The findings aim to inform public health strategies and improve malaria management in the region. Also, the results highlight critical insights into the resistance patterns of mosquitoes and suggest strategies for enhancing community engagement in malaria reduction efforts. Result of the sensitivity analysis revealed that the expansion of mosquitoes in the community was significantly influenced by the parameters with positive index. As their values increasing, the burden on mosquitoes in the community is reduced by parameters with negative index, which were significant factors affecting insecticide susceptibility in Anopheles-gambiae mosquitoes. Variations in these environmental conditions led to fluctuations in the mosquito’s response to the insecticides. Additionally, based on the findings, it is recommended to implement targeted insecticide resistance management strategies to maintain the efficacy of current control measures. Finally, enhancing community awareness programs on malaria prevention can further aid in reducing transmission rates. Collaboration between local health authorities and researchers is crucial to adapt interventions to the specific needs of the area

Biografieën auteurs

  • Adamu, Gambo, Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria

    Department of Mathematics; Lecturer I

  • Ibrahim I. Adamu, Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria

    Department of Mathematics; Professor

  • Holy-Heavy M. Balami, Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria

    Department of Mathematics; Reader

  • Ahmed. K. Dotia, Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria

    Department of Mathematics; Senior Lecturer

  • Alhaji M. Usman, Department of Environmental Health Sciences, Federal University of Health Science Azare, Bauchi

    Department of Environmental Health Sciences; Reader

  • Abdulmumini Husseini, Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria

    Department of Mathematics; Assistant Lecturer

  • Amidu A. Oyebanjo, Department of Mathematics, Nigerian Army University Biu, Borno State, Nigeria

    Department of Mathematics; Assistant Lecturer

Referenties

Alhaj, M. S., and Nyabadza, F. (2025). A mathematical model of malaria transmission in conflict- affected regions and the implications on malaria interventions. Scientific African, e02746.

Ayalew, A., Molla, Y., and Woldegbreal, A. (2024). Modelling and stability analysis of the

dynamics of malaria disease transmission with some control strategies. In Abstract and

Applied Analysis, 2024(1), 8837744). Wiley.

Brauer, F., Castillo-Chavez, C., Mubayi, A., and Towers, S. (2016). Some models for epidemics

of vector-transmitted diseases. Infectious Disease Modelling, 1(1), 79-87.

Busari, L. O., Raheem, H. O., Iwalewa, Z. O., Fasasi, K. A., and Adeleke, M. A. (2023).

Investigating insecticide susceptibility status of adult mosquitoes against some class of

insecticides in Osogbo metropolis, Osun State, Nigeria. Plos one, 18(5), e0285605.

Chitnis, N., Hyman, J. M., & Cushing, J. M. (2008). Determining important parameters in the

spread of malaria through the sensitivity analysis of a mathematical model. Bulletin of

Mathematical Biology, 70, 1272-1296.

Diekmann, O., Heesterbeek, J. A. P., and Roberts, M. G. (2010). The construction of next

generation matrices for compartmental epidemic models. Journal of the Royal Society

Interface, 7(47), 873-885.

Duguay, C., Mosha, J. F., Lukole, E., Mangalu, D., Thickstun, C., Mallya, E., and Kulkarni, M.

A. (2023). Assessing risk factors for malaria and schistosomiasis among children in Misungwi,

Tanzania, an area of co-endemicity: A mixed methods study. PLOS Global Public Health,

(11), e0002468.

Fagbohun, I. K., Idowu, E. T., Otubanjo, O. A., and Awolola, T. S. (2020). Susceptibility status

of mosquitoes (Diptera: Culicidae) to malathion in Lagos, Nigeria. Animal Research

International, 17(1), 3541-3549.

Feachem, R. G., Chen, I., Akbari, O., Bertozzi-Villa, A., Bhatt, S., Binka, F., and Mpanju-

Shumbusho, W. (2019). Malaria eradication within a generation: ambitious, achievable, and

necessary. The Lancet, 394(10203), 1056-1112.

Haile, G. T., Koya, P. R., and Mosisa Legesse, F. (2025). Sensitivity analysis of a

mathematical model for malaria transmission accounting for infected ignorant humans and

relapse dynamics. Frontiers in Applied Mathematics and Statistics, 10, 1487291.

Helikumi, M., Bisaga, T., Makau, K. A., and Mhlanga, A. (2024). Modelling the Impact of

Human Awareness and Insecticide Use on Malaria Control: A Fractional-Order Approach.

Mathematics, 12(22), 3607.

Kura, I. S., Ahmad, H., Olayemi, I. K., Solomon, D., Ahmad, A. H., and Salim, H. (2022). The

status of knowledge, attitude, and practice in relation to major mosquito borne diseases among

community of Niger State, Nigeria. African Journal of Biomedical Research, 25(3), 339-343.

Lees, R. S., Fornadel, C., Snetselaar, J., Wagman, J., and Spiers, A. (2023). Insecticides for

mosquito control: improving and validating methods to strengthen the evidence base. Insects,

(2), 116.

Murray, J.D. (2001). Mathematical Biology I, An introduction, 3rd Ed. Springer-Verlag Berlin

Heidelberg.

Mwanga, G. G. (2025). Mathematical modelling and optimal control of malaria transmission

with antimalarial drug and insecticide resistance. Journal of Biological Dynamics, 19(1),

Opaginni, D.B., and M.O. Durojaye. (2025). Mathematical Modelling and Analysis of Malaria

Transmission Dynamics with Early and Late Treatment Interventions. Asian Research

Journal of Mathematics. 21 (7), 78-98. https://doi.org/10.9734/arjom/2025/v21i7959.

Pusawang, K., Sattabongkot, J., Saingamsook, J., Zhong, D., Yan, G., Somboon, P., and Sriwichai,P. (2022).

Insecticide Susceptibility Status of Anopheles and Aedes Mosquitoes in Malaria and Dengue Endemic

Areas, Thai– Myanmar Border. Insects, 13(11), 1035.

Ukpai, O. M., and Ekedo, C. M. (2019). Insecticide susceptibility status of Culex

quinquefasciatus Diptera: Culicidae in Umudike, Ikwuano LGA Abia State,Nigeria.

International Journal of Innovation Sciences and Resources. 6(1),114-118.

Van den Driessche, P., and Watmough, J. (2002). Reproduction numbers and sub-threshold

endemic equilibria for compartmental models of disease transmission. Mathematical

biosciences, 180(1-2), 29-48.

Van den Driessche, P. (2017). Reproduction numbers of infectious disease models. Infectious

disease modelling, 2(3), 288-303.

Wako, B. H., Dawed, M. Y., and Obsu, L. L. (2025). Mathematical model analysis of malaria

transmission dynamics with induced complications. Scientific African, 28, e02635.

World Health Organization. (2024). WHO Malaria Policy Advisory Group (MPAG) meeting

report, 4, 5 and 7 March 2024. World Health Organization.

World Health Organization. (2023). World malaria report 2023. meeting report, 18– 20 April 2023.

(Accessed July, 2025), https://iris.who.int/handle/10665/374472.

World Health Organization. (2015). Global technical strategy for malaria 2016-2030. World

Health Organization. (Accessed July, 2025).

##submission.downloads##

Gepubliceerd

2025-09-28

##submission.dataAvailability##

The results of this investigation were supported by collected data within Biu and hypothetical data, found in the reviewed publications.

Citeerhulp

Modelling and Sensitivity Analysis of Insecticide Susceptibility Status of Anopheles-gambiae Mosquitoes and Community Awareness of Malaria. (2025). International Journal of Development Mathematics (IJDM), 2(3), 056-083. https://doi.org/10.62054/ijdm/0203.04