Fuzzy Analytical Hierarchy Process Model for Malaria Control Strategies Prioritization in North-East, Nigeria
Article Sidebar
Page Numbers:
563-588
Digital Object Identifier:
10.58578/mjms.v4i3.11850
Viewed: 1 times
Downloaded: 0 times
LYAS Publisher cordially invites qualified professionals to serve as Editors or Reviewers. Your expertise will make an important contribution to maintaining and strengthening the academic quality of our publications. Interested applicants are kindly requested to complete the application form at the following link: Editors & Reviewers
Please feel free to contact us if you need any further information about the submission process or if you have any additional questions.
Authors:Joel Simon1*, Ahmed Abdulkadir2, Kazeem Eyitayo Lasisi3, A. Bashir4
Copyright :Authors retain copyright and grant the journal right of first publication.
Main Article Content
Abstract
Although the Fuzzy Analytic Hierarchy Process (F-AHP) is widely used to address complex multi-criteria decision-making problems under uncertainty, its application to malaria intervention prioritization in resource-constrained settings, particularly North-East Nigeria, remains limited. This study developed and applied an F-AHP decision-support framework to prioritize malaria control interventions based on epidemiological, economic, operational, and social considerations. A mixed-methods approach involved 18 purposively selected experts, including epidemiologists, medical doctors, and health educators from the six states of North-East Nigeria. Primary data were collected through structured questionnaires, while secondary evidence was drawn from peer-reviewed literature, national malaria control guidelines, and relevant health reports. Five evaluation criteria and five intervention alternatives were assessed using fuzzy pairwise comparison matrices. Expert judgments were represented by triangular fuzzy numbers and defuzzified using the centroid method to generate normalized priority weights and global intervention rankings. All judgment matrices met the recommended consistency threshold (CR ≤ 0.10), supporting the internal consistency of the evaluations. Acceptability emerged as the most influential criterion (0.387), followed by cost-effectiveness (0.283) and health impact (0.200). Among the intervention alternatives, insecticide-treated nets/long-lasting insecticidal nets ranked first, with a global priority weight of 0.346, followed by indoor residual spraying at 0.278. These findings demonstrate that social acceptability, economic efficiency, and health impact are central determinants of malaria intervention priorities in the region. The study contributes to fuzzy multi-criteria decision-making in public health by providing a transparent and systematic framework for incorporating uncertainty into expert judgments. Practically, the framework can support policymakers, malaria control programmes, and public health stakeholders in allocating limited resources and selecting contextually appropriate interventions in North-East Nigeria. It also provides a foundation for integrating stochastic and adaptive approaches into future malaria intervention prioritization under temporal and epidemiological uncertainty.
Citation Metrics:
Downloads
Citation Metrics & Similar Scopus Articles
-
Najafi E. (2027)Analyzing the process of dynamic and tense discourse systems in the poem "katibeh" of Akhavan salesLanguage Related Research, 17(4), 263-291
-
Urazkeldiyeva D.A. (2027)Development of technology for obtaining high-purity sodium chloride with induced impurity removal and process modelingKompleksnoe Ispolzovanie Mineralnogo Syra, 342(3), 56-64
-
Hassanalizadeh S. (2027)Phonological and Morphological Changes of Persian Loanwords in Ottoman Turkish Language in the Process of LocalizationLanguage Related Research, 17(4), 433-467
Article Details
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
References
Abdullah, Hafeez, N., Guzmán Sánchez-Mejorada, C., Torres Ruiz, M. J., Quintero Téllez, R., Alex, E. A., Sidorov, G., & Gelbukh, A. (2026). Enhancing decision intelligence using hybrid machine learning framework with linear programming for enterprise project selection and portfolio optimization. AI, 7(2), 52. https://doi.org/10.3390/ai7020052
Accrombessi, M., Cook, J., Dangbénon, E., Yovogan, B., Akpovi, H., Sovi, A., Adoha, C., Assongba, L., Sidick, A., Akinro, B., Ossè, R., Tokponnon, F. T., Aïkpon, R., Ogouyèmi-Hounto, A., Padonou, G. G., Kleinschmidt, I., Messenger, L., Rowland, M., Ngufor, C., … Akogbéto, M. (2023). Efficacy of pyriproxyfen–pyrethroid long-lasting insecticidal nets (LLINs) and chlorfenapyr–pyrethroid LLINs compared with pyrethroid-only LLINs for malaria control in Benin: A cluster-randomised, superiority trial. The Lancet, 401(10375), 435–446. https://doi.org/10.1016/S0140-6736(22)02319-4
Agomo, C. O., Mishra, N., Olukosi, Y. A., Gupta, R., Kamlesh, K., Aina, O. O., & Awolola, S. T. (2021). Mutations in Pfcrt and Pfmdr1 genes of Plasmodium falciparum isolates from two sites in Northcentral and Southwest Nigeria. Infection, Genetics and Evolution, 95, 105042. https://doi.org/10.1016/j.meegid.2021.105042
Alexander, P. A. (2022). The development of expertise: The journey from acclimation to proficiency. Educational Psychologist, 57(3), 145–165. https://doi.org/10.1080/00461520.2022.2035038
Alsalem, M. A., Alamoodi, A. H., Albahri, O. S., Dawood, K. A., Mohammed, R. T., Alnoor, A., Zaidan, A. A., Albahri, A. S., Zaidan, B. B., Jumaah, F. M., & Al-Obaidi, J. R. (2022). Multi-criteria decision-making for coronavirus disease 2019 applications: A theoretical analysis review. Artificial Intelligence Review, 55(6), 4979–5062. https://doi.org/10.1007/s10462-021-10124-x
Bakır, M., & Atalık, Ö. (2021). Application of fuzzy AHP and fuzzy MARCOS approach for the evaluation of e-service quality in the airline industry. Decision Making: Applications in Management and Engineering, 4(1), 127–152. https://doi.org/10.31181/dmame2104127b
Belton, V., & Stewart, T. J. (2002). Multiple criteria decision analysis: An integrated approach. Kluwer Academic Publishers. https://doi.org/10.1007/978-1-4615-1495-4
Chang, D.-Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655. https://doi.org/10.1016/0377-2217(95)00300-2
Cinelli, M., Kadziński, M., Miebs, G., Gonzalez, M., & Słowiński, R. (2020). Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system. European Journal of Operational Research, 284(2), 633–651. https://doi.org/10.1016/j.ejor.2019.07.056
Demissie, D. B., Fetensa, G., Desta, T., & Tiyare, F. T. (2025). Effectiveness and efficacy of long-lasting insecticidal nets for malaria control in Africa: Systematic review and meta-analysis of randomized controlled trials. International Journal of Environmental Research and Public Health, 22(7), 1045. https://doi.org/10.3390/ijerph22071045
Dengela, D., Seyoum, A., Lucas, B., Johns, B., George, K., Belemvire, A., Caranci, A. T., Norris, L. C., & Fornadel, C. (2018). Multi-country assessment of residual bio-efficacy of insecticides used for indoor residual spraying in malaria control on different surface types: Results from program monitoring in 17 PMI/USAID-supported IRS countries. Parasites & Vectors, 11, 71. https://doi.org/10.1186/s13071-017-2608-4
Firdaus, M. H., Ho Imran, D. S., Puteh, S. E. W., Zhueng, T. J., Abdul Hamid, M. H., Idris, Z. M. D., & Abdul Manaf, M. R. (2026). Strategic resource allocation for malaria elimination in endemic settings: A systematic review of cost-effectiveness evidence. Frontiers in Public Health, 13, 1718225. https://doi.org/10.3389/fpubh.2025.1718225
Gou, X., Xu, X., Deng, F., Zhou, W., & Herrera-Viedma, E. (2024). Medical health resources allocation evaluation in public health emergencies by an improved ORESTE method with linguistic preference orderings. Fuzzy Optimization and Decision Making, 23(1), 1–27. https://doi.org/10.1007/s10700-023-09409-3
Hongoh, V., Hoen, A. G., Aenishaenslin, C., Waaub, J.-P., Bélanger, D., & Michel, P. (2011). Spatially explicit multi-criteria decision analysis for managing vector-borne diseases. International Journal of Health Geographics, 10, 70. https://doi.org/10.1186/1476-072X-10-70
Irish, S. R., Nimmo, D., Bharmel, J., Tripet, F., Müller, P., Manrique-Saide, P., & Moore, S. J. (2024). A review of selective indoor residual spraying for malaria control. Malaria Journal, 23, 252. https://doi.org/10.1186/s12936-024-05053-3
Ishizaka, A., & Siraj, S. (2018). Are multi-criteria decision-making tools useful? An experimental comparative study of three methods. European Journal of Operational Research, 264(2), 462–471. https://doi.org/10.1016/j.ejor.2017.05.041
Kahraman, C., Çevik Onar, S., & Öztayşi, B. (2015). Fuzzy multicriteria decision-making: A literature review. International Journal of Computational Intelligence Systems, 8(4), 637–666. https://doi.org/10.1080/18756891.2015.1046325
La Torre, D. (2022). Multiple criteria decision making in health and medicine. Journal of Multi-Criteria Decision Analysis, 29(1–2), 3–4. https://doi.org/10.1002/mcda.1783
Liu, Y., Eckert, C. M., & Earl, C. (2020). A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications, 161, 113738. https://doi.org/10.1016/j.eswa.2020.113738
Mandali, H., Keighobadi, E., Ebrahimi, H., Moradi Hanifi, S., Ayat, S. M., & Ghashghaei, M. (2025). Machine learning and Bayesian network based on fuzzy AHP framework for risk assessment in process units. Scientific Reports, 15, 39083. https://doi.org/10.1038/s41598-025-25690-1
Mbewe, N. J., Tungu, P. K., Messenger, L. A., Bradley, J., Mangesho, P. E., Shirima, B., Moshi, O., Shayo, M. F., Seif, M., Portwood, N. M., Snetselaar, J., Azizi, S., Magogo, F. S., Mabenga, P., Sudi, W. S., Mlay, G., Kirby, M., Mosha, F., Kisinza, W., … Rowland, M. (2025). A noninferiority cluster randomised evaluation of a broflanilide indoor residual spraying insecticide, VECTRON T500, for malaria vector control in Tanzania. Scientific Reports, 15, 15013. https://doi.org/10.1038/s41598-025-99809-9
Mosha, J. F., Kulkarni, M. A., Lukole, E., Matowo, N. S., Pitt, C., Messenger, L. A., Mallya, E., Jumanne, M., Aziz, T., Kaaya, R., Shirima, B., Isaya, G., Taljaard, M., Martin, J. L., Hashim, R., Thickstun, C., Manjurano, A., Kleinschmidt, I., Mosha, F., … Protopopoff, N. (2022). Effectiveness and cost-effectiveness against malaria of three types of dual-active-ingredient long-lasting insecticidal nets (LLINs) compared with pyrethroid-only LLINs in Tanzania: A four-arm, cluster-randomised trial. The Lancet, 399(10331), 1227–1241. https://doi.org/10.1016/S0140-6736(21)02499-5
Ocan, M., Ojiambo, K. O., Nakalembe, L., Kinalwa, G., Kinengyere, A. A., Nsobya, S., Arinaitwe, E., & Mawejje, H. (2025). The effectiveness of indoor residual spraying for malaria control in sub-Saharan Africa: A systematic protocol review and meta-analysis. International Journal of Environmental Research and Public Health, 22(6), 822. https://doi.org/10.3390/ijerph22060822
Razzaq, O. A., Fahad, M., & Khan, N. A. (2021). Different variants of pandemic and prevention strategies: A prioritizing framework in fuzzy environment. Results in Physics, 28, 104564. https://doi.org/10.1016/j.rinp.2021.104564
Saaty, T. L., & Vargas, L. G. (2012). Models, methods, concepts & applications of the analytic hierarchy process (2nd ed.). Springer. https://doi.org/10.1007/978-1-4614-3597-6
Sayed, H. A. A., Abdelhamid, M. A., Abdelkader, T. K., Lai, Q., Mousa, A. M., & Refai, M. (2024). Machine learning and analytic hierarchy process integration for selecting a sustainable tractor. Scientific Reports, 14, 26735. https://doi.org/10.1038/s41598-024-78023-z
Simon, J., Adamu, A., Abdulkadir, A., & Henry, A. S. (2019). Analytical hierarchy process (AHP) model for prioritizing alternative strategies for malaria control. Asian Journal of Probability and Statistics, 5(1), 1–8. https://doi.org/10.9734/ajpas/2019/v5i130124
Sotoudeh-Anvari, A. (2022). The applications of MCDM methods in COVID-19 pandemic: A state-of-the-art review. Applied Soft Computing, 126, 109238. https://doi.org/10.1016/j.asoc.2022.109238
Thokala, P., & Duenas, A. (2012). Multiple criteria decision analysis for health technology assessment. Value in Health, 15(8), 1172–1181. https://doi.org/10.1016/j.jval.2012.06.015
Uzoka, F.-M. E., Obot, O., Barker, K., & Osuji, J. (2011). An experimental comparison of fuzzy logic and analytic hierarchy process for medical decision support systems. Computer Methods and Programs in Biomedicine, 103(1), 10–27. https://doi.org/10.1016/j.cmpb.2010.06.003
World Health Organization. (2023). World malaria report 2023. https://www.who.int/publications/i/item/9789240086173
Young, A. J., Eaton, W., Worges, M., Hiruy, H., Maxwell, K., Audu, B. M., Marasciulo, M., Nelson, C., Tibenderana, J., & Abeku, T. A. (2022). A practical approach for geographic prioritization and targeting of insecticide-treated net distribution campaigns during public health emergencies and in resource-limited settings. Malaria Journal, 21, 10. https://doi.org/10.1186/s12936-021-04028-y
Zhou, Y., Zhang, W.-X., Tembo, E., Xie, M.-Z., Zhang, S.-S., Wang, X.-R., Wei, T.-T., Feng, X., Zhang, Y.-L., Du, J., Liu, Y.-Q., Zhang, X., Cui, F., & Lu, Q.-B. (2022). Effectiveness of indoor residual spraying on malaria control: A systematic review and meta-analysis. Infectious Diseases of Poverty, 11, 83. https://doi.org/10.1186/s40249-022-01005-8