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Author: search.filters.author.Ahuekwe, E. F.Subject: search.filters.subject.L1014F

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    Performance assessment of Bayesian meta-analytic predictive model on kdr mutation in insecticide-resistant malarial vectors in sub-Saharan Africa.
    (Malaria Journal, 24(1),, 2025) Ahuekwe, E. F.; Taiwo, D. I.
    Mosquito populations’ selective pressure arising from the widespread and prolonged use of insecticides, especially pyrethroids, for both agricultural usages and public health outcomes, has immensely contributed to the emergence and heavily spread of insecticide resistance. In this study, a systematic review identified eight eligible case–control or cohort studies published between 2015 and 2025 across sub-Saharan Africa that reported both allele and/or genotype frequencies of L1014F and L1014S. The predictive performance and inferential robustness of a Bayesianw meta-analytic model were applied and evaluated on two knockdown resistance (kdr) mutations, L1014F and L1014S, in the Anopheles mosquito populations. Using the Markov Chain Monte Carlo (MCMC) sampling to compute pooled concordance statistics, odds ratios, and perform funnel plot asymmetry tests (Egger, Macaskill, Debray). The results revealed that L1014F showed a stronger and more consistent association with phenotypic resistance compared to L1014S, with odds ratios (OR) as high as 4.44 (95% CI 3.40–5.80). However, concordance statistics for both mutations demonstrated wide confidence intervals (L1014F: 0.141; CI − 0.095 to 0.459; L1014S: 0.169; CI − 0.399 to 0.688), indicating moderate predictive reliability. The Bayesian framework effectively synthesized complex and heterogeneous resistance data, confirming the operational relevance of KDR mutations in resistance surveillance. The global significance of these results enhances the predictive analytics in resistance management, such that resistance evolution is temporally and spatially dynamic. The integration of Bayesian modelling into existing entomological surveillance systems shifts the paradigm towards more adaptive and anticipatory management. Although data sparsity and regional heterogeneity warrant cautious interpretation, integrating ecological and thermodynamic variables into predictive models is essential for enhancing future resistance forecasting.
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    Knockdown Resistance Mutations and Pyrethroid Resistance in Anopheles Mosquitoes in Sub-Saharan Africa: A Systematic Review and Meta-analysis
    (Journal of Science and Technology, Research Vol. 7,, 2025) Ahuekwe, E. F.; Taiwo, Damilare Isaiah
    Resistance to pyrethroids is conferred in voltagegated sodium channels through the mechanism of kdr mutation, which also decreases the insecticides' binding affinity to their targets, making them less effective. These mutations affect the efficacy of indoor residual spraying (IRS), which are encoded in the VGSC gene, including the effectiveness of insecticide-treated nets (ITNS). This study represents the first meta-analysis to evaluate the resistance impact of L1014F and L1014S mutations in Anopheles mosquitoes within sub-Saharan Africa. Eight studies that meet with the inclusion criteria were analyzed, encompassing 4,690 mosquito samples. Due to substantial between-study heterogeneity, random effects (R.E) models were applied. The pooled odds ratio (OR) for L1014F (L vs F) was 2.14(95% CI: 1.17-2.93), and for L1014S (S vs F), it was 0.899 (95% CI: 0.297- 1.293), indicating a significant association with resistance. Sensitivity analysis revealed that excluding a study with high variability decreased the ORs, showing the influence of publication bias and small sample size. Funnel plot asymmetry and Egger’s test confirmed the presence of publication bias, affecting effect estimates. Due to high heterogeneity and limited studies, the observed resistance effects of L1014F and L1014S mutations are inconclusive. In addition, validating the relevance of these genotype alleles in insecticide resistance and malaria control initiatives in endemic regions requires extensive research