ArticleBMC public health2025
Bayesian hierarchical spatial ecological model assessing the nexus of vegetation index, insecticide-treated bed-nets and livestock cattle density on lymphatic filariasis transmission.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Recent advances in machine learning and Bayesian modeling for tropical disease prediction, diagnosis, and risk analysis: a scoping review.BMC infectious diseases · 2026Article
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Abstract
Lymphatic filariasis (LF) remains endemic in Nigeria, exhibiting pronounced spatial heterogeneity. This study employed Bayesian spatio-temporal modelling with a beta-binomial likelihood and a modified Besag-York-Mollie (BYM) random effect on national data from 2013, 2015, 2018, and 2021. It assessed ecological and intervention drivers of LF transmission. Results identified persistent high-risk clusters (RR > 2.25) in northern (Zamfara, Kano, Plateau) and southeastern states (Ebonyi, Enugu), which correlated with high prevalence (10.95-21.84%). Notably, insecticide-treated net (ITN) coverage showed counterintuitive positive associations with LF prevalence in 2013 (RR = 5.31, 95% CI: 0.076-3.26) and 2015 (RR = 7.90, 0.056-4.075), although these effects diminished after 2015. Enhanced vegetation index (VIND) and livestock cattle density (LSCA) demonstrated non-significant, temporally unstable effects, reflecting their context-dependent roles in vector ecology. Spatial dependence remained consistently strong (ρ = 0.75-0.82), with 41-54% of transmission variance attributable to location. Spatial and temporal shifts revealed expanding high-risk local government areas (LGAs) (189 in 2013 to 204 in 2018), mainly driven by conflict-affected northeastern states (Borno, Yobe), with partial declines post-2018 observed in southern regions. The pooled model obscured critical dynamics, inflating spatial heterogeneity (σ = 1.29 vs. annual values of 0.80-0.92). We conclude that LF transmission is influenced by spatially structured ecological and intervention interactions, highlighting the need for adaptive, context-specific strategies. Prioritising longitudinal surveillance and conflict-sensitive interventions in high-risk agro-pastoral zones (North Central, Southeast) will enhance Nigeria's elimination efforts.
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