Epidemiol Health.
2021;43(1):e2021041. 10.4178/epih.e2021041.
Modeling the relationship between malaria prevalence and insecticide-treated bed net coverage in Nigeria using a Bayesian spatial generalized linear mixed model with a Leroux prior
- Affiliations
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- 1Department of Mathematics, University of Medical Sciences, Ondo, Nigeria
- 2Department of Biological Sciences, University of Medical Sciences, Ondo, Nigeria
- 3Department of Physical Sciences, Landmark University, Omu-Aran, Nigeria
- KMID: 2522386
- DOI: http://doi.org/10.4178/epih.e2021041
Abstract
OBJECTIVES
To evaluate malaria transmission in relation to insecticide-treated net (ITN) coverage in Nigeria.
METHODS
We used an exploratory analysis approach to evaluate variation in malaria transmission in relation to ITN distribution in 1,325 Demographic and Health Survey clusters in Nigeria. A Bayesian spatial generalized linear mixed model with a Leroux conditional autoregressive prior for the random effects was used to model the spatial and contextual variation in malaria prevalence and ITN distribution after adjusting for environmental variables.
RESULTS
Spatial smoothed maps showed the nationwide distribution of malaria and ITN. The distribution of ITN varied significantly across the 6 geopolitical zones (p<0.05). The North-East had the least ITN distribution (0.196±0.071), while ITN distribution was highest in the South-South (0.309±0.075). ITN coverage was also higher in rural areas (0.281±0.074) than in urban areas (0.240±0.096, p<0.05). The Bayesian hierarchical regression results showed a non-significant negative relationship between malaria prevalence and ITN coverage, but a significant spatial structured random effect and unstructured random effect. The correlates of malaria transmission included rainfall, maximum temperature, and proximity to water.
CONCLUSIONS
Reduction in malaria transmission was not significantly related to ITN coverage, although much could be achieved in attempts to curtail malaria transmission through enhanced ITN coverage. A multifaceted and integrated approach to malaria control is strongly advocated.
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