Insecticide-treated nets (ITNs) are one of the most effective and widely available methods for preventing malaria, and there is interest in understanding the complexities of behavioural drivers of non-use among those with access. This analysis evaluated net use behaviour in Ghana by exploring how several household and environmental variables relate to use among Ghanaians with access to a net.
Survey data from the Ghana 2014 Demographic and Health Survey and the 2016 Malaria Indicator Survey were used to calculate household members’ access to space under a net as well as the proportion of net use conditional on access (NUCA). Geospatial information on cluster location was obtained, as well as average humidex, a measure of how hot it feels, for the month each cluster was surveyed. The relationship between independent variables and net use was assessed via beta-binomial regression models that controlled for spatially correlated random effects using non-Gaussian kriging.
In both surveys, increasing wealth was associated with decreased net use among those with access in households when compared to the poorest category. In 2014, exposure to messages about bed net use for malaria prevention was associated with increased net use (OR 2.5, 95% CrI 1.5–4.2), as was living in a rural area in both 2014 (OR 2.5, 95% CrI 1.5–4.3) and 2016 (OR 1.6, 95% CrI 1.1–2.3). The number of nets per person was not associated with net use in either survey. Model fit was improved for both surveys by including a spatial random effect for cluster, demonstrating some spatial autocorrelation in the proportion of people using a net. Humidex, electricity in the household and IRS were not associated with NUCA.
Net use conditional on access is affected by household characteristics and is also spatially-dependent in Ghana. Setting (whether the household was urban or rural) plays a role, with wealthier and more urban households less likely to use nets when they are available. It will likely be necessary in the future to focus on rural settings, urban settings, and wealth status independently, both to better understand predictors of household net use in these areas and to design more targeted interventions to ensure consistent use of vector control interventions that meet specific needs of the population.