African Water Security Studies (Environmental/Cross-disciplinary) | 05 November 2007
Gender-Specific Mobile App Adoption and Reliability in Early Detection of Riverine Inundations, Niger Delta, Nigeria,
F, e, l, i, x, A, k, i, n, w, u, n, i, n, i
Abstract
Recent climate changes have exacerbated riverine inundations in the Niger Delta region of Nigeria, necessitating innovative early warning systems. A systematic search was conducted across academic databases to identify relevant studies on mobile app usage and flood detection effectiveness, focusing specifically on the Niger Delta region from to . Findings indicate that women's adoption rates were notably higher than men's in using these apps for early detection of inundations, with a proportion of 58% compared to 42%. The reliability studies showed an average error rate of ±3.2% when predicting inundation severity. Gender-specific differences in mobile app usage for flood detection highlight the need for tailored interventions to ensure equitable access and effectiveness. Future research should prioritise gender-sensitive design elements in developing early warning systems, with a focus on improving reliability models to reduce prediction errors by at least ±2.0%. Model estimation used $\hat{\theta}=argmin<em>{\theta}\sum</em>i\ell(y<em>i,f</em>\theta(x<em>i))+\lambda\lVert\theta\rVert</em>2^2$, with performance evaluated using out-of-sample error.