Data-Driven Community Resilience: Evaluating Data Visualization Tools in Tanzania's Natural Disaster Prevention Initiatives

Natural disasters pose significant threats to communities in Tanzania, necessitating effective communication strategies for prevention and resilience building. A mixed-methods approach was employed, including surveys, focus groups, and observational studies to assess user engagement and feedback from communities using data visualization tools. Data visualization tools significantly increased user engagement by 30% (95% CI: 18-42%) compared to traditional communication methods in enhancing community understanding of disaster risks. The study underscores the effectiveness of data visualization in improving community resilience and highlights its potential for broader application in disaster management programmes. Communities should be actively involved in designing and implementing data visualization tools, and continuous user feedback is crucial for their ongoing improvement. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.