Bayesian Hierarchical Model for Cost-Effectiveness Evaluation of Regional Monitoring Networks in Tanzania, 2003

Regional monitoring networks are critical for environmental surveillance in Tanzania. The need to evaluate their cost-effectiveness is paramount, especially considering limited resources. A Bayesian hierarchical model was designed to incorporate spatial variability and heterogeneity across different regions. The model accounts for varying costs and benefits associated with network deployment, using data from previous monitoring efforts. The model estimated that a cost-effectiveness ratio varied by region, ranging from $1.20$ to $1.80$ per unit of environmental impact reduction. The Bayesian hierarchical model provided nuanced insights into the network's performance and highlighted areas where investments could be optimised for maximum benefit. Based on our findings, it is recommended that additional resources be allocated to regions with a higher cost-effectiveness ratio, particularly in high-risk zones identified by the model.