Development of a Maintenance Management Cost-Effectiveness Prediction Model for Ageing Bridge Infrastructure: A Case of TARURA, Tanga Region, Tanzania

Bridges managed by the Tanzania Rural and Urban Roads Agency (TARURA) in Tanga Region are maintained largely reactively. About 78% of the annual bridge maintenance budget of TZS 850 million is spent on emergency repairs that cost 2.5 to 4 times more than equivalent preventive work. Existing bridge prediction models mostly predict condition rather than cost, require long inspection histories or large datasets, and omit institutional factors such as budget adequacy. This study therefore developed a maintenance management cost-effectiveness prediction model for ageing bridges in Tanga Region. It adopted a pragmatic philosophy and a convergent parallel mixed-methods design within a single case study of TARURA Tanga. Data were collected through document review, field observation and a structured questionnaire administered to 80 TARURA staff and contractors selected by stratified random and purposive sampling. Factors were ranked with the Relative Importance Index (RII). A multiple linear regression (MLR) model of annual maintenance cost was then estimated from the records of 80 bridges and benchmarked against a Random Forest. Seven of fourteen candidate factors met the RII threshold of 0.74, led by budget adequacy and allocation methods (0.970) and coastal exposure and corrosion (0.945). On a hold-out test set, the MLR achieved R² = 0.833 and MAPE = 13.0%, outperforming the Random Forest (R² = 0.517, MAPE = 22.5%). Structural age had the largest cost-increasing effect, and treatment selection had the largest cost-reducing effect. Each one-level improvement across all seven factors lowered predicted annual cost by about TZS 2.43 million per bridge. The study concludes that institutional factors drive bridge maintenance cost alongside physical deterioration. It also concludes that a transparent model built on routine inspection data can rank interventions by cost-effectiveness under a fixed budget. It recommends that TARURA Tanga shift funds from emergency to preventive maintenance and prioritise corrosion protection for coastal bridges and axle-load control on agricultural routes. It further recommends standardising inspection records to capture the model inputs and adopting the model as a spreadsheet decision tool until a computerised Bridge Management System is developed.