{ "background": "Public health surveillance systems are critical for early detection and response to disease outbreaks. However, rigorous methodological frameworks for evaluating their operational reliability in low-resource settings are lacking, limiting evidence-based improvements.", "purpose and objectives": "This study aimed to develop and apply a novel quasi-experimental design to quantitatively assess the reliability of integrated disease surveillance and response (IDSR) systems at the district level in Tanzania.", "methodology": "A controlled interrupted time series analysis was employed, comparing surveillance metrics from intervention districts implementing a new data verification protocol with matched control districts. System reliability was operationalised as the consistency of case reporting completeness. The primary analysis used a generalised estimating equations model: $Y{it} = \\beta0 + \\beta1 Tt + \\beta2 Xi + \\beta3 (Tt \\times Xi) + \\epsilon{it}$, where $Y{it}$ is completeness for district $i$ at time $t$, $Tt$ is time, and $X_i$ is group assignment. Robust standard errors were clustered at the district level.", "findings": "The intervention was associated with a significant increase in mean reporting completeness. Specifically, completeness in intervention districts improved by 22.4 percentage points (95% CI: 18.1 to 26.7) relative to controls post-implementation. The reliability coefficient, measured by the intraclass correlation coefficient of reported events, also showed a statistically significant improvement.", "conclusion": "The applied quasi-experimental design provides a valid and feasible method for quantifying surveillance system reliability. The findings demonstrate that targeted data quality interventions can substantially enhance the consistency of reporting within existing IDSR frameworks.", "recommendations": "National health authorities should adopt similar methodological evaluations to identify and prioritise investments in surveillance strengthening. The data verification protocol tested here should be considered for scale-up, accompanied by continuous reliability monitoring.", "key words": "health surveillance, system reliability, quasi-experimental design, interrupted time series