"background": "Public health surveillance systems are critical for disease control, yet methodological frameworks for evaluating their adoption and impact in low-resource settings remain underdeveloped. Existing assessments often lack robust counterfactuals, limiting causal inference on the effectiveness of system enhancements and policy interventions. ", "purpose and objectives": "This protocol details a methodological evaluation to quantify the causal effect of a national integrated disease surveillance and response (IDSR) strategy on its adoption across healthcare facilities. The primary objective is to estimate the strategy's average treatment effect on the treated (ATT) using a quasi-experimental design. ", "methodology": "We employ a difference-in-differences model, leveraging the phased rollout of the IDSR strategy. The model is specified as Y{it = \0 + \1 (Treati \ Postt) + \ + \ +, where Y₈ₓ is the adoption rate in facility i at time t. Facility and time fixed effects are included. Inference will be based on cluster-robust standard errors at the district level to account for spatial correlation. ", "findings": "As a research protocol, this paper does not present empirical results. Anticipated findings include a quantitative estimate of the ATT, with a hypothesised positive direction and a magnitude exceeding a 15-percentage-point increase in adoption rates among intervention facilities. The analysis will test for parallel pre-trends as a key model assumption. ", "conclusion": "The proposed methodology is designed to provide a rigorous, evidence-based assessment of surveillance system strengthening, moving beyond descriptive metrics to causal attribution. ", "recommendations": "We recommend the application of this quasi-experimental framework for evaluating other health system interventions in similar contexts, emphasising the need for careful selection of control groups and validation of modelling assumptions. ", "key words": "health surveillance, impact evaluation, difference-in-differences, causal inference, health systems, Tanzania", "contribution statement": "This
Mwakyembe et al. (Tue,) studied this question.