To measure if a large health campaign led to a significant decrease in a disease rate across an entire community over many years, which specific type of evaluation is required?

The specific type of evaluation required is an Impact Evaluation. An Impact Evaluation is designed to assess the causal effect of a program, policy, or intervention on long-term outcomes or impacts. It aims to determine whether the intervention, in this case, the large health campaign, directly led to the observed fundamental changes, which is a significant decrease in a disease rate across an entire community over many years. This type of evaluation goes beyond simply describing what happened (outputs) or short-term changes (outcomes) to establish if the campaign was responsible for the deeper, sustained changes. The core challenge of an Impact Evaluation is to establish causality, meaning proving that the campaign *caused* the decrease in the disease rate, rather than the change being due to other external factors or pre-existing trends. To achieve this, an Impact Evaluation seeks to construct a counterfactual. The counterfactual represents the hypothetical scenario of what would have happened to the disease rate in the absence of the health campaign. By comparing the actual disease rate in the community after the campaign to this rigorously constructed counterfactual, evaluators can estimate the campaign's net effect. This often involves employing robust research designs, such as experimental methods like Randomized Controlled Trials (if ethical and feasible for community-wide interventions) or quasi-experimental methods like Difference-in-Differences, Regression Discontinuity, or Interrupted Time Series analysis. These methods are used to create valid comparison groups or conditions that closely mimic the counterfactual, allowing for a credible assessment of the campaign's long-term influence on the disease rate.