Evaluating the Effectiveness of Vaccines Using a Regression Discontinuity Design

Area of Science:

• Epidemiology
• Global Health
• Vaccinology

Background:

• Infectious disease epidemiologists and global health researchers critically evaluate disease prevention and control strategies.
• Assessing the impact of vaccines and vaccination programs is a key research aim.
• Regression discontinuity design (RDD) is a quasi-experimental approach rarely used in this field.

Purpose of the Study:

• To describe the features of RDDs and their application in epidemiologic research.
• To illustrate the utility of RDDs for estimating vaccine effects using specific scenarios and examples.
• To advocate for the broader adoption of RDDs in vaccine research and disease control strategy evaluation.

Main Methods:

• Description of the regression discontinuity design (RDD) methodology.
• Application of RDDs to observational data where intervention eligibility is based on a defined cutoff (e.g., age, grade).
• Illustrative examples of RDD application in vaccine effect estimation.

Main Results:

• RDDs are well-suited for estimating vaccine effects due to common eligibility criteria in vaccination programs.
• The approach can address research questions where randomized controlled trials are infeasible or challenging.
• RDDs provide a valuable tool for advancing the understanding of vaccine impacts.

Conclusions:

• Epidemiologic researchers should consider RDDs for evaluating disease prevention and control interventions.
• RDDs can significantly advance future vaccine research by providing robust estimates from observational data.
• This quasi-experimental design offers a viable alternative to RCTs in specific public health contexts.