Modern approaches to predicting vaccine hesitancy: A scoping review

Motivated by the disproportionate burden of infectious diseases on vulnerable populations and the risk of future pandemics, we conducted a scoping review to analyze the state of the literature about "vaccine uptake indices," defined as models that predict vaccination rates by geospatial area. We analyzed novel vaccine uptake indices created in response to the recent COVID-19 pandemic. The aim of this scoping review is to survey the state of the literature regarding vaccine uptake indices relating to COVID-19 and other infectious diseases.

We conducted a scoping review with a systematic search strategy to identify relevant articles from the databases Embase, PubMed, and Web of Science with title and abstract screening, full-text review, and data extraction.

Database searches resulted in 3,615 potential articles, of which 229 reports were included. Fifteen studies (7%) were determined to be methodologically advanced vaccine uptake indices that had at least three of the following characteristics: the use of individual- and population-level predictor variables (100 [44%]), geo-spatiotemporal analysis (58 [25%]), data usage agnostic to vaccine specificity (50 [22%]), or sociobehavioral frameworks of health (such as the Health Belief Model and Theory of Planned Behavior) (30 [13%]).

This scoping review offers suggestions for future research of next-generation vaccine uptake indices before use in vaccination campaigns of recurring or novel infectious diseases. Areas to pursue include utilizing individual-level data about vaccination behaviors in conjunction with administrative data, solving the challenge of implementing small-area spatiotemporal analysis, using vaccine-agnostic methods that consider data from more than one infectious disease, and assisting causal inference with theoretical frameworks.