Big Data Applications in Vaccinology

Background

When the non-epidemiologist thinks of vaccines, they think of flu shots and other immunizations given routinely to children and young adults. But, underlying these medical achievements is the need for processing and drawing understanding from huge datasets. Many of these Big Data processes are similar to those used in other industries, so from that perspective vaccine development and evaluation draws on tools that have matured in other areas such as finance and supply chain (Jordan, Dossou & Chang Jr., 2019). It is important, though, to understand how these tools are being employed, for as this understanding is more broadly dispersed throughout the data community, new applications can be more readily devised and more opportunities for protection from these illnesses and parasites can be developed.

Before proceeding with the study, it is important to define what is meant, in this effort, by Big Data technologies. This is important because of the wide range of understanding that exists about the definitions of Big Data and the tools and technologies associated with it. For the present project, a rather wide view of these terms is taken. This will allow the results to paint as clear a picture as possible of the state of the art and reduce the number of studies overlooked for terminological reasons. For the purposes of this study, the term “Big Data technologies” will include all forms of data analytics, machine learning, deep learning, and datamining. To reduce the complexity of the searches, the study does not use all possible terms describing these processes. However, the databases searched do a very good job of providing results that include other terms related to the basic terms listed above, so for example papers including terms such as “artificial intelligence” and “support vector machine” will be included even without those terms being used in the actual search expression. The terms used in this study are defined below: