Estimating the size of fields in biomedical sciences.

Scientific research output has increased exponentially over the past few decades, but not equally across all fields of study, and we lack clear methods for estimating the size of any given field of research. Understanding how fields grow, change, and are organized is essential to understanding how human resources are allocated to the investigation of scientific problems. In this study, we estimated the size of certain biomedical fields from the number of unique author names appearing in field-relevant publications in the PubMed database. Focusing on microbiology, where the size of fields is often associated with those who work on a particular microbe, we find large differences in the size of its subfields. We found that plotting the number of unique investigators as a function of time can show changes consistent with growing or shrinking fields. In general, the number of unique author names associated with a particular microbe correlated with the number of disease cases attributed to that microbe, suggesting that the microbiology field workforce is deployed in a manner consistent with the medical importance of the microbe in question. We propose that unique author counts can be used to measure the size of the workforce in any given field, analyze the overlap of the workforce between fields, and compare how the workforce correlates to available research funds and the public health burden of a field.IMPORTANCEScience and its individual fields are growing at spectacular rates along with the number of papers being generated each year. However, we lack methods to investigate the size of these fields, many times relying on anecdotal knowledge on which fields are "hot topics" or oversaturated. Thus, we developed a bibliometric method analyzing authorship information from PubMed to estimate the size of fields based on unique author counts. Our major findings are that unique author counts serve as an efficient measurement of the size of a given field. Additionally, the size of a biomedical science field correlates to its public health burden when compared to case numbers. This method allows us to compare growth rates, workforce distribution, and the allocation of resources between fields to understand how scientific fields self-regulate. These insights can, in turn, help guide policymaking, for example, in funding allocation, to ensure fields are not neglected.