The long COVID research literature

Abstract

While the COVID-19 pandemic morphs into less malignant forms, the virus has spawned a series of poorly understood, post-infection symptoms with staggering ramifications, i. e., long COVID (LC). This bibliometric study profiles the rapidly growing LC research domain [5,243 articles from PubMed and Web of Science (WoS)] to make its knowledge content more accessible. The article addresses What? Where? Who? and When? questions. A 13-topic Concept Grid presents bottom-up topic clusters. We break out those topics with other data fields, including disciplinary concentrations, topical details, and information on research "players" (countries, institutions, and authors) engaging in those topics. We provide access to results via a Dashboard website. We find a strongly growing, multidisciplinary LC research domain. That domain appears tightly connected based on shared research knowledge. However, we also observe notable concentrations of research activity in different disciplines. Data trends over 3 years of LC research suggest heightened attention to psychological and neurodegenerative symptoms, fatigue, and pulmonary involvement.

Keywords: COVID-19; bibliometrics; long COVID; research profile; tech mining; text analysis.

Figure 1

PRISMA flow diagram.

Figure 2

Concept grid of long COVID research topics.

Figure 3

The long COVID dashboard: Sample VizLink^® view.

Figure 4

Long COVID publications.

Figure 5

Long COVID publications' Web of Science Categories, mapping similarity in their citing of journals.

Figure 6

Emergence dimensions. Only the top entities in each section are shown (to avoid undue clutter). For example, 45 terms or phrases are scored as emergent (scoring over 1.77), but only 10 are plotted (scoring over 3.4). Values plotted reflect total counts in the dataset; they are not limited to records including emergent terms.

Figure 7

Exploring topics together with research players.