National Scientific Funding for Interdisciplinary Research: A Comparison Study of Infectious Diseases in the US and EU

Abstract

Infectious diseases have been continuously and increasingly threatening human health and welfare due to a variety of factors such as globalisation, environmental, demographic changes, and emerging pathogens. In order to establish an interdisciplinary approach for coordinating R&D via funding, it is imperative to discover research trends in the field. In this paper, we apply machine learning methodologies and network analyses to understand how the European Union (EU) and the United States (US) have invested their funding in infectious diseases research utilising an interdisciplinary approach. The purpose of this paper is to use public R&D project data as data and to grasp the research trends of epidemic diseases in the US and EU through scientometric analysis.

A Strategy for International Cooperation in the COVID-19 Pandemic Era: Focusing on National Scientific Funding Data

“…It has data from approximately 1 million nationally funded projects between 2012 and 2018. The detailed process of database establishment is described in [ 15 ]. The data from Korea were collected from NTIS, which is utilized in many studies of Korean R&D trends [ 23 , 24 , 25 ].…”

“…As a way of identifying coronavirus-related R&D areas, the co-occurrence matrix was made in terms of the ASJC code (All Science Journal Classification Codes) of Scopus by using the Vantage Point ® system (Search Technology, Inc., Norcross, GA, USA) as demonstrated in [ 15 ]. From the single standard’s perspective, the ASJC code was previously assigned to all the projects in the global R&D database that employed the machine learning approach to classify the different R&D projects that stemmed from the US, the EU, and Japan [ 15 ]. The number of data utilized by Korea, which has the characteristics of the centralized database, was as high as that used by the US.…”

“…Identifying the association among ASJC codes through the co-occurrence matrix implied a network structure. Thus, the VOSViewer (Leiden University, Gravenhage, the Netherlands) software was used as a network structure visualization tool to understand the relationship between ASJC codes [ 15 ]. The VOSViewer system calculates the similarity between each component and visualizes the network structure in the form of a cluster map or a topographic map [ 28 ].…”

“…Although the world is already preparing to tackle the newest emergent virus strain [ 1 ], vaccine research and development are highly complex and require concerted public funding efforts for a long period of time [ 8 , 13 ]. In order to improve the efficiency of the allocation of the funding for infectious disease-related R&D, it is necessary to understand the current trends of coronavirus disease-related scientific research funding around the world to consider the directions for the global collaborative research and development [ 14 , 15 ].…”

“…Due to the magnitude of the public funds invested in infectious disease-related research [ 14 ], the Korean government has to evaluate their investment strategy about which research fields must be invested in and in which research fields is needed collaboration with international partners to reach important research goals [ 13 ]. To date, few studies have provided a comprehensive analysis of infectious disease R&D from a public funding perspective [ 13 , 14 , 15 ]. To the best of our knowledge, there is no study to satisfy both prerequisites for understanding what coronavirus disease-related research and development has been conducted from both the world’s and South Korea’s perspectives.…”