Infectious epidemics and the research output of nations: A data-driven analysis

Abstract

During the last years, several infectious diseases have caused widespread nationwide epidemics that affected information seeking behaviours, people mobility, economics and research trends. Examples of these epidemics are 2003 severe acute respiratory syndrome (SARS) epidemic in mainland China and Hong Kong, 2014–2016 Ebola epidemic in Guinea and Sierra Leone, 2015–2016 Zika epidemic in Brazil, Colombia and Puerto Rico and the recent COVID-19 epidemic in China and other countries. In this research article, we investigate the effect of large-scale outbreaks of infectious diseases on the research productivity and landscape of nations through the analysis of the research outputs of main countries affected by SARS, Zika and Ebola epidemics as returned by Web of Science Core Collection. Despite the mobility restrictions and the limitations of work conditions due to the epidemics, we surprisingly found that the research characteristics and productivity of the countries that have excellent or moderate research traditions and communities are not affected by infectious epidemics due to their robust long-term research structures and policy. Similarly, large-scale infectious outbreaks can even boost the research productivity of countries with limited research traditions thanks to international capacity building collaborations provided by organisations and associations from leading research countries.

Mohamed Ali Hadj Taieb
Mohamed Ali Hadj Taieb
Assistant professor

My research interests include semantic similarity, semantic relatedness, knowledge representation, Big Data, social media, data management systems and graph embedding.

Mohamed Ben Aouicha
Mohamed Ben Aouicha
Professor

My research interests concern information retrieval, semantic technologies, social media analytics, knowledge representation, Big Data and graph embedding.