Dengue and Early Warning Systems: A review based on Social Network Analysis

Abstract Dengue has become one of the fastest-growing mosquito-borne viral diseases in many parts of the world. There is no specific treatment or vaccine for this fever and this makes it highly challenging for the successful control and elimination of this disease. However, foreseeing an outbreak can help in taking preventive measures against the widespread virus. This, in turn, boosted the research works on the development of early warning systems. The purpose of this study is to review the literature on the development of different early warning systems in a systematic way using the techniques of main path analysis and article clustering. Main path analysis which makes use of citation information traces the evolution of a particular scientific field as well as the significant articles in the research area. Article clustering is used to analyze the structure of the research. We have used Pajek and Gephi, programs to analyse and visualize large networks for the main path analysis and the article clustering respectively. This study would be helpful to quickly identify major research works happened so far in this area and to provide better solutions.