Abstract
Over the years, the research community has conducted a number of studies in order to identify the comorbidity patterns on the basis of numerous factors such as genetics, metabolites, microbes, Protein-Protein Interactions (PPIs), and microRNAs (miRNAs). However, to the best of our knowledge, no study has been conducted to review and summarize the literature on the basis of different network analysis levels, namely, micro, meso, macro, and hybrid to identify disease comorbidity patterns. In this study, we have conducted a systematic literature review to select, extract, and critically analyze previous related studies. We also elaborate different methods of social network analysis which have been employed for finding disease associations. This study has also identified least, average, and most used methods at micro, meso, and macro-levels. The analysis suggests that the full potential of the network analysis has not yet been exploited in the research domain of disease-disease association. A number of future research avenues have been identified, which have a potential to yield new findings.