Chapter 19 - Computational biology and biosensors as surveillance tools for emerging and re-emerging infectious diseases

Abstract

The continuous increase in emerging infectious diseases (EIDs) as well as reemerging infectious diseases (RIDs) have a cataclysmic impact on society and the world’s economy. Out of various reasons for this, the foremost cause is global warming which has altered the disease epidemiology, population susceptibility and increased exposure to causative agents. In addition, global warming has also affected the geographical distribution of vectors/intermediate host distribution, including invertebrate hosts (insects), rodents and migratory birds. The fast and accurate diagnosis of a virus or antigen impacts the effectiveness of zoning, monitoring, or removal techniques due to the danger presented by EIDs. The world has witnessed the dawn of a new era of computer-driven research in medical sciences over the last couple of decades. On one hand, recent advancements in high-throughput sequencing platforms have led to a generation of a large repertoire of omics data from pathogens as well as their corresponding hosts. On the other hand, structural genomics and molecular modeling have accelerated structure-based drug discovery. This has led to a sudden surge in advanced computational tools capable of processing such “big data” and systems biology approaches, enabling researchers to attain a deeper understanding of biological mechanisms underlying such infections, molecular interactions, host-pathogen interactions and pathogen evolution. In addition, such information also helps in developing faster detection strategies and diagnostic tools for pathogenicity. The existing diagnostics and surveillance systems are time consuming and lack accuracy.