Coronavirus disease-19 (COVID-19) was declared a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that targets the lower respiratory tract in human species. Since the target receptor molecule is angiotensin-converting enzyme 2 (ACE2), which is highly expressed on the cell lining of the respiratory tract, the virus is responsible for causing acute respiratory distress syndrome (ARDS). Computational tools such as artificial intelligence, machine learning and deep learning-based platforms are used for drug repurposing, identification, and selection of target molecules that can be used for vaccine development and antiviral drug production. Computer-aided drug designing, molecular docking and homology modelling are some of the most widely used in silico models for drug discovery against COVID-19. It is important to take preventive measures to control the spread of the virus. The present review focuses on the computational tools used for recognising the target molecules for vaccine production, the transmission networks of COVID-19 and the long-term strategies to prevent future pandemics such as COVID-19.