The containment of infectious diseases is challenging due to complex transmutation in the biological system, intricate global interactions, intense mobility, and multiple transmission modes . An emergent disease has the potential to turn into a pandemic impacting millions of people with loss of life, mental health, and severe economic impairment . Multifarious approaches to risk management have been explored for combating an epidemic spread . This work presents the implementation of engineering safety principles to pandemic risk management . We have assessed the pandemic risk using Paté-Cornell's six levels of uncertainty . The susceptible, exposed, infected, quarantined, recovered, deceased (SEIQRD), an advanced mechanistic model, along with the Monte Carlo simulation, has been used to estimate the fatality risk . The risk minimization strategies have been categorized into hierarchical safety measures . We have developed an event tree model of pandemic risk management for distinct risk-reducing strategies realized due to natural evolution, government interventions, societal responses, and individual practices . The roles of distinct interventions have also been investigated for an infected individual's survivability with the existing healthcare facilities . We have studied the Corona Virus Disease of 2019 (COVID-19) for pandemic risk management using the proposed framework . The results highlight effectiveness of the proposed strategies in containing a pandemic.