Forecasting the impact of epidemic outbreaks on the supply chain: modelling asymptomatic cases of the COVID-19 pandemic

Abstract

An epidemic outbreak largely disrupts supply chains (SCs) worldwide through plummeting business confidence, especially when it becomes a pandemic; its unpredictable re-emergence and spreadability may lead to inappropriate decision-making, in turn causing severe economic shocks. In March 2020, the coronavirus disease 2019 (COVID-19) outbreak attained a pandemic level, and many millions of cases were confirmed globally. Many countries reported an increasing number of active cases and formulated long-term lockdown guidelines, which resulted in an unexpected disruption of SCs. A key challenge in this scenario is that the rising number of confirmed COVID-19 cases does not necessarily reflect the already infected or asymptomatic cases. It is thus critical to understand the impact of asymptomatic carriers on the SC, as they may be the key driver of the novel virus spread, disrupting long-term SCs. This paper generalised the susceptible-exposed-infected-recovered (S-E-I-R) approach to create a mathematical model for which the impact of a proposed asymptomatic situation on the SC is evaluated through the basic reproduction number (R0), considered the main driver of SC disruption and the equilibrium status of infection over time. This paper presents an action plan for reducing disruption in the SC based on the R0 of the model. Overall, the current study as validated through a case study suggests that the asymptomatic-situation-based model is more convenient for critically understanding as well as forecasting the outbreak’s impact on SCs. This study also highlights different perspectives of SCs for managing such types of pandemics using modelling approaches.