ABSTRACT
Disruptions in the food supply chains caused by the COVID-19 pandemic have destabilized the balance between production, supply, transport, distribution, and consumption. Consequently, these disruptions have affected food and nutritional security all over the world. This study proposes a framework for investigating the impact of COVID-19 on food supply chains, considering Eastern Africa as a focus region with Kenya and Rwanda as case studies. A systems thinking approach with three systemic components (food and nutrition, COVID-19 contagion, and human health) was applied. The contagion component was characterized by the susceptible, exposed, infected, recovered, and deceased (SEIRD) epidemiological modeling method. We then applied a causal loop diagram and stock and flow diagrams to map the links and interactions between variables from the contagion, health, and food supply chain components of the whole system. The results reveal that COVID-19 has adversely affected food and nutritional security in Eastern African countries. Key response measures to COVID-19 such as lockdowns, closure of borders, isolation, and quarantining have resulted in labor shortages, increased unemployment rates, loss of income, and the subsequent contraction of economies. The disruption of the food supply chain has negatively impacted the main pillars of food and nutrition security, which are availability, accessibility, utilization, and stability. We suggest direct food supply from local producers to the consuming communities to shorten the food supply chain and therefore enhance food self-sufficiency to reduce the severe effects of COVID-19 on food and nutrition security. Overall, our study provides a useful framework to help design better policies and build more resilient and inclusive food systems during COVID-19 and similar pandemics in the future.
ABSTRACT
We present a case study on modeling and predicting the course of Covid-19 in the Indian city of Pune. The results presented in this paper are concerned primarily with the wave of infections triggered by the Delta variant during the period between February and June 2021. Our work demonstrates the necessity for bringing together compartmental stock-and-flow and agent-based models and the limitations of each approach when used individually. Some of the work presented here was carried out in the process of advising the local city administration and reflects the challenges associated with employing these models in a real-world environment with its uncertainties and time pressures. Our experience, described in the paper, also highlights the risks associated with forecasting the course of an epidemic with evolving variants. © 2022 IEEE.