Impact of COVID-19 food supply chain: Comparing the use of IoT in three South African supermarkets.

This study aims to understand the impact of the COVID-19 pandemic by comparing the performance of three major supermarkets in South Africa and addressing the following questions. 1) What is the impact of a supply chain disruption on the food system? 2) What interventions (short and long-term) are taken by the food supply chain to mitigate disruption? 3) What does the post-pandemic picture look like for the food retail sector? This study adopts a comparative research approach and investigates direct strategies adopted by various food supply chain actors to mitigate the impact of covid-19. This study compares how retailers Checkers, Woolworths, and Pick n Pay have adapted their business models to remain resilient during COVID-19 lockdown. The results show that the food supply chain remained resilient even with demand management challenges at the lockdown. Food supply chain issues came under a spotlight as borders and production plants were shut down or restricted to contain the spread of the virus. This study establishes that the food shortage is primarily caused by panic buying at the beginning of lockdown, causing shock in the supply chain cadence. The other aspect of food security issue is attributed to food availability and socioeconomic problems resulting from loss of income. On sustainability, there are fears that control measures such as packaging (increased use of plastic), cleaning chemicals, waste and sanitisation of space to maintain hygiene as required for covid-19 can undermine the gains towards preserving the environment.

Modeling hospital energy and economic costs for COVID-19 infection control interventions.

The study objective assessed the energy demand and economic cost of two hospital-based COVID-19 infection control interventions: negative pressure (NP) treatment rooms and xenon pulsed ultraviolet (XP-UV) equipment. After projecting COVID-19 hospitalizations, a Hospital Energy Model and Infection De-escalation Models quantified increases in energy demand and reductions in infections. The NP intervention was applied to 11, 22, and 44 rooms for small, medium, and large hospitals, while the XP-UV equipment was used eight, nine, and ten hours a day. For small, medium, and large hospitals, the annum kWh for NP rooms were 116,700 kWh, 332,530 kWh, 795,675 kWh, which correspond to annum energy costs of $11,845 ($1,077/room), $33,752 ($1,534/room), and $80,761 ($1,836/room). For XP-UV, the annum-kilowatt-hours (and costs) were 438 ($45), 493 ($50), and 548 ($56) for small, medium, and large hospitals. While energy efficiencies may be expected for the large hospital, the hospital contained more energy-intensive use rooms (ICUs) which resulted in higher operational and energy costs. XP-UV had a greater reduction in secondary COVID-19 infections in large and medium hospitals. NP rooms had a greater reduction in secondary SARS-CoV-2 transmission in small hospitals. Early implementation of interventions can result in realized cost savings through reduced hospital-acquired infections.

Impact of industry 4.0 on healthcare systems of low- and middle- income countries: a systematic review.

Purpose: A growing body of empirical research has emerged, focused on leveraging Industry 4.0 technologies to develop and optimise systems within various operational contexts, including healthcare delivery. However, even though a significant number of studies have been published on application of digital technologies in enhancing delivery and health outcomes of health systems, systematic studies that review how extensively these technologies have been applied within a low- and middle-income economies' context remain scarce in the literature. This work attempts to close that gap by investigating the impact of industry 4.0 on healthcare systems in emerging economies. Methods: The study follows a systematic review approach and uses PRISMA guidelines to conduct the research and synthesise its findings. A final sample of 72 articles is selected for in-depth review following a systematic screening from an initial list of 597 results. Results: The study successfully synthesises the latest research in the subject area and reveals that, hitherto, approaches to use of digital tools have been fragmented and thus unable to provide holistic optimisation solutions for healthcare systems in low-resource settings. The analysis exposes a heavy skew towards adoption of mobile health and telemedicine technologies, with conspicuous research gaps in the use of augmented reality, additive manufacturing as well as simulation and digital twin technologies. Conclusions: The study provides researchers, health-care practitioners and systems engineers with knowledge on the state-of-the-art in healthcare systems optimisation and points out research gaps that may be addressed through future empirical studies.