Sustainable and Robust Home Healthcare Logistics: A Response to the COVID-19 Pandemic

Abstract

Today, research on healthcare logistics is an important challenge in developing and developed countries, especially when a pandemic such as COVID-19 occurs. The responses required during such a pandemic would benefit from an efficiently designed model for robust and sustainable healthcare logistics. In this study, we focus on home healthcare logistics and services for planning the routing and scheduling of caregivers to visit patients’ homes. Due to the need for social distancing during the COVID-19 pandemic, these services are highly applicable for reducing the growth of the epidemic. In addition to this challenge, home healthcare logistics and services must be redesigned to meet the standards of a triple bottom line approach based on sustainable development goals. A triple bottom line approach finds a balance between economic, environmental, and social criteria for making a sustainable decision. Although, recently, the concept of green home healthcare has been studied based on the total cost and green emissions of home healthcare logistics and services, as far as we know, no research has been conducted on the formulation of a triple bottom line approach for home healthcare logistics and services. To achieve social justice for caregivers, the goal of balancing working time is to find a balance between unemployment time and overtime. Another contribution of this research is to develop a scenario-based robust optimization approach to address the uncertainty of home healthcare logistics and services and to assist with making robust decisions for home healthcare planning. Since our multi-objective optimization model for sustainable and robust home healthcare logistics and services is more complex than other studies, the last novel contribution of this research is to establish an efficient heuristic algorithm based on the Lagrangian relaxation theory. An initial solution is found by defining three heuristic algorithms. Our heuristic algorithms use a symmetric pattern for allocating patients to pharmacies and planning the routing of caregivers. Then, a combination of the epsilon constraint method and the Lagrangian relaxation theory is proposed to generate high-quality Pareto-based solutions in a reasonable time period. Finally, an extensive analysis is done to show that our multi-objective optimization model and proposed heuristic algorithm are efficient and practical, as well as some sensitivities are studied to provide some managerial insights for achieving sustainable and robust home healthcare services in practice.

Sustainable development-oriented location-transportation integrated optimization problem regarding multi-period multi-type disaster medical waste during COVID-19 pandemic

“…As above mentioned, once contaminated disaster medical waste is improperly managed, it may increase the infection risks of novel coronavirus among residents, thus adverse influences on social sustainability (Kargar et al, 2020 ). Transportation activities on disaster medical waste clean-up would inherently produce carbon emissions, thus unfavourable impacts on environment (Fathollahi-Fard et al, 2022 ; Jalloul et al, 2022 ). Although most of studies addressed the costs spent in handling medical waste, it cannot turn a blind eye on the fact that disaster medical waste clean-up activities also can create economic benefits (Boonmee et al, 2018 ).…”

Challenges and Impacts of COVID-19 Pandemic on Global Waste Management Systems: A Review

“…[9,22]. This is because the severe acute respiratory syndrome (SARS) coronavirus responsible for spreading the disease of COVID-19 possesses a peculiar morphology [23][24][25][26] and structure, which help it to retain its lifespan for 3 h in the atmosphere as part of aerosols, 4 h on copper surfaces, 24 h on cardboards, 2-3 days on stainless steel, 3 days on plastics and sewage, and 3-4 days on solid faeces [16,27,28]. This is why the abnormal structure and varied lifespans on different media or object surfaces that might be present in existing wastes have become a topic of concern in relation to the acceleration of this deadly disease [29].…”

An Analytical Model for Confronting the Omicron Variant During COVID-19 Pandemic: A System Dynamic Approach

“…In coronary conditions, vaccination is one of the most important factors to consider, for example, in order to expedite vaccination in Canada, vaccination services were provided in both pharmacies and hospitals [21]. In another paper, Fathollahifard et al [32] in 2022, in this paper present a model for robust multi-objective optimization for a routing optimization problem and scheduling for the use of a home health care logistics network. The benefits of an efficient design are critical to responding to or responding to epidemics such as COVID-19.…”