ABSTRACT
We consider a hierarchical maximal covering location problem (HMCLP) to locate health centres and hospitals so that the maximum demand is covered by two levels of services in a successively inclusive hierarchy. We extend the HMCLP by introducing the partial coverage and a new definition of the referral. The proposed model may enable an informed decision on the healthcare system when dynamic adaptation is required, such as a COVID-19 pandemic. We define the referral as coverage of health centres by hospitals. A hospital may also cover demand through referral. The proposed model is solved optimally for small problems. For large problems, we propose a customised genetic algorithm. Computational study shows that the GA performs well, and the partial coverage substantially affects the optimal solutions. © 2023 Inderscience Enterprises Ltd.
ABSTRACT
We consider a hierarchical maximal covering location problem (HMCLP) to locate health centres and hospitals so that the maximum demand is covered by two levels of services in a successively inclusive hierarchy. We extend the HMCLP by introducing the partial coverage and a new definition of the referral. The proposed model may enable an informed decision on the healthcare system when dynamic adaptation is required, such as a COVID-19 pandemic. We define the referral as coverage of health centres by hospitals. A hospital may also cover demand through referral. The proposed model is solved optimally for small problems. For large problems, we propose a customised genetic algorithm. Computational study shows that the GA performs well, and the partial coverage substantially affects the optimal solutions. [Submitted: 20 January 2021;Accepted: 15 January 2022]
ABSTRACT
Background: The 2019 novel coronavirus disease (COVID-19) has caused a global health catastrophe by affecting the human population around the globe. Unfortunately, there is no specific medi-cation or treatment currently available for COVID-19. Objective: It is extremely important to find effective drug treatment in order to put an end to this pandemic period and return to normal daily life. In this context and considering the urgency, rather than focusing on the discovery of novel compounds, it is critical to explore the effects of existing herbal agents with proven antiviral properties on the virus. Methods: Molecular docking studies were carried out employing three different methods, Glide extra precision (XP) docking, induced fit docking (IFD), and molecular mechanics/generalized born surface area (MM/GBSA), to determine the potential antiviral and antibacterial effects of 58 phytochemicals present in Rosmarinus officinalis, Thymbra spicata, Satureja thymbra, and Stachys lavandulifolia plants against the main protease (Mpro) and angiotensin-converting enzyme 2 (ACE2) enzymes. Results: 7 compounds stood out among all the molecules, showing very high binding affinities. Accord-ing to our findings, the substances chlorogenic acid, rosmarinic acid, and rosmanol exhibited extremely significant binding affinities for both Mpro and ACE2 enzymes. Furthermore, carnosic acid and alpha-cadinol showed potent anti-Mpro activity, whereas caffeic acid and carvacrol exhibited promising anti-ACE2 activity. Conclusion: Chlorogenic acid, rosmarinic acid, rosmanol, carnosic acid, alpha-cadinol, caffeic acid, and carvacrol compounds have been shown to be powerful anti-SARS-CoV-2 agents in docking simulations against Mpro and ACE2 enzymes, as well as ADME investigations.