ABSTRACT
Recently, the coronavirus pandemic has caused widespread panic around the world. Modern technologies can be used to monitor and control this highly contagious disease. A plausible solution is to equip each patient who is diagnosed with or suspected of having COVID-19 with sensors that can monitor various healthcare and location parameters and report them to the desired facility to control the spread of the disease. However, the simultaneous communication of numerous sensors installed in most of an area's population results in a massive burden on existing Long-Term Evolution (LTE) networks. The existing network becomes oversaturated because it has to manage two more kinds of traffic in addition to regular traffic (text, voice, and video). Healthcare traffic is generated by many sensors deployed over a huge population, and extra traffic is generated by people contacting their family members via video or voice calls. In pandemics, e-healthcare traffic is critical and should not suffer packet loss or latency due to network overload. In this research, we studied the performance of existing networks under various conditions and predicted the severity of network degradation in an emergency scenario. We proposed and evaluated three schemes (doubling bandwidth, combining LTE-A and LTE-M networks, and request queuing) for ensuring the quality of service (QoS) of healthcare sensor (HCS) network traffic without perturbation from routine human-to-human or machine-to-machine communications. We simulated all proposed schemes and compared them with existing network scenarios. Although it is observed from the results that doubling the bandwidth serves the purpose, it is a time-consuming and expensive solution that seems non-practical in case a sudden peak occurs during an emergency. We can conclude by analyzing the simulations that the proposed queuing scheme is best-suitable under all studied scenarios where QoS for HCS traffic is never compromised, which is the ultimate goal of this research.
ABSTRACT
Context: The contagious global pandemic of coronavirus 2019 (COVID-19) has prompted many Moroccans to turn to traditional phytoremedies. Aims: To highlight the ethnopharmacological information and the risks of intoxication related to the use of herbal medicine to combat COVID-19. Methods: Through a semi-structured questionnaire and using the "Free listing" technique, an ethnobotanical survey was conducted among 36 herbalists of the Meknes prefecture to collect ethnopharmacological data on species used in the fight against COVID-19. Then, many databases were used to document their pharmacological and toxicological activities. Results: A total of 36 species in 22 families were reported to be used to prepare traditional recipes against COVID-19. According to the relative frequency index of citation, the species Artemisia herba-alba Asso, Eucalyptus globulus Labill, Syzygium aromaticum (L.) Merr. & L.M. Perry, Citrus limon (L.) Osbeck, and Zingiber officinale Roscoe. were recommended by all respondents and recorded the highest usage values. Based on the value of the plant parts index, leaves were the most used part (PPV = 0.37). Most of the remedies were prepared as infusions and administered orally. The bibliographic research revealed that the plants used have several biological activities and are frequently used to treat respiratory diseases. However, some of them have been reported to be toxic. Conclusions: Recommended species are endowed with innumerable biological activities. They can be a promising alternative to combat COVID-19. However, their toxic effects require pharmacotoxicological studies to ensure the safety and efficacy of these natural remedies.