A systematic review of trials currently investigating therapeutic modalities for post-acute COVID-19 syndrome and registered on WHO International Clinical Trials Platform.

BACKGROUND: Post-acute COVID-19 syndrome (PACS) is a well-recognized, complex, systemic disease which is associated with substantial morbidity. There is a paucity of established interventions for the treatment of patients with this syndrome. OBJECTIVES: To systematically review registered trials currently investigating therapeutic modalities for PACS. DATA SOURCES: A search was conducted up to the 16 September, 2022, using the COVID-19 section of the WHO Internal Clinical Trials Registry Platform. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS: Interventional clinical trials of any sample size examining any therapeutic modality targeting persistent symptoms among individuals after diagnosis with COVID-19. METHODS: Data on trial characteristics and intervention characteristics were collected and summarized. RESULTS: After screening 17 125 trials, 388 trials, from 42 countries, were eligible. In total, we had 406 interventions, of which 368 were mono-therapeutic strategies, whereas 38 were intervention combinations. Among 824 primary outcomes identified, there were >300 different outcomes. Rehabilitation was the most employed class of intervention in 169 trials. We encountered 76 trials examining the pharmacological agents of various classes, with the most common agent being colchicine. Complementary and alternative medicine encompassed 64 trials exploring traditional Chinese medicine, Ayurveda, homeopathic medications, naturopathic medications, vitamins, dietary supplements, and botanicals. Psychotherapeutic and educational interventions were also employed in 12 and 4 trials, respectively. Other interventions, including transcranial direct current stimulation, transcutaneous auricular vagus nerve stimulation, general electrical stimulation, cranial electrotherapy stimulation, various stem cell interventions, and oxygen therapy interventions, were also employed. CONCLUSION: We identified 388 registered trials, with a high degree of heterogeneity, exploring 144 unique mono-therapeutic interventions for PACS. Most studies target general alleviation of symptoms. There is a need for further high-quality and methodologically robust PACS treatment trials to be conducted with standardization of outcomes while following WHO's recommendation for uniform evaluation and treatment.

Institutional Response Strategies of Health Crises Through Public's Lens

This descriptive study employs the Social Mediated Crisis Communication Model [SMCC] to primarily identify the crisis response strategies adopted by the Palestinian Ministry of Health in facing the Corona Covid-19 pandemic. The extent to which the public accepted these strategies approved by the ministry following the form of the messages directed to the audience is consequently examined. The study, at the same vein, attempts to detect the audiences' emotional responses that have been shaped following the selected form of messages under analysis. Traditional media, social media or offline word-of-mouth entail the form of message. A content analysis was conducted on the ministry's communications during the study period. To triangulate the data, a questionnaire has been designed and electronically distributed on a sample of 370 students enrolled at Hebron University, Palestine. The analysis has shown that the supportive strategies are the most acceptable responses to the audience. They create a positive emotional reaction following the type of message source applied. The study also concludes that—in health crises—social media and offline word-of-mouth are more convenient as a form of message at the outbreak and during the pandemic. The form of message is highly influential on the development of internal and external dependent-attributed emotions. The current study argues that it is essential to adopt social media and offline word-of-mouth as a communication form during health crises. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Institutional Response Strategies of Health Crises Through Public’s Lens

This descriptive study employs the Social Mediated Crisis Communication Model [SMCC] to primarily identify the crisis response strategies adopted by the Palestinian Ministry of Health in facing the Corona Covid-19 pandemic. The extent to which the public accepted these strategies approved by the ministry following the form of the messages directed to the audience is consequently examined. The study, at the same vein, attempts to detect the audiences’ emotional responses that have been shaped following the selected form of messages under analysis. Traditional media, social media or offline word-of-mouth entail the form of message. A content analysis was conducted on the ministry’s communications during the study period. To triangulate the data, a questionnaire has been designed and electronically distributed on a sample of 370 students enrolled at Hebron University, Palestine. The analysis has shown that the supportive strategies are the most acceptable responses to the audience. They create a positive emotional reaction following the type of message source applied. The study also concludes that—in health crises—social media and offline word-of-mouth are more convenient as a form of message at the outbreak and during the pandemic. The form of message is highly influential on the development of internal and external dependent-attributed emotions. The current study argues that it is essential to adopt social media and offline word-of-mouth as a communication form during health crises. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Lightweight CNN-based Models for Masked Face Recognition

Covid-19 has become one of the most threatening diseases in the world. Therefore, governments and health organizations asked people to wear masks in order to control the spread of such threatening diseases. During this epidemic, people must obey the rules of wearing masks that play a vital role in controlling the outbreak of COVID-19. In order to identify the persons who do not wear the mask, an automated recognition system is discussed in this paper. This model automatically detects masked faces using deep learning techniques;TensorFlow, and Keras. The proposed method effectively differentiates between masked faces and unmasked faces to help governments, companies, and organizations monitoring and detecting who broke the rule of wearing masks. The implementation of this model is based on three pre-trained models;MobileNetV2, DenseNet, and NASNetMobile. In terms of accuracy, MobilenetV2 reached 0.9859, while DenseNets and NASNetMobile reached 0.9852 and 0.9758 respectively. The contribution of this article is to present the feasibility of using a lightweight model (i.e. NasNetMobile) that can be implemented even on low-resource devices (i.e. mobile) to recognize masked faces efficiently. © 2021 IEEE.