Abdullah Baz^1,*, Hosam Alhakami²

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1155-1174, 2021, DOI:10.32604/cmc.2020.013215

Abstract The World Health Organization declared COVID-19 a pandemic on March 11, 2020 stating that it is a worldwide danger and requires imminent preventive strategies to minimise the loss of lives. COVID-19 has now affected millions across 211 countries in the world and the numbers continue to rise. The information discharged by the WHO till June 15, 2020 reports 8,063,990 cases of COVID-19. As the world thinks about the lethal malady for which there is yet no immunization or a predefined course of drug, the nations are relentlessly working at the most ideal preventive systems to contain the infection. The Kingdom… More >

Sunil Kumar Sharma¹, Shivam Bhardwaj^2,*, Rashmi Bhardwaj³, Majed Alowaidi¹

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 805-825, 2021, DOI:10.32604/cmc.2020.011937

Abstract This article discusses short–term forecasting of the novel Corona Virus (COVID-19) data for infected and recovered cases using the ARIMA method for Saudi Arabia. The COVID-19 data was obtained from the Worldometer and MOH (Ministry of Health, Saudi Arabia). The data was analyzed for the period from March 2, 2020 (the first case reported) to June 15, 2020. Using ARIMA (2, 1, 0), we obtained the short forecast up to July 02, 2020. Several statistical parameters were tested for the goodness of fit to evaluate the forecasting methods. The results show that ARIMA (2, 1, 0) gave a better forecast… More >

Panagiotis G. Asteris^1,*, Maria G. Douvika¹, Chrysoula A. Karamani¹, Athanasia D. Skentou¹, Katerina Chlichlia², Liborio Cavaleri³, Tryfon Daras⁴, Danial J. Armaghani⁵, Theoklis E. Zaoutis⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 815-828, 2020, DOI:10.32604/cmes.2020.013280

Abstract The modeling and risk assessment of a pandemic phenomenon such as COVID-19 is an important and complicated issue in epidemiology, and such an attempt is of great interest for public health decision-making. To this end, in the present study, based on a recent heuristic algorithm proposed by the authors, the time evolution of COVID-19 is investigated for six different countries/states, namely New York, California, USA, Iran, Sweden and UK. The number of COVID-19-related deaths is used to develop the proposed heuristic model as it is believed that the predicted number of daily deaths in each country/state includes information about the… More >

Flavia M. Wehrle^1,2,3, Markus A. Landolt^3,4,5, Beatrice Latal^1,3, Sarah Rometsch⁶, Matthias Greutmann^7,*

Congenital Heart Disease, Vol.15, No.5, pp. 301-308, 2020, DOI:10.32604/CHD.2020.013078

Abstract Background: The risk for a severe disease course in case of infection with SARS-CoV-2 in young adults with congenital heart disease is largely unknown, potentially leading to uncertainty and anxiety among affected patients. This study aims to investigate health-related concerns, health-related quality of life and psychological adjustment in patients with congenital heart disease compared to healthy peers during the COVID-19 pandemic. Methods: One-hundred patients with congenital heart disease and 50 controls (M = 29.7, SD = 3.8 years) were recruited. They completed an online survey including the assessment of health-related concerns regarding COVID-19, the 12-item Short Form Health Survey and… More >

Sanaa Al-Marzouki¹, Farrukh Jamal², Christophe Chesneau^3,*, Mohammed Elgarhy⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 437-458, 2020, DOI:10.32604/cmes.2020.011521

Abstract Recent studies have pointed out the potential of the odd Fréchet family (or class) of continuous distributions in fitting data of all kinds. In this article, we propose an extension of this family through the so-called “Topp-Leone strategy”, aiming to improve its overall flexibility by adding a shape parameter. The main objective is to offer original distributions with modifiable properties, from which adaptive and pliant statistical models can be derived. For the new family, these aspects are illustrated by the means of comprehensive mathematical and numerical results. In particular, we emphasize a special distribution with three parameters based on the… More >

Xu Zhu¹, Meng Xia¹, Yingzhe Hu¹, Lin Zhang^1,*, Yun Lu², Ying Zhang¹, Xudong Guo¹

International Journal of Mental Health Promotion, Vol.22, No.3, pp. 149-157, 2020, DOI:10.32604/IJMHP.2020.011097

Abstract The purpose of the study was to investigate the mental status and psychological needs of police officers during the COVID-19 outbreak in China. The Anti-Pandemic Public Mental Status Scale and self-administered Psychological Needs Scale were administered online to police officers in Y city, a significant sub-central city of Hubei Province, where was affected by the pandemic the most seriously. A total of 5,467 valid questionnaires were collected, of which female police accounted for 17.7%. Compared with the national public and Y city public data previously measured using the Anti-Pandemic Public Mental Status Scale, this study found that 24.6% of the… More >

Xiaoming Jia, Linyu You, Qin An^*

International Journal of Mental Health Promotion, Vol.22, No.3, pp. 115-121, 2020, DOI:10.32604/IJMHP.2020.011120

Abstract Psychological hotlines became the most convenient and feasible way to provide psychological intervention for the needy after the outbreak of COVID- 19. Hotlines assisting in defeating the coronavirus functioned quite differently from general psychological hotlines and face-to-face counseling. This article discusses the specificity of hotlines of this kind, including appropriate operational procedures that include the overall assessment and the empathetic understanding of the clients, a quick focus on goals, and real-world oriented assistance. Major administrative and ethical concerns are also addressed. More >

Peipeng Yu¹, Zhihua Xia^{1, *}, Jianwei Fei¹, Sunil Kumar Jha^{1, 2}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 743-760, 2020, DOI:10.32604/cmc.2020.011391

Abstract Coronaviruses are a well-known family of viruses that can infect humans or animals. Recently, the new coronavirus (COVID-19) has spread worldwide. All countries in the world are working hard to control the coronavirus disease. However, many countries are faced with a lack of medical equipment and an insufficient number of medical personnel because of the limitations of the medical system, which leads to the mass spread of diseases. As a powerful tool, artificial intelligence (AI) has been successfully applied to solve various complex problems ranging from big data analysis to computer vision. In the process of epidemic control, many algorithms… More >

Ibrahim Arpaci¹, Shadi Alshehabi², Mostafa Al-Emran^{3, *}, Mahmoud Khasawneh⁴, Ibrahim Mahariq⁴, Thabet Abdeljawad^{5, 6, 7}, Aboul Ella Hassanien^{8, 9}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 193-204, 2020, DOI:10.32604/cmc.2020.011489

Abstract People started posting textual tweets on Twitter as soon as the novel coronavirus (COVID-19) emerged. Analyzing these tweets can assist institutions in better decision-making and prioritizing their tasks. Therefore, this study aimed to analyze 43 million tweets collected between March 22 and March 30, 2020 and describe the trend of public attention given to the topics related to the COVID-19 epidemic using evolutionary clustering analysis. The results indicated that unigram terms were trended more frequently than bigram and trigram terms. A large number of tweets about the COVID-19 were disseminated and received widespread public attention during the epidemic. The high-frequency… More >