A view of the health services after COVID-19: an Egyptian perspective

Kamel, Mohamed I.

doi:10.1080/20905068.2020.1789391

Cited by 10 publications

(9 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many scholars have studied the COVID-19 spread in Egypt from various perspectives: a) impact of partial and complete lockdown on the air quality and health environment ( Abou El-Magd and Zanaty, 2020 ), b) public awareness and attitude towards the COVID-19 ( Abdelhafiz et al, 2020 ), c) psychological impact of COVID-19 on healthcare professionals and the public ( Elkholy et al, 2020 ; AboKresha et al, 2021 ; Arafa et al, 2021 ), d) influence of COVID-19 pandemic on education in medical schools ( Shehata et al, 2020 ), e) skeleton of the health services post COVID-19 ( Kamel, 2020 ). This research is concerned with applying time-series analysis to estimate the number of COVID-19 cases.…”

Section: Related Workmentioning

confidence: 99%

Deep learning model for forecasting COVID-19 outbreak in Egypt

Marzouk

Elshaboury

AbdelLatif

et al. 2021

Process Safety and Environmental Protection

View full text Add to dashboard Cite

The World Health Organization has declared COVID-19 as a global pandemic in early 2020. A comprehensive understanding of the epidemiological characteristics of this virus is crucial to limit its spreading. Therefore, this research applies artificial intelligence-based models to predict the prevalence of the COVID-19 outbreak in Egypt. These models are long short-term memory network (LSTM), convolutional neural network, and multilayer perceptron neural network. They are trained and validated using the dataset records from 14 February 2020 to 15 August 2020. The results of the models are evaluated using the determination coefficient and root mean square error. The LSTM model exhibits the best performance in forecasting the cumulative infections for one week and one month ahead. Finally, the LSTM model with the optimal parameter values is applied to forecast the spread of this epidemic for one month ahead using the data from 14 February 2020 to 30 June 2021. The total size of infections, recoveries, and deaths is estimated to be 285,939, 234,747, and 17,251 cases on 31 July 2021. This study could assist the decision-makers in developing and monitoring policies to confront this disease.

show abstract

Section: Related Workmentioning

confidence: 99%

Deep learning model for forecasting COVID-19 outbreak in Egypt

Marzouk

Elshaboury

AbdelLatif

et al. 2021

Process Safety and Environmental Protection

View full text Add to dashboard Cite

show abstract

“…The first component of this strategy is leveraging affordable and prevalent technology. Some interventions in this category include tele-consults (like phone consultations), telemonitoring through portable and wearable devices that can be used by the patient to measure and monitor vital signs, and tele-pharmacy to support e-prescribing by qualified healthcare professionals (21,22).…”

mentioning

confidence: 99%

COVID-19: implications for NCDs and the continuity of care in Sub-Saharan Africa

2021

View full text Add to dashboard Cite

There has been a rise in non-communicable diseases (NCD) in Sub-Saharan Africa (SSA), driven by westernization, urbanization and unhealthy lifestyles. The prevalence of NCDs and their risk factors vary considerably in SSA between countries and the various sub-populations. A study documented the prevalence of stroke ranging from 0.07 to 0.3%, diabetes mellitus from 0 to 16%, hypertension from 6 to 48%, obesity from 0.4 to 43%, and current smoking from 0.4 to 71%. The numbers of these NCD cases are predicted to rise over the next decade. However, in the context of a global pandemic such as COVID-19, with the rising cases, lockdowns and deaths recorded worldwide, many people living with NCDs may find accessing care more difficult. The majority of the available resources on the subcontinent have been diverted to focus on the ongoing pandemic. This has caused interruptions in care, complication management, drug pick-up alongside the almost neglected silent NCD epidemic, with major consequences for the health system post the COVID-19 era. We explore the issues surrounding the continuity of care and offer some solutions for Sub-Saharan Africa.

show abstract

“…Until mid-July, the Egypt recorded the highest number of deaths, afterwards, South Africa became the most affected country in terms of deaths, despite the rigorous preventive measures. The situation in Egypt may be explained by the poor health system [32] and the wave of patients COVID-19 which is growing day after day. However, the results of the SEIQRDP models correspond very well to the provided data.…”

Section: Resultsmentioning

confidence: 99%

“…was in the first place in terms of death until mid-July when the south of Africa is now the country most affected by the coronavirus in terms of death [32] and the wave of patients COVID-19 which is growing day after day. However, the results of the SEIQRDP models correspond very well to the provided data.…”

Section: Resultsmentioning

confidence: 99%

Mathematical Modeling of COVID-19 Pandemic in the African Continent

Aries

Ounis

2020

Preprint

View full text Add to dashboard Cite

The present work aims to give a contribution to the understanding of the highly infectious pandemic caused by the COVID-19 in the African continent. The study focuses on the modelling and the forecasting of COVID-19 spread in the most affected African continent, namely: Morocco, Algeria, Tunisia, Egypt and South Africa and for the sake of comparison two of the most affected European country are also considered, namely: France and Italy. To this end, an epidemiological SEIQRDP model is presented, which is an adaptation of the classic SIR model widely used in mathematical epidemiology. In order to better coincide with the preventive measures taken by the governments to deal with the spread of COVID-19, this model considers the quarantine. For the identification of the models parameters, official data of the pandemic up to August 1st, 2020 are considered. The results show that the number of infections due to the use of quarantine is expected to be very low provided the isolation is effective. However, it is increasing in some countries with the early lifting of containment. Finally, the information provided by the SEIQRDP model could help to establish a realistic assessment of the short-term pandemic situation. Moreover, this will help maintain the most appropriate and necessary public health measures after the lockdown lifting.

show abstract

A view of the health services after COVID-19: an Egyptian perspective

Cited by 10 publications

References 18 publications

Deep learning model for forecasting COVID-19 outbreak in Egypt

Deep learning model for forecasting COVID-19 outbreak in Egypt

COVID-19: implications for NCDs and the continuity of care in Sub-Saharan Africa

Mathematical Modeling of COVID-19 Pandemic in the African Continent

Contact Info

Product

Resources

About