17 10 20655 https://socictopen.socict.org/files/original/dd16bf820146beed2939a26a2cbba4a2.pdf 5509ea0d9a695fc64d5e5f1b8f11db64 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Predictors of Length of Hospital Stay, Mortality, and Outcomes Among Hospitalised COVID-19 Patients in Saudi Arabia: A Cross-Sectional Study. Creator An entity primarily responsible for making the resource Abdallah Y. Naser, Hassan Alwafi, Sultan Qanash, Ahmad S Brinji, Maher A Ghazawi, Basil Alotaibi, Ahmad Alghamdi, Aisha Alrhmani, Reham Fatehaldin, Ali Alelyani, Abdulrhman Basfar, Abdulaziz AlBarakati, Ghaidaa F Alsharif, Elaf F Obaid, Mohammed Shabrawishi Description An account of the resource COVID-19 pandemic is a major strain on health and economic systems, with rapidly increasing demand for in patients' facilities. Disease diagnosis and estimating patients at higher risk is important for the optimal management during the pandemic. This study aimed to identify the predictors of mortality and length of hospital stay in COVID-19 patients. A retrospective cross-sectional study was conducted between March 2020 and August 2020 at Al-Noor Specialist Hospital in Mecca, Saudi Arabia. All patients who were admitted and had a confirmed COVID-19 diagnosis by a real-time polymerase chain reaction (PCR) were included in the study. Descriptive statistics were used to describe patients' demographic characteristics, laboratory findings, and clinical outcomes. Multiple logistic/linear regression analysis was used to identify predictors of death and length of stay at the hospital. A total of 706 patients were hospitalised for COVID-19. The mean age was 48.0 years (SD: 15.6 years). More than half of the patients (68.5%; n= 292) were males. The median duration of stay at the hospital was 6.0 days (IQR: 300-10:00). The prevalence rate of venous thromboembolism (VTE) among the patients was 3.0% (n= 21). In the multivariate logistic regression analysis, age (AOR: 1.05; 1.02-1.09), patients with end-stage renal disease (AOR: 6.44; 2.20-18.87), low Oxygen saturation SPO2 (AOR: 9.92; 4.19-23.50), D.dimer >0.5 (AOR: 13.31; 5.45-32.49), ESR>10 mm/h (AOR: 4.08; 1.72-9.68), Ferritin>400mcg/L (AOR: 18.55; 6.89-49.96), and Procalcitonin>0.5ug/L (AOR: 8.23; 1.81- 37.40) were associated with a higher risk of death among patients with COVID-19. Patients with VTE (AOR: 12.86; 3.07- 53.92) were at higher risk of death due to COVID-19. Hospitalised COVID-19 patients have multiple negative consequences in terms of their laboratory findings, signs and symptoms. Age and end-stage renal diseases have a significant impact on the mortality rate and the length of hospital stay among COVID-19 patients. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource Saudi Arabia, ICU, covid-19, survival, Length of Stay, Hospitalisation Identifier An unambiguous reference to the resource within a given context 10.2147/JMDH.S304788 Source A related resource from which the described resource is derived Journal of multidisciplinary healthcare https://socictopen.socict.org/files/original/0c6ffe5c3c102e1dcbdd28e06af45f5f.pdf bdc61c15bf724e996a41157763bf5d74 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Charge-transfer chemistry of azithromycin, the antibiotic used worldwide to treat the coronavirus disease (COVID-19). Part III: A green protocol for facile synthesis of complexes with TCNQ, DDQ, and TFQ acceptors. Creator An entity primarily responsible for making the resource Abdel Majid A Adam, Hosam A Saad, Moamen S Refat, Mohamed S Hegab, Amnah M Alsuhaibani Description An account of the resource Investigating the chemical properties of molecules used to combat the COVID-19 pandemic is of vital and pressing importance. In continuation of works aimed to explore the charge-transfer chemistry of azithromycin, the antibiotic used worldwide to treat COVID-19, the disease resulting from infection with the novel SARS-CoV-2 virus, in this work, a highly efficient, simple, clean, and eco-friendly protocol was used for the facile synthesis of charge-transfer complexes (CTCs) containing azithromycin and three π-acceptors: 7,7,8,8-tetracyanoquinodimethane (TCNQ), 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ), and tetrafluoro-1,4-benzoquinone (TFQ). This protocol involves grinding bulk azithromycin as the donor (D) with the investigated acceptors at a 1:1 M ratio at room temperature without any solvent. We found that this protocol is environmentally benign, avoids hazardous organic solvents, and generates the desired CTCs with excellent yield (92-95%) in a straightforward means. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, SARS-CoV-2, azithromycin, Charge-transfer, DDQ, Eco-friendly, TCNQ, TFQ Identifier An unambiguous reference to the resource within a given context 10.1016/j.molliq.2021.116250 Source A related resource from which the described resource is derived Journal of molecular liquids https://socictopen.socict.org/files/original/e2cfe5c15c3c3cf86299f5274bb74ae4.pdf ad3ac50feefa92dc9e6c706b657a3bb1 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Imaging of COVID-19 simulators Creator An entity primarily responsible for making the resource Abdelghany Mohammed Motawea, Suzan Omar, Rabab Yasin Description An account of the resource Abstract Background Coronavirus (COVID-19) pneumonia emerged in Wuhan, China, in December 2019. It was highly contagious spreading all over the world, with a rapid increase in the number of deaths. The reported cases have reached more than 14 million with more than 600,000 deaths around the world. So, the pandemic of COVID-19 became a surpassing healthcare crisis with an intensive load on the healthcare resources. In this study, the aim was to differentiate COVID-19 pneumonia from its mimickers as atypical infection, interstitial lung diseases, and eosinophilic lung diseases based on CT, clinical, and laboratory findings. Results This retrospective study included 260 patients, of which 220 were confirmed as COVID-19 positive by two repeated RT-PCR test and 40 were classified as non-COVID by two repeated negative RT-PCR test or identification of other pathogens, other relevant histories, or clinical findings. In this study, 158 patients were male (60.7 %) and 102 patients were female (39.3%). There was 60.9% of the COVID-19 group were male and 39.1% were female. Patients in the non-COVID group were significantly older (the mean age was 46.4) than those in the confirmed COVID-19 group (35.2y). In the COVID-19 group, there was exposure history to positive cases in 84.1% while positive exposure history was 20% in the non-COVID group. Conclusion The spectrum of CT imaging findings in COVID-19 pneumonia is wide that could be contributed by many other diseases making the interpretation of chest CTs nowadays challenging to differentiate between different diseases having the same signs and act as deceiving simulators in the era of COVID-19. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource atypical pneumonia, Interstitial lung diseases, CT computed tomography, COVID-19 coronavirus infections Identifier An unambiguous reference to the resource within a given context 10.1186/s43055-020-00379-9 Source A related resource from which the described resource is derived Biotemas Publisher An entity responsible for making the resource available Universidade Federal de Santa Catarina Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medical physics. Medical radiology. Nuclear medicine https://socictopen.socict.org/files/original/7823483d323587a02caf6acc78c6ca76.pdf 02d0aaebe6315cfcd9a62f46507d371f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparative study of machine learning methods for COVID-19 transmission forecasting. Creator An entity primarily responsible for making the resource Abdelkader Dairi, Fouzi Harrou, Abdelhafid Zeroual, Mohamad Mazen Hittawe, Ying Sun Description An account of the resource Within the recent pandemic, scientists and clinicians are engaged in seeking new technology to stop or slow down the COVID-19 pandemic. The benefit of machine learning, as an essential aspect of artificial intelligence, on past epidemics offers a new line to tackle the novel Coronavirus outbreak. Accurate short-term forecasting of COVID-19 spread plays an essential role in improving the management of the overcrowding problem in hospitals and enables appropriate optimization of the available resources (i.e., materials and staff).This paper presents a comparative study of machine learning methods for COVID-19 transmission forecasting. We investigated the performances of deep learning methods, including the hybrid convolutional neural networks-Long short-term memory (LSTM-CNN), the hybrid gated recurrent unit-convolutional neural networks (GAN-GRU), GAN, CNN, LSTM, and Restricted Boltzmann Machine (RBM), as well as baseline machine learning methods, namely logistic regression (LR) and support vector regression (SVR). The employment of hybrid models (i.e., LSTM-CNN and GAN-GRU) is expected to eventually improve the forecasting accuracy of COVID-19 future trends. The performance of the investigated deep learning and machine learning models was tested using confirmed and recovered COVID-19 cases time-series data from seven impacted countries: Brazil, France, India, Mexico, Russia, Saudi Arabia, and the US. The results reveal that hybrid deep learning models can efficiently forecast COVID-19 cases. Also, results confirmed the superior performance of deep learning models compared to the two considered baseline machine learning models. Furthermore, results showed that LSTM-CNN achieved improved performances with an averaged mean absolute percentage error of 3.718%, among others. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, hybrid deep learning, short-term forecasting, GAN-GRU, LSTM-CNN Identifier An unambiguous reference to the resource within a given context 10.1016/j.jbi.2021.103791 Source A related resource from which the described resource is derived Journal of biomedical informatics https://socictopen.socict.org/files/original/cdc63a8fd47dd77a22b78fd51602755b.pdf b21af1e4d62ecb8140f8fbffa15b6247 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Agricultura sostenible Description An account of the resource Dominio científico: Agricultura sostenible Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Paisaje agrario en contextos periurbanos mediterráneos: el caso del Gran Sousse (Túnez) Creator An entity primarily responsible for making the resource Abdelkarim Hamrita, Rafael Mata, Nieves López-Estébanez, Hichem Rejeb Description An account of the resource La protección de la agricultura periurbana mediante la zonificación de determinados suelos como no urbanizables por los instrumentos de planificación urbanística y territorial resulta insuficiente frente a las fuertes presiones de usos residenciales, industriales, infraestructurales y, en ocasiones, turísticos que provocan su fragilidad. En este texto se aborda la potencialidad del paisaje para activar este tipo de agricultura que se desenvuelve bajo influencia urbana directa y se adopta el Landscape Character Assessment como metodología sistemática de identificación y caracterización de los paisajes de la agricultura periurbana del Gran Sousse, la principal aglomeración urbana y turística del Sahel tunecino, con objeto de su evaluación, ordenación y promoción. Se adopta la noción de carácter del paisaje y se relaciona con las políticas públicas de gestión de los espacios agrarios periurbanos tunecinos y la percepción social, mediante entrevistas a una muestra de actores locales y regionales. Se analiza la diversidad paisajística concretada en Áreas Paisajísticas de Agricultura Periurbana (APAP), caracterizadas a partir de su particular fisonomía, y de los principales elementos y funcionamiento pasado y presente. El estudio concluye con la propuesta de un proyecto de paisaje como infraestructura verde, que implica un modelo de gestión de conflictos de acuerdo con las necesidades propias del paisaje, de los agricultores y de la población que lo percibe y lo utiliza como espacio abierto, fortaleciendo su función de productor de alimentos de calidad y de proximidad, como un ejercicio de participación y gobernanza territorial. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource agricultura periurbana, carácter del paisaje, gobernanza, multifuncionalidad, proyecto de paisaje Identifier An unambiguous reference to the resource within a given context 10.21138/bage.3143 Source A related resource from which the described resource is derived Boletín de la Asociación de Geógrafos Españoles Publisher An entity responsible for making the resource available Asociación Española de Geografía Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Geography (General), Environmental sciences Relation A related resource <a href="https://bage.age-geografia.es/ojs/index.php/bage/article/view/3143" target="_blank" rel="noreferrer noopener">https://bage.age-geografia.es/ojs/index.php/bage/article/view/3143</a> https://socictopen.socict.org/files/original/a2e6a4f290f7642208a1e6f2a72107df.pdf d3feec05f15233ef63ff5374a95c72dc Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource MERS-CoV in Upper Respiratory Tract and Lungs of Dromedary Camels, Saudi Arabia, 2013–2014 Creator An entity primarily responsible for making the resource Abdelmalik I. Khalafalla, Xiaoyan Lu, Abdullah I.A. Al-Mubarak, Abdul Hafeed S. Dalab, Khalid A.S. Al-Busadah, Dean D. Erdman Description An account of the resource To assess the temporal dynamics of Middle East respiratory syndrome coronavirus (MERS-CoV) infection in dromedary camels, specimens were collected at 1–2 month intervals from 2 independent groups of animals during April 2013–May 2014 in Al-Ahsa Province, Saudi Arabia, and tested for MERS-CoV RNA by reverse transcription PCR. Of 96 live camels, 28 (29.2%) nasal swab samples were positive; of 91 camel carcasses, 56 (61.5%) lung tissue samples were positive. Positive samples were more commonly found among young animals (4 years of age). The proportions of positive samples varied by month for both groups; detection peaked during November 2013 and January 2014 and declined in March and May 2014. These findings further our understanding of MERS-CoV infection in dromedary camels and may help inform intervention strategies to reduce zoonotic infections. Date A point or period of time associated with an event in the lifecycle of the resource 2015 Subject The topic of the resource MERS-CoV, Dromedary camels, Saudi Arabia, Abattoir, Viruses, Middle East respiratory syndrome Identifier An unambiguous reference to the resource within a given context DOI: 10.3201/eid2107.150070 Source A related resource from which the described resource is derived Emerging Infectious Diseases Publisher An entity responsible for making the resource available Centers for Disease Control and Prevention Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Infectious and parasitic diseases, Medicine Language A language of the resource EN https://socictopen.socict.org/files/original/21b240f4b1be0968835879d42609b0e4.pdf a39b446f75d1fd9bd034aa569b76a0cd Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Does improvement in the environmental sustainability rating help to reduce the COVID-19 cases? Controlling financial development, price level and carbon damages. Creator An entity primarily responsible for making the resource Abdelmohsen A. Nassani, Muhammad Moinuddin Qazi Abro, Sameh E. Askar, Muhammad Khalid Anser, Khalid Zaman, Bushra Usman, Shabir Hyder Description An account of the resource The study's objective is to evaluate the impact of environmental sustainability rating, financial development, changes in the price level and carbon damages on the new COVID-19 cases in a cross-sectional panel of 17 countries. The study developed two broad models to analyse the relationship between the stated factors at the current level and forecast level. The results show that improvement in the environmental sustainability rating and financial efficiency reduces the COVID-19 cases, while continued economic growth and changes in price level likely to exacerbate the COVID-19 cases across countries. The forecast results suggest the U-shaped relationship between COVID-19 cases and carbon damages controlling financial development, price level and environmental sustainability rating. The variance decomposition analysis shows that carbon damages, environmental sustainability rating and price level changes will largely influence COVID-19 cases over the next year. The soundness of economic and ecological regulated policies would be helpful to contain coronavirus cases globally. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19 pandemic, Carbon damages, Environmental sustainability rating, Financial development, price level, Robust least squares regression Identifier An unambiguous reference to the resource within a given context 10.1007/s11356-021-13873-y Source A related resource from which the described resource is derived Environmental science and pollution research international https://socictopen.socict.org/files/original/0176f6e470f60de668ddcc86b644f251.pdf b1a341d3152684d16239977746787197 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource To which extent a convalescent plasma therapy could be a benefit for COVID-19 patients? Creator An entity primarily responsible for making the resource Abdelmonem Ali, Ahmed Abuelhassan, Ebtehal Fawzi, Alfatih Albasher, Sheima Elbasheer, Nagia Suliman, Alaa Elhussein, Mayada Ali Description An account of the resource The emergence of an unprecedented pandemic SARS-COV-2 caused perplexed in the medical community because of a high infection rate and rising mortality among COVID-19 patients. Till now, there is no particular treatment for the disease; nevertheless, there is an extensive effort from scientists to find out an immediate therapeutic plan to show how to deal with the current situation. One of the solutions currently presented is Convalescence plasma (CP). Through this narrative review, we will shed light on CP's efficiency as a therapeutic agent for COVID-19, especially there is no proven vaccine or antiviral available up to date. CP could be considered one of the therapeutic approaches, but some limitations are still considered before it is established as a therapeutic agent. Along with evaluating CP from blood donors, the plasma companies could take future steps by manufacturing a target dose of globulins that contain standardized antibody, to reach the terms of health setting administering therapy. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource covid-19, neutralizing antibodies, transfusion, convalescence plasma Identifier An unambiguous reference to the resource within a given context 10.47108/jidhealth.Vol3.Iss4.79 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine, Medicine (General) https://socictopen.socict.org/files/original/78ebf49673bbcfe07a5fa1990824847d.pdf 9a6e19e047c5cfe71bbf168d49d29255 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Convalescent Plasma a Potential Therapy in Covid-19 Patients in Low Resource Setting Creator An entity primarily responsible for making the resource Abdelrahman H. Abdelmoneim, Mujahed I. Mustafa, Raghda Hatim Abdalhaleem Adlan, Noun Eltayeb Ahmed Abdulgader, Hiba Awadelkareem Osman Fadl, Nosaiba Kamal Alhassan, Sahar G. Elbager Description An account of the resource Background: The COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At the time of writing, neither a cure nor a vaccine has been approved by the World health organization (WHO) for this disease. Given the fact that the severe acute respiratory syndrome coronavirus (SARS) and Middle East Respiratory Syndrome (MERS) viruses have a genetic sequencing similar to SARS-CoV-2, and since the use of convalescent plasma therapy (CP) has proved its efficacy in SARS and MERS virus infections, researchers are starting to focus more on it as a possible therapy for the COVID-19 disease. The main objective of this rapid review is to report and summarize the published evidence on the role of convalescent plasma therapy in the current COVID-19 pandemic. Method: The PICO method was used to establish the review question. Moreover, papers were gathered from PubMed and Google scholar, critically appraised for the best evidence. Piersons 5-component scheme was used to check the quality of the review papers. Results: After website screening: 10 papers in PubMed and 6 papers from Google scholars were retrieved. There were encouraging reports regarding the uses of CP in the previous viral outbreaks likes SARS and Ebola, yet there is still a doubt on the efficacy of this mode of therapy in the current COVID-19 pandemic. Conclusion: CP is a very promising treatment approach for COVID-19 patients; however, more clinical trials are required to validate the effectiveness of this therapy. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource covid-19, SARS-CoV-2, Therapy, Convalescent plasma therapy Identifier An unambiguous reference to the resource within a given context 10.18502/sjms.v15i5.7175 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine https://socictopen.socict.org/files/original/3d618002e3323d9b953fda74fe672d01.pdf 9b85cc2dace05f17c37e4a0c339b50b3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Optimal Containment Control Strategy of the Second Phase of the COVID-19 Lockdown in Morocco Creator An entity primarily responsible for making the resource Abdessamad Tridane, Omar Zakary, Mostafa Rachik, Mustapha Lhous, El Mostafa Magri Description An account of the resource This work investigates the optimal control of the second phase of the COVID-19 lockdown in Morocco. The model consists of susceptible, exposed, infected, recovered, and quarantine compartments (SEIRQD model), where we take into account contact tracing, social distancing, quarantine, and treatment measures during the nationwide lockdown in Morocco. First, we present different components of the model and their interactions. Second, to validate our model, the nonlinear least-squares method is used to estimate the model’s parameters by fitting the model outcomes to real data of the COVID-19 in Morocco. Next, to investigate the impact of optimal control strategies on this pandemic in the country. We also give numerical simulations to illustrate and compare the obtained results with the actual situation in Morocco. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource covid-19, Optimal control, treatment, contact-tracing, lockdown Identifier An unambiguous reference to the resource within a given context 10.3390/app10217559 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Chemistry, Engineering (General). Civil engineering (General), Technology, Physics