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  1. Article ; Online: Measurement Method for Evaluating the Lockdown Policies during the COVID-19 Pandemic.

    Al Zobbi, Mohammed / Alsinglawi, Belal / Mubin, Omar / Alnajjar, Fady

    International journal of environmental research and public health

    2020  Volume 17, Issue 15

    Abstract: Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses ...

    Abstract Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses have been done to provide close support to decision-makers. We propose a method comprising data analytics and machine learning classification for evaluating the effectiveness of lockdown regulations. Lockdown regulations should be reviewed on a regular basis by governments, to enable reasonable control over the outbreak. The model aims to measure the efficiency of lockdown procedures for various countries. The model shows a direct correlation between lockdown procedures and the infection rate. Lockdown efficiency is measured by finding a correlation coefficient between lockdown attributes and the infection rate. The lockdown attributes include retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, residential, and schools. Our results show that combining all the independent attributes in our study resulted in a higher correlation (0.68) to the dependent value Interquartile 3 (Q3). Mean Absolute Error (MAE) was found to be the least value when combining all attributes.
    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus Infections/prevention & control ; Humans ; Pandemics/prevention & control ; Pneumonia, Viral/prevention & control ; Policy ; Quarantine/legislation & jurisprudence ; Quarantine/standards ; SARS-CoV-2 ; Schools
    Keywords covid19
    Language English
    Publishing date 2020-08-02
    Publishing country Switzerland
    Document type Journal Article
    ISSN 1660-4601
    ISSN (online) 1660-4601
    DOI 10.3390/ijerph17155574
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Measurement Method for Evaluating the Lockdown Policies during the COVID-19 Pandemic

    Mohammed Al Zobbi / Belal Alsinglawi / Omar Mubin / Fady Alnajjar

    International Journal of Environmental Research and Public Health, Vol 17, Iss 5574, p

    2020  Volume 5574

    Abstract: Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses ...

    Abstract Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses have been done to provide close support to decision-makers. We propose a method comprising data analytics and machine learning classification for evaluating the effectiveness of lockdown regulations. Lockdown regulations should be reviewed on a regular basis by governments, to enable reasonable control over the outbreak. The model aims to measure the efficiency of lockdown procedures for various countries. The model shows a direct correlation between lockdown procedures and the infection rate. Lockdown efficiency is measured by finding a correlation coefficient between lockdown attributes and the infection rate. The lockdown attributes include retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, residential, and schools. Our results show that combining all the independent attributes in our study resulted in a higher correlation (0.68) to the dependent value Interquartile 3 (Q3). Mean Absolute Error (MAE) was found to be the least value when combining all attributes.
    Keywords COVID-19 ; infectious disease modeling ; basic reproduction number ; machine learning ; government regulations ; spread control ; Medicine ; R ; covid19
    Subject code 006
    Language English
    Publishing date 2020-08-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Measurement Method for Evaluating the Lockdown Policies during the COVID-19 Pandemic

    Al Zobbi, Mohammed / Alsinglawi, Belal / Mubin, Omar / Alnajjar, Fady

    Int. j. environ. res. public health (Online)

    Abstract: Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses ...

    Abstract Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses have been done to provide close support to decision-makers. We propose a method comprising data analytics and machine learning classification for evaluating the effectiveness of lockdown regulations. Lockdown regulations should be reviewed on a regular basis by governments, to enable reasonable control over the outbreak. The model aims to measure the efficiency of lockdown procedures for various countries. The model shows a direct correlation between lockdown procedures and the infection rate. Lockdown efficiency is measured by finding a correlation coefficient between lockdown attributes and the infection rate. The lockdown attributes include retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, residential, and schools. Our results show that combining all the independent attributes in our study resulted in a higher correlation (0.68) to the dependent value Interquartile 3 (Q3). Mean Absolute Error (MAE) was found to be the least value when combining all attributes.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #693335
    Database COVID19

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  4. Article: A simulated measurement for COVID-19 pandemic using the effective reproductive number on an empirical portion of population: epidemiological models.

    Alsinglawi, Belal / Mubin, Omar / Alnajjar, Fady / Kheirallah, Khalid / Elkhodr, Mahmoud / Al Zobbi, Mohammed / Novoa, Mauricio / Arsalan, Mudassar / Poly, Tahmina Nasrin / Gochoo, Munkhjargal / Khan, Gulfaraz / Dev, Kapal

    Neural computing & applications

    2021  , Page(s) 1–9

    Abstract: COVID-19 as a global pandemic has had an unprecedented impact on the entire world. Projecting the future spread of the virus in relation to its characteristics for a specific suite of countries against a temporal trend can provide public health guidance ... ...

    Abstract COVID-19 as a global pandemic has had an unprecedented impact on the entire world. Projecting the future spread of the virus in relation to its characteristics for a specific suite of countries against a temporal trend can provide public health guidance to governments and organizations. Therefore, this paper presented an epidemiological comparison of the traditional SEIR model with an extended and modified version of the same model by splitting the infected compartment into asymptomatic mild and symptomatic severe. We then exposed our derived layered model into two distinct case studies with variations in mitigation strategies and non-pharmaceutical interventions (NPIs) as a matter of benchmarking and comparison. We focused on exploring the United Arab Emirates (a small yet urban centre (where clear sequential stages NPIs were implemented). Further, we concentrated on extending the models by utilizing the effective reproductive number (
    Language English
    Publishing date 2021-10-09
    Publishing country England
    Document type Journal Article
    ZDB-ID 1480526-1
    ISSN 1433-3058 ; 0941-0643
    ISSN (online) 1433-3058
    ISSN 0941-0643
    DOI 10.1007/s00521-021-06579-2
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  5. Article ; Online: Improving MapReduce privacy by implementing multi-dimensional sensitivity-based anonymization

    Mohammed Al-Zobbi / Seyed Shahrestani / Chun Ruan

    Journal of Big Data, Vol 4, Iss 1, Pp 1-

    2017  Volume 23

    Abstract: Abstract Big data is predominantly associated with data retrieval, storage, and analytics. Data analytics is prone to privacy violations and data disclosures, which can be partly attributed to the multi-user characteristics of big data environments. ... ...

    Abstract Abstract Big data is predominantly associated with data retrieval, storage, and analytics. Data analytics is prone to privacy violations and data disclosures, which can be partly attributed to the multi-user characteristics of big data environments. Adversaries may link data to external resources, try to access confidential data, or deduce private information from the large number of data pieces that they can obtain. Data anonymization can address some of these concerns by providing tools to mask and can help with concealing the vulnerable data. Currently available anonymization methods, however, are not capable of accommodating the big data scalability, granularity, and performance in efficient manners. In this paper, we introduce a novel framework that implements SQL-like Hadoop ecosystems, incorporating Pig Latin with the additional splitting of data. The splitting reduces data masking and increases the information gained from the anonymized data. Our solution provides a fine-grained masking and concealment, which is based on access level privileges of the user. We also introduce a simple classification technique that can accurately measure the anonymization extent in any anonymized data. The results of testing this classification technique and the proposed sensitivity-based anonymization method using different samples will also be discussed. These results show the significant benefits of the proposed approach, particularly regarding reduced information loss associated with the anonymization processes.
    Keywords Anonymization ; Big data ; Data privacy ; Granular access ; Hadoop ; MapReduce ; Computer engineering. Computer hardware ; TK7885-7895 ; Information technology ; T58.5-58.64 ; Electronic computers. Computer science ; QA75.5-76.95
    Subject code 005
    Language English
    Publishing date 2017-12-01T00:00:00Z
    Publisher SpringerOpen
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  6. Article ; Online: Measurement method for evaluating the lockdown policies during the COVID-19 pandemic

    Al-Zobbi, Mohammed (S32092) / Alsinglawi, Belal (S32288) / Mubin, Omar (R17188) / Alnajjar, Fady

    2020  

    Abstract: Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses ...

    Abstract Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses have been done to provide close support to decision-makers. We propose a method comprising data analytics and machine learning classification for evaluating the effectiveness of lockdown regulations. Lockdown regulations should be reviewed on a regular basis by governments, to enable reasonable control over the outbreak. The model aims to measure the efficiency of lockdown procedures for various countries. The model shows a direct correlation between lockdown procedures and the infection rate. Lockdown efficiency is measured by finding a correlation coefficient between lockdown attributes and the infection rate. The lockdown attributes include retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, residential, and schools. Our results show that combining all the independent attributes in our study resulted in a higher correlation (0.68) to the dependent value Interquartile 3 (Q3). Mean Absolute Error (MAE) was found to be the least value when combining all attributes.
    Keywords 111706 - Epidemiology ; pandemics ; communicable diseases ; machine learning ; COVID-19 (disease) ; covid19
    Subject code 006
    Language English
    Publisher Switzerland, MDPI
    Publishing country au
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Telehealth utilization during the Covid-19 pandemic: A systematic review.

    Garfan, Salem / Alamoodi, A H / Zaidan, B B / Al-Zobbi, Mohammed / Hamid, Rula A / Alwan, Jwan K / Ahmaro, Ibraheem Y Y / Khalid, Eman Thabet / Jumaah, F M / Albahri, O S / Zaidan, A A / Albahri, A S / Al-Qaysi, Z T / Ahmed, M A / Shuwandy, Moceheb Lazam / Salih, Mahmood M / Zughoul, Omar / Mohammed, K I / Momani, Fayiz

    Computers in biology and medicine

    2021  Volume 138, Page(s) 104878

    Abstract: During the coronavirus disease (COVID-19) pandemic, different technologies, including telehealth, are maximised to mitigate the risks and consequences of the disease. Telehealth has been widely utilised because of its usability and safety in providing ... ...

    Abstract During the coronavirus disease (COVID-19) pandemic, different technologies, including telehealth, are maximised to mitigate the risks and consequences of the disease. Telehealth has been widely utilised because of its usability and safety in providing healthcare services during the COVID-19 pandemic. However, a systematic literature review which provides extensive evidence on the impact of COVID-19 through telehealth and which covers multiple directions in a large-scale research remains lacking. This study aims to review telehealth literature comprehensively since the pandemic started. It also aims to map the research landscape into a coherent taxonomy and characterise this emerging field in terms of motivations, open challenges and recommendations. Articles related to telehealth during the COVID-19 pandemic were systematically searched in the WOS, IEEE, Science Direct, Springer and Scopus databases. The final set included (n = 86) articles discussing telehealth applications with respect to (i) control (n = 25), (ii) technology (n = 14) and (iii) medical procedure (n = 47). Since the beginning of the pandemic, telehealth has been presented in diverse cases. However, it still warrants further attention. Regardless of category, the articles focused on the challenges which hinder the maximisation of telehealth in such times and how to address them. With the rapid increase in the utilization of telehealth in different specialised hospitals and clinics, a potential framework which reflects the authors' implications of the future application and opportunities of telehealth has been established. This article improves our understanding and reveals the full potential of telehealth during these difficult times and beyond.
    MeSH term(s) COVID-19 ; Humans ; Pandemics/prevention & control ; SARS-CoV-2 ; Telemedicine
    Language English
    Publishing date 2021-09-20
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Review ; Systematic Review
    ZDB-ID 127557-4
    ISSN 1879-0534 ; 0010-4825
    ISSN (online) 1879-0534
    ISSN 0010-4825
    DOI 10.1016/j.compbiomed.2021.104878
    Database MEDical Literature Analysis and Retrieval System OnLINE

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