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  1. Book ; Online: Leveraging Data Science for Global Health

    Celi, Leo Anthony / Majumder, Maimuna S. / Ordóñez, Patricia / Osorio, Juan Sebastian / Paik, Kenneth E. / Somai, Melek

    2020  

    Author's details edited by Leo Anthony Celi, Maimuna S. Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E. Paik, Melek Somai
    Keywords Health informatics ; Health economics ; Medizin ; Informatik
    Subject Computerwissenschaft ; Humanmedizin ; Heilkunst ; Medicine
    Subject code 502.85
    Language English
    Size 1 Online-Ressource (XII, 475 p. 196 illus., 175 illus. in color)
    Edition 1st ed. 2020
    Publisher Springer International Publishing ; Imprint: Springer
    Publishing place Cham
    Document type Book ; Online
    HBZ-ID HT020544767
    ISBN 978-3-030-47994-7 ; 9783030479930 ; 9783030479954 ; 9783030479961 ; 3-030-47994-3 ; 3030479935 ; 3030479951 ; 303047996X
    DOI 10.1007/978-3-030-47994-7
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Online: Leveraging Data Science for Global Health

    Celi, Leo Anthony / Majumder, Maimuna S. / Ordóñez, Patricia / Osorio, Juan Sebastian / Paik, Kenneth E. / Somai, Melek

    2020  

    Abstract: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine ... ...

    Abstract This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure - and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources - including news media, social media, Google Trends, and Google Street View - can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient
    Keywords Medicine (General) ; Information technology ; Economic theory. Demography ; Medizin ; Informatik
    Subject Computerwissenschaft ; Humanmedizin ; Heilkunst ; Medicine
    Size 1 electronic resource (475 pages)
    Publisher Springer Nature
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT020676424
    ISBN 9783030479947 ; 3030479943
    DOI 10.1007/978-3-030-47994-7
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Book ; Online ; E-Book: Ebola's message

    Evans, Nicholas G. / Smith, Tara C. / Majumder, Maimuna S.

    public health and medicine in the Twenty-First century

    (Basic bioethics)

    2016  

    Author's details edited by Nicholas G. Evans, Tara C. Smith, and Maimuna S. Majumder
    Series title Basic bioethics
    Language English
    Size 1 Online-Ressource (xvii, 270 Seiten)
    Publisher MIT Press
    Publishing place Cambridge, Massachusetts
    Publishing country United States
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT019441827
    ISBN 978-0-262-33619-2 ; 9780262035071 ; 0-262-33619-7 ; 0262035073
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  4. Article ; Online: US COVID-19 clinical trial leadership gender disparities.

    Sehgal, Neil K R / Brownstein, John S / Majumder, Maimuna S / Tuli, Gaurav

    The Lancet. Digital health

    2023  Volume 5, Issue 3, Page(s) e109–e111

    MeSH term(s) Humans ; COVID-19 ; Leadership ; Research Personnel ; Sex Distribution
    Language English
    Publishing date 2023-02-13
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ISSN 2589-7500
    ISSN (online) 2589-7500
    DOI 10.1016/S2589-7500(23)00017-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Corrigendum to "Modeling vaccination coverage during the 2022 central Ohio measles outbreak: a cross-sectional study" [The Lancet Regional Health-Americas 2023; 23: 100533].

    Martoma, Rosemary A / Washam, Matthew / Martoma, Joshua C / Cori, Anne / Majumder, Maimuna S

    Lancet regional health. Americas

    2024  Volume 30, Page(s) 100677

    Abstract: This corrects the article DOI: 10.1016/j.lana.2023.100533.]. ...

    Abstract [This corrects the article DOI: 10.1016/j.lana.2023.100533.].
    Language English
    Publishing date 2024-01-23
    Publishing country England
    Document type Published Erratum
    ISSN 2667-193X
    ISSN (online) 2667-193X
    DOI 10.1016/j.lana.2024.100677
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis.

    Majumder, Maimuna S / Cusick, Marika / Rose, Sherri

    BMJ open

    2023  Volume 13, Issue 2, Page(s) e065751

    Abstract: Objectives: As highlighted by the COVID-19 pandemic, researchers are eager to make use of a wide variety of data sources, both government-sponsored and alternative, to characterise the epidemiology of infectious diseases. The objective of this study is ... ...

    Abstract Objectives: As highlighted by the COVID-19 pandemic, researchers are eager to make use of a wide variety of data sources, both government-sponsored and alternative, to characterise the epidemiology of infectious diseases. The objective of this study is to investigate the strengths and limitations of sources currently being used for research.
    Design: Retrospective descriptive analysis.
    Primary and secondary outcome measures: Yearly number of national-level and state-level disease-specific case counts and disease clusters for three diseases (measles, mumps and varicella) during a 5-year study period (2013-2017) across four different data sources: Optum (health insurance billing claims data), HealthMap (online news surveillance data), Morbidity and Mortality Weekly Reports (official government reports) and National Notifiable Disease Surveillance System (government case surveillance data).
    Results: Our study demonstrated drastic differences in reported infectious disease incidence across data sources. When compared with the other three sources of interest, Optum data showed substantially higher, implausible standardised case counts for all three diseases. Although there was some concordance in identified state-level case counts and disease clusters, all four sources identified variations in state-level reporting.
    Conclusions: Researchers should consider data source limitations when attempting to characterise the epidemiology of infectious diseases. Some data sources, such as billing claims data, may be unsuitable for epidemiological research within the infectious disease context.
    MeSH term(s) Humans ; United States/epidemiology ; Information Sources ; Pandemics ; Retrospective Studies ; COVID-19/epidemiology ; Data Analysis
    Language English
    Publishing date 2023-02-28
    Publishing country England
    Document type Journal Article ; Research Support, U.S. Gov't, P.H.S.
    ZDB-ID 2599832-8
    ISSN 2044-6055 ; 2044-6055
    ISSN (online) 2044-6055
    ISSN 2044-6055
    DOI 10.1136/bmjopen-2022-065751
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Early transmissibility assessment of a novel coronavirus in Wuhan, China.

    Majumder, Maimuna S / Mandl, Kenneth D

    SSRN

    2020  , Page(s) 3524675

    Keywords covid19
    Language English
    Publishing date 2020-01-24
    Publishing country United States
    Document type Preprint
    ISSN 1556-5068
    ISSN (online) 1556-5068
    DOI 10.2139/ssrn.3524675
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Early in the Epidemic: Impact of preprints on global discourse of 2019-nCoV transmissibility.

    Majumder, Maimuna S / Mandl, Kenneth D

    SSRN

    2020  , Page(s) 3536663

    Keywords covid19
    Language English
    Publishing date 2020-02-12
    Publishing country United States
    Document type Preprint
    ISSN 1556-5068
    ISSN (online) 1556-5068
    DOI 10.2139/ssrn.3536663
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

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  9. Article ; Online: Measuring concordance of data sources used for infectious disease research in the USA

    Maimuna S Majumder / Sherri Rose / Marika Cusick

    BMJ Open, Vol 13, Iss

    a retrospective data analysis

    2023  Volume 2

    Abstract: Objectives As highlighted by the COVID-19 pandemic, researchers are eager to make use of a wide variety of data sources, both government-sponsored and alternative, to characterise the epidemiology of infectious diseases. The objective of this study is to ...

    Abstract Objectives As highlighted by the COVID-19 pandemic, researchers are eager to make use of a wide variety of data sources, both government-sponsored and alternative, to characterise the epidemiology of infectious diseases. The objective of this study is to investigate the strengths and limitations of sources currently being used for research.Design Retrospective descriptive analysis.Primary and secondary outcome measures Yearly number of national-level and state-level disease-specific case counts and disease clusters for three diseases (measles, mumps and varicella) during a 5-year study period (2013–2017) across four different data sources: Optum (health insurance billing claims data), HealthMap (online news surveillance data), Morbidity and Mortality Weekly Reports (official government reports) and National Notifiable Disease Surveillance System (government case surveillance data).Results Our study demonstrated drastic differences in reported infectious disease incidence across data sources. When compared with the other three sources of interest, Optum data showed substantially higher, implausible standardised case counts for all three diseases. Although there was some concordance in identified state-level case counts and disease clusters, all four sources identified variations in state-level reporting.Conclusions Researchers should consider data source limitations when attempting to characterise the epidemiology of infectious diseases. Some data sources, such as billing claims data, may be unsuitable for epidemiological research within the infectious disease context.
    Keywords Medicine ; R
    Subject code 006
    Language English
    Publishing date 2023-02-01T00:00:00Z
    Publisher BMJ Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  10. Article: An Epidemic Model for Multi-Intervention Outbreaks.

    Schaber, Kathryn L / Kumar, Sagar / Lubwama, Baker / Desai, Angel / Majumder, Maimuna S

    medRxiv : the preprint server for health sciences

    2023  

    Abstract: Modeling is an important tool to utilize at the beginning of an infectious disease outbreak, as it allows estimation of parameters - such as the basic reproduction number, ...

    Abstract Modeling is an important tool to utilize at the beginning of an infectious disease outbreak, as it allows estimation of parameters - such as the basic reproduction number,
    Language English
    Publishing date 2023-06-29
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.06.27.23291973
    Database MEDical Literature Analysis and Retrieval System OnLINE

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