2 datasets found
  1. f

    Independent variables for modelling child survival determinants in Africa.

    • figshare.com
    xls
    Updated Jul 10, 2024
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    Sunday A. Adedini; Seun Stephen Anjorin; Jacob Wale Mobolaji; Elvis Anyaehiechukwu Okolie; Sanni Yaya (2024). Independent variables for modelling child survival determinants in Africa. [Dataset]. http://doi.org/10.1371/journal.pgph.0003022.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jul 10, 2024
    Dataset provided by
    PLOS Global Public Health
    Authors
    Sunday A. Adedini; Seun Stephen Anjorin; Jacob Wale Mobolaji; Elvis Anyaehiechukwu Okolie; Sanni Yaya
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Africa
    Description

    Independent variables for modelling child survival determinants in Africa.

  2. f

    Results of scenario analysis for projected demographic events and impact of...

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    Lumbwe Chola; Shelley McGee; Aviva Tugendhaft; Eckhart Buchmann; Karen Hofman (2023). Results of scenario analysis for projected demographic events and impact of family planning on maternal, newborn and child mortality (shown are changes in 2030). [Dataset]. http://doi.org/10.1371/journal.pone.0130077.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Lumbwe Chola; Shelley McGee; Aviva Tugendhaft; Eckhart Buchmann; Karen Hofman
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    All essential maternal and child health interventions are scaled up to 99% coverage. Potential life years gained = total deaths multiplied by life expectancy (27 years for mothers and 60 years for neonates and children). CPR = Contraceptive prevalence rate. *Results only for CPR increase by 5%. Figures rounded to the nearest 100.Results of scenario analysis for projected demographic events and impact of family planning on maternal, newborn and child mortality (shown are changes in 2030).

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Email
Click to copy link
Link copied
Close
Cite
Sunday A. Adedini; Seun Stephen Anjorin; Jacob Wale Mobolaji; Elvis Anyaehiechukwu Okolie; Sanni Yaya (2024). Independent variables for modelling child survival determinants in Africa. [Dataset]. http://doi.org/10.1371/journal.pgph.0003022.t001

Independent variables for modelling child survival determinants in Africa.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jul 10, 2024
Dataset provided by
PLOS Global Public Health
Authors
Sunday A. Adedini; Seun Stephen Anjorin; Jacob Wale Mobolaji; Elvis Anyaehiechukwu Okolie; Sanni Yaya
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
Africa
Description

Independent variables for modelling child survival determinants in Africa.

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