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A proportional incidence rate model for aggregated data to study the vaccine effectiveness against COVID‐19 hospital and ICU admissions.

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Title: A proportional incidence rate model for aggregated data to study the vaccine effectiveness against COVID‐19 hospital and ICU admissions.
Authors: Yan, Ping1,2, ping.yan55@gmail.com, Mullah, Muhammad Abu Shadeque1,3, Tuite, Ashleigh4
Source: Biometrics; Dec2023, Vol. 79 Issue 4, p3954-3967, 14p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 174345204
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: A proportional incidence rate model for aggregated data to study the vaccine effectiveness against COVID‐19 hospital and ICU admissions.
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  Data: <searchLink fieldCode="AU" term="%22Yan%2C+Ping%22">Yan, Ping</searchLink><relatesTo>1,2</relatesTo>, <i>ping.yan55@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Mullah%2C+Muhammad+Abu+Shadeque%22">Mullah, Muhammad Abu Shadeque</searchLink><relatesTo>1,3</relatesTo><br /><searchLink fieldCode="AU" term="%22Tuite%2C+Ashleigh%22">Tuite, Ashleigh</searchLink><relatesTo>4</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Biometrics%22">Biometrics</searchLink>; Dec2023, Vol. 79 Issue 4, p3954-3967, 14p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=174345204
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    Identifiers:
      – Type: doi
        Value: 10.1111/biom.13915
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      – Code: eng
        Text: English
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        PageCount: 14
        StartPage: 3954
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      – TitleFull: A proportional incidence rate model for aggregated data to study the vaccine effectiveness against COVID‐19 hospital and ICU admissions.
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            NameFull: Yan, Ping
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            NameFull: Mullah, Muhammad Abu Shadeque
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            NameFull: Tuite, Ashleigh
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            – D: 01
              M: 12
              Text: Dec2023
              Type: published
              Y: 2023
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              Value: 79
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