IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2022i1p610-d1019459.html
   My bibliography  Save this article

COVID-19 in German Nursing Homes: The Impact of Facilities’ Structures on the Morbidity and Mortality of Residents—An Analysis of Two Cross-Sectional Surveys

Author

Listed:
  • Benedikt Preuß

    (SOCIUM Research Center on Inequality and Social Policy, University of Bremen, 28359 Bremen, Germany)

  • Lasse Fischer

    (Competence Center for Clinical Trials Bremen (KKSB), University of Bremen, 28359 Bremen, Germany)

  • Annika Schmidt

    (Institute for Public Health and Nursing Research, University of Bremen, 28359 Bremen, Germany)

  • Kathrin Seibert

    (Institute for Public Health and Nursing Research, University of Bremen, 28359 Bremen, Germany
    Leibniz Science Campus Digital Public Health, 28359 Bremen, Germany)

  • Viktoria Hoel

    (Institute for Public Health and Nursing Research, University of Bremen, 28359 Bremen, Germany
    Leibniz Science Campus Digital Public Health, 28359 Bremen, Germany)

  • Dominik Domhoff

    (Institute for Public Health and Nursing Research, University of Bremen, 28359 Bremen, Germany
    Leibniz Science Campus Digital Public Health, 28359 Bremen, Germany)

  • Franziska Heinze

    (SOCIUM Research Center on Inequality and Social Policy, University of Bremen, 28359 Bremen, Germany)

  • Werner Brannath

    (Competence Center for Clinical Trials Bremen (KKSB), University of Bremen, 28359 Bremen, Germany)

  • Karin Wolf-Ostermann

    (Institute for Public Health and Nursing Research, University of Bremen, 28359 Bremen, Germany
    Leibniz Science Campus Digital Public Health, 28359 Bremen, Germany)

  • Heinz Rothgang

    (SOCIUM Research Center on Inequality and Social Policy, University of Bremen, 28359 Bremen, Germany
    Leibniz Science Campus Digital Public Health, 28359 Bremen, Germany)

Abstract

The COVID-19 pandemic constitutes an exceptional risk to people living and working in nursing homes (NHs). There were numerous cases and deaths among NH residents, especially at the beginning of the pandemic when no vaccines had yet been developed. Besides regional differences, individual NHs showed vast differences in the number of cases and deaths: while in some, nobody was affected, in others, many people were infected or died. We examine the relationship between facility structures and their effect on infections and deaths of NH residents and infections of staff, while considering the influence of COVID-19 prevalence among the general population on the incidence of infection in NHs. Two nationwide German surveys were conducted during the first and second pandemic waves, comprising responses from n = 1067 NHs. Different hurdle models, with an assumed Bernoulli distribution for zero density and a negative binomial distribution for the count density, were fitted. It can be shown that the probability of an outbreak, and the number of cases/deaths among residents and staff, increased with an increasing number of staff and the general spread of the virus. Therefore, reverse isolation of NH residents was an inadequate form of protection, especially at the beginning of the pandemic.

Suggested Citation

  • Benedikt Preuß & Lasse Fischer & Annika Schmidt & Kathrin Seibert & Viktoria Hoel & Dominik Domhoff & Franziska Heinze & Werner Brannath & Karin Wolf-Ostermann & Heinz Rothgang, 2022. "COVID-19 in German Nursing Homes: The Impact of Facilities’ Structures on the Morbidity and Mortality of Residents—An Analysis of Two Cross-Sectional Surveys," IJERPH, MDPI, vol. 20(1), pages 1-13, December.
    • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:610-:d:1019459
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/1/610/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/1/610/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zeileis, Achim & Kleiber, Christian & Jackman, Simon, 2008. "Regression Models for Count Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i08).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Totterman, Stephen, 2021. "Vehicle-based recreation and compliance for three beaches in northern New South Wales," OSF Preprints ja8h6, Center for Open Science.
    2. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    3. Sewando, Ponsian T. & Mdoe, N. Y. S. & Mutabazi, K. D. S, 2011. "Farmers’ preferential choice decisions to alternative cassava value chain strands in Morogoro rural district, Tanzania," MPRA Paper 29797, University Library of Munich, Germany.
    4. Lawrence N Kazembe, 2013. "A Bayesian Two Part Model Applied to Analyze Risk Factors of Adult Mortality with Application to Data from Namibia," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-10, September.
    5. Ina Falfán & Luis Zambrano, 2023. "Lacustrine Urban Blue Spaces: Low Availability and Inequitable Distribution in the Most Populated Cities in Mexico," Land, MDPI, vol. 12(1), pages 1-18, January.
    6. Guarino, Ernestino de Souza Gomes & Barbosa, Ana Márcia & Waechter, Jorge Luiz, 2012. "Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams," Ecological Modelling, Elsevier, vol. 230(C), pages 22-33.
    7. Evgenii V. Gilenko & Elena A. Mironova, 2017. "Modern claim frequency and claim severity models: An application to the Russian motor own damage insurance market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1311097-131, January.
    8. Andre Jungmittag, 2019. "Service trade restrictiveness and internationalisation of retail trade," International Economics and Economic Policy, Springer, vol. 16(2), pages 293-333, April.
    9. Bonnini, S. & Borghesi, M. & Giacalone, M., 2024. "Semi-parametric approach for modelling overdispersed count data with application to Industry 4.0," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    10. Erni, Birgit & Bonnevie, Bo T. & Oschadleus, Hans-Dieter & Altwegg, Res & Underhill, Les G., 2013. "moult: An R Package to Analyze Moult in Birds," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i08).
    11. Zeileis, Achim & Koenker, Roger, 2008. "Econometrics in R: Past, Present, and Future," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i01).
    12. Christian Balcells, 2022. "Determinants of firm boundaries and organizational performance: an empirical investigation of the Chilean truck market," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 423-461, April.
    13. Lindsay P Campbell & Daniel C Reuman & Joel Lutomiah & A Townsend Peterson & Kenneth J Linthicum & Seth C Britch & Assaf Anyamba & Rosemary Sang, 2019. "Predicting Abundances of Aedes mcintoshi, a primary Rift Valley fever virus mosquito vector," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-19, December.
    14. Moritz Berger & Gerhard Tutz, 2021. "Transition models for count data: a flexible alternative to fixed distribution models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(4), pages 1259-1283, October.
    15. Malhado, Ana C.M. & Santos, Janisson & Correia, Ricardo A. & Campos-Silva, João V. & Teles, Davi & Costa, Marcos H. & Jepson, Paul & Ladle, Richard J., 2020. "Monitoring and mapping non-governmental conservation action in Amazonia," Land Use Policy, Elsevier, vol. 94(C).
    16. Filipe Sengo Furtado & Thomas Reutterer & Nadine Schröder, 2022. "The carrot and the stick in online reviews: determinants of un-/helpfulness voting choices," Journal of Business Economics, Springer, vol. 92(4), pages 565-590, May.
    17. Taro Kanatani & Kuninori Nakagawa, 2023. "Analysis of reporting lag in daily data of COVID-19 in Japan," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-20, December.
    18. Weko, Silvia & Goldthau, Andreas, 2022. "Bridging the low-carbon technology gap? Assessing energy initiatives for the Global South," Energy Policy, Elsevier, vol. 169(C).
    19. Taghouti, Ibtissem & Martinez-Gomez, Victor & Coque, José María Garcia Alvarez, 2015. "Exploring Eu Food Safety Notifications On Agro-Food Imports: Are Mediterranean Partner Countries Discriminated?," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(2), pages 1-15, April.
    20. Xi-Ling Wang & Lin Yang & King-Pan Chan & Susan S Chiu & Kwok-Hung Chan & J S Malik Peiris & Chit-Ming Wong, 2012. "Model Selection in Time Series Studies of Influenza-Associated Mortality," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-7, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:610-:d:1019459. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.