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. 2023 Feb 28;20(5):4375.
doi: 10.3390/ijerph20054375.

Spatial Distribution of COVID-19 Hospitalizations and Associated Risk Factors in Health Insurance Data Using Bayesian Spatial Modelling

Boris Kauhl  1 , Jörg König  1 , Sandra Wolf  2
Affiliations

Spatial Distribution of COVID-19 Hospitalizations and Associated Risk Factors in Health Insurance Data Using Bayesian Spatial Modelling

Boris Kauhl et al. Int J Environ Res Public Health. .

Abstract

The onset of COVID-19 across the world has elevated interest in geographic information systems (GIS) for pandemic management. In Germany, however, most spatial analyses remain at the relatively coarse level of counties. In this study, we explored the spatial distribution of COVID-19 hospitalizations in health insurance data of the AOK Nordost health insurance. Additionally, we explored sociodemographic and pre-existing medical conditions associated with hospitalizations for COVID-19. Our results clearly show strong spatial dynamics of COVID-19 hospitalizations. The main risk factors for hospitalization were male sex, being unemployed, foreign citizenship, and living in a nursing home. The main pre-existing diseases associated with hospitalization were certain infectious and parasitic diseases, diseases of the blood and blood-forming organs, endocrine, nutritional and metabolic diseases, diseases of the nervous system, diseases of the circulatory system, diseases of the respiratory system, diseases of the genitourinary and symptoms, and signs and findings not classified elsewhere.

Keywords: Bayesian spatial modelling; COVID-19; GIS; health insurance.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Accumulated one-year incidence of COVID-19 hospitalizations (2021).
See this image and copyright information in PMC

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References

    1. Sohrabi C., Alsafi Z., O’Neill N., Khan M., Kerwan A., Al-Jabir A., Iosifidis C., Agha R. World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19) Int. J. Surg. 2020;76:71–76. doi: 10.1016/j.ijsu.2020.02.034. - DOI - PMC - PubMed
    1. United Nations UN Response to COVID-19. [(accessed on 8 December 2022)]. Available online: https://www.un.org/en/coronavirus/UN-response.
    1. Aral N., Bakir H. Spatiotemporal Analysis of Covid-19 in Turkey. Sustain. Cities Soc. 2022;76:103421. doi: 10.1016/j.scs.2021.103421. - DOI - PMC - PubMed
    1. Ärzteblatt.de Rückblick 2020: Die Welt im Griff des Virus. [(accessed on 29 November 2022)]. Available online: https://www.aerzteblatt.de/nachrichten/119821/Rueckblick-2020-Die-Welt-i....
    1. Felbermayr G., Hinz J., Chowdhry S. Après-ski: The spread of coronavirus from Ischgl through Germany. Ger. Econ. Rev. 2021;22:415–446. doi: 10.1515/ger-2020-0063. - DOI