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[Spatio-temporal distribution of COVID-19 in Cologne and associated socio-economic factors in the period from February 2020 to October 2021]. / Die zeitlich-räumliche Verteilung von COVID-19 in Köln und beeinflussende soziale Faktoren im Zeitraum Februar 2020 bis Oktober 2021.
Neuhann, Florian; Ginzel, Sebastian; Buess, Michael; Wolff, Anna; Kugler, Sabine; Schlanstedt, Günter; Kossow, Annelene; Nießen, Johannes; Rüping, Stefan.
Affiliation
  • Neuhann F; Gesundheitsamt der Stadt Köln, Neumarkt 15-21, 50667, Köln, Deutschland. florian.neuhann@uni-heidelberg.de.
  • Ginzel S; Heidelberg Institute of Global Health, Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Deutschland. florian.neuhann@uni-heidelberg.de.
  • Buess M; School of Medicine, Levy Mwanawasa Medical University, Lusaka, Sambia. florian.neuhann@uni-heidelberg.de.
  • Wolff A; Fraunhofer Institut für Intelligente Analyse und Informationssysteme IAIS, Sankt Augustin, Deutschland.
  • Kugler S; Gesundheitsamt der Stadt Köln, Neumarkt 15-21, 50667, Köln, Deutschland.
  • Schlanstedt G; Gesundheitsamt der Stadt Köln, Neumarkt 15-21, 50667, Köln, Deutschland.
  • Kossow A; Fraunhofer Institut für Intelligente Analyse und Informationssysteme IAIS, Sankt Augustin, Deutschland.
  • Nießen J; Dezernat für Soziales, Gesundheit und Wohnen - Sozialplanung/Sozialberichterstattung der Stadt Köln, Köln, Deutschland.
  • Rüping S; Gesundheitsamt der Stadt Köln, Neumarkt 15-21, 50667, Köln, Deutschland.
Article in De | MEDLINE | ID: mdl-35920847
ABSTRACT
BACKGROUND AND GOALS Even in the early phase of the COVID-19 pandemic, which took a very different course globally, there were indications that socio-economic factors influenced the dynamics of disease spread, which from the second phase (September 2020) onwards particularly affected people with a lower socio-economic status. Such effects can also be seen within a large city. The present study visualizes and examines the spatio-temporal spread of all COVID-19 cases reported in Cologne, Germany (February 2020-October 2021) at district level and their possible association with socio-economic factors.

METHODS:

Pseudonymized data of all COVID-19 cases reported in Cologne were geo-coded and their distribution was mapped in an age-standardized way at district level over four periods and compared with the distribution of social factors. The possible influence of the selected factors was also examined in a regression analysis in a model with case growth rates.

RESULTS:

The small-scale local infection process changed during the pandemic. Neighborhoods with weaker socio-economic indices showed higher incidence over a large part of the pandemic course, with a positive correlation between poverty risk factors and age-standardized incidence. The strength of this correlation changed over time.

CONCLUSION:

The timely observation and analysis of the local spread dynamics reveals the positive correlation of disadvantaging socio-economic factors on the incidence rate of COVID-19 at the level of a large city and can help steer local containment measures in a targeted manner.
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Full text: 1 Database: MEDLINE Main subject: COVID-19 Type of study: Etiology_studies / Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Limits: Humans Country/Region as subject: Europa Language: De Year: 2022 Type: Article

Full text: 1 Database: MEDLINE Main subject: COVID-19 Type of study: Etiology_studies / Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Limits: Humans Country/Region as subject: Europa Language: De Year: 2022 Type: Article