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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

BACKGROUND AND GOALSEven 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 lo...

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Published in:Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Gesundheitsforschung, Gesundheitsschutz, 2022-09, Vol.65 (9), p.853-862
Main Authors: Neuhann, Florian, Ginzel, Sebastian, Buess, Michael, Wolff, Anna, Kugler, Sabine, Schlanstedt, Günter, Kossow, Annelene, Nießen, Johannes, Rüping, Stefan
Format: Article
Language:ger
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Summary:BACKGROUND AND GOALSEven 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. METHODSPseudonymized 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. RESULTSThe 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. CONCLUSIONThe 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.
ISSN:1437-1588
DOI:10.1007/s00103-022-03573-4