Social disparities in the first wave of COVID-19 incidence rates in Germany: a county-scale explainable machine learning approach.

ABSTRACT:

Objectives

Knowledge about the socioeconomic spread of the first wave of COVID-19 infections in Germany is scattered across different studies. We explored whether COVID-19 incidence rates differed between counties according to their socioeconomic characteristics using a wide range of indicators.

Data and method

We used data from the Robert Koch-Institute (RKI) on 204 217 COVID-19 diagnoses in the total German population of 83.1 million, distinguishing five distinct periods between 1 January and 23 July 2020. For each period, we calculated age-standardised incidence rates of COVID-19 diagnoses on the county level and characterised the counties by 166 macro variables. We trained gradient boosting models to predict the age-standardised incidence rates with the macrostructures o

SUBMITTER: Doblhammer G 

PROVIDER: S-EPMC8852237 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature