Statistical analysis of three data sources for Covid-19 monitoring in Rhineland-Palatinate, Germany

Publication date: Sep 21, 2023

In Rhineland-Palatinate, Germany, a system of three data sources has been established to track the Covid-19 pandemic. These sources are the number of Covid-19-related hospitalizations, the Covid-19 genecopies in wastewater, and the prevalence derived from a cohort study. This paper presents an extensive comparison of these parameters. It is investigated whether wastewater data and a cohort study can be valid surrogate parameters for the number of hospitalizations and thus serve as predictors for coming Covid-19 waves. We observe that this is possible in general for the cohort study prevalence, while the wastewater data suffer from a too large variability to make quantitative predictions by a purely data-driven approach. However, the wastewater data as well as the cohort study prevalence are able to detect hospitalizations waves in a qualitative manner. Furthermore, a detailed comparison of different normalization techniques of wastewater data is provided.

Concepts Keywords
Cdc_ueberblick Cohort
German Covid
Inexpensive Doi
Mathematics Genecopies


Type Source Name
disease MESH Covid-19
disease VO Viruses
disease VO USA
disease VO population
disease MESH infection
disease VO organization
disease VO protocol
drug DRUGBANK Water
disease VO volume
drug DRUGBANK Oxygen
drug DRUGBANK Activated charcoal
drug DRUGBANK Medical air
disease IDO facility
disease MESH uncertainty
disease VO time
disease IDO process
drug DRUGBANK Gold
disease MESH respiratory diseases
disease MESH influenza
disease VO gene
drug DRUGBANK Cysteamine
disease MESH Hepatitis
drug DRUGBANK Ademetionine
disease MESH Viral Diseases
disease VO NadA
disease MESH Water Quality

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