Related Experiment Video
Updated: Jun 27, 2025

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
Published on: April 9, 2021
Statistical analysis of three data sources for Covid-19 monitoring in Rhineland-Palatinate, Germany
Maximilian Pilz1, Karl-Heinz Küfer2, Jan Mohring2
1Fraunhofer Institute for Industrial Mathematics, Kaiserslautern, Germany. maximilian.pilz@itwm.fraunhofer.de.
Abstract:
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 and 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.
Related Concept Videos
Steps in Outbreak Investigation
Statistical Methods for Analyzing Epidemiological Data
Statistical Software for Data Analysis and Clinical Trials
Comparing the Survival Analysis of Two or More Groups

