Integrating Region-Specific SARS-CoV-2 Data for Statistical Wastewater Monitoring

TL;DR

This paper presents a statistical framework for utilizing wastewater SARS-CoV-2 data in health surveillance, aiding epidemic management by monitoring virus concentrations and assessing sampling strategies.

Contribution

It introduces a novel statistical process control approach tailored for wastewater data to support decision-making during epidemics.

Findings

Effective monitoring of SARS-CoV-2 levels in wastewater.

Assessment of Austria's sampling strategy.

Framework for epidemic alerting system.

Abstract

Wastewater data can be very useful for epidemic control during a disease outbreak and proper synthesis of different sources of information can be integrated towards an alerting system, that can be used for decision support. Wastewater data are considered to be of high quality, since they do not depend on testing and can take into account asymptomatic cases. However, little effort has been given into utilizing such information in statistical process control procedures, usually aimed at industrial problems. In this article, we demonstrate how wastewater data can be utilized in health surveillance and propose a statistical framework that can act as a decision support tool. Specifically, we analyze SARS-CoV-2 wastewater data from Austria, constructing summary variables to implicitly describe the Covid-19 prevalence and, based on them, we assess the effectiveness of the current sampling strategy of Austria. We propose a framework of a statistical process monitoring system to aid epidemic management procedures in case SARS-CoV-2 concentration gets dangerously high.