Uncovering dynamics between SARS-CoV-2 wastewater concentrations and community infections via Bayesian spatial functional concurrent regression

TL;DR

This paper introduces a Bayesian spatial functional concurrent regression model to analyze the dynamic relationship and time lag between SARS-CoV-2 wastewater concentrations and community infection rates, accounting for spatial, temporal, and noise complexities.

Contribution

It presents a novel Bayesian modeling approach that captures spatial and temporal dependencies and estimates the delay between wastewater signals and infection outbreaks.

Findings

Estimated a 5-11 day lag between wastewater spikes and infection reports.

Identified fluctuating relationships between wastewater levels and positivity rates.

Provided interpretable insights into the dynamics of COVID-19 spread.

Abstract

Monitoring wastewater concentrations of SARS-CoV-2 yields a low-cost, noninvasive method for tracking disease prevalence and provides early warning signs of upcoming outbreaks in the serviced communities. There is tremendous clinical and public health interest in understanding the exact dynamics between wastewater viral loads and infection rates in the population. As both data sources may contain substantial noise and missingness, in addition to spatial and temporal dependencies, properly modeling this relationship must address these numerous complexities simultaneously while providing interpretable and clear insights. We propose a novel Bayesian functional concurrent regression model that accounts for both spatial and temporal correlations while estimating the dynamic effects between wastewater concentrations and positivity rates over time. We explicitly model the time lag between the two series and provide full posterior inference on the possible delay between spikes in wastewater concentrations and subsequent outbreaks. We estimate a time lag likely between 5 to 11 days between spikes in wastewater levels and reported clinical positivity rates. Additionally, we find a dynamic relationship between wastewater concentration levels and the strength of its association with positivity rates that fluctuates between outbreaks and non-outbreaks.