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Metrics to relate COVID-19 wastewater data to clinical testing dynamics.

Authors :
Xiao A
Wu F
Bushman M
Zhang J
Imakaev M
Chai PR
Duvallet C
Endo N
Erickson TB
Armas F
Arnold B
Chen H
Chandra F
Ghaeli N
Gu X
Hanage WP
Lee WL
Matus M
McElroy KA
Moniz K
Rhode SF
Thompson J
Alm EJ
Source :
MedRxiv : the preprint server for health sciences [medRxiv] 2021 Jun 16. Date of Electronic Publication: 2021 Jun 16.
Publication Year :
2021

Abstract

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. We collected 24-hour composite wastewater samples from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and measured SARS-CoV-2 RNA concentrations using RT-qPCR. We show that the relationship between wastewater viral titers and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater viral titers and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. We find that the WC ratio increases after key events, providing insight into the balance between disease spread and public health response. We also find that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity. These three metrics could complement a framework for integrating wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Details

Language :
English
Database :
MEDLINE
Journal :
MedRxiv : the preprint server for health sciences
Publication Type :
Academic Journal
Accession number :
34159339
Full Text :
https://doi.org/10.1101/2021.06.10.21258580