https://digital.csic.es/bitstream/10261/239339/1/preprints202104.0481.v1.pdf

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020.

Understanding and managing uncertainty and variability for wastewater monitoring beyond the pandemic: Lessons learned from the United Kingdom national COVID-19 surveillance programmes.

Background: The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change. Objectives: We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate Re in near real time, independent of clinical data and without the associated biases. Methods: We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence. Results: The method to estimate Re from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. Discussion: To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050 

Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2

Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19.

A year since the declaration of the global coronavirus disease 2019 (COVID-19) pandemic there have been over 110 million cases and 2.5 million deaths. Using methods to track community spread of other viruses such as poliovirus, environmental virologists and those in the wastewater based epidemiology (WBE) field quickly adapted their existing methods to detect SARS-CoV-2 RNA in wastewater. Unlike COVID-19 case and mortality data, there was not a global dashboard to track wastewater monitoring of SARS-CoV-2 RNA worldwide. This study describes the development of the "COVIDPoops19" dashboard to disseminate information regarding sites, universities, research institutions and private laboratories in countries that are involved in WBE for SARS-CoV-2. Methods to assemble the dashboard combined standard literature review, direct submissions, and daily, social media keyword searches. Over 200 universities, 1,000 sites, and 50 countries with 59 dashboards monitor wastewater for SARS-CoV-2 RNA. However, monitoring is inequitably distributed in high-income countries and data are not widely shared publicly or accessible to researchers to inform public health actions, meta-analysis, better coordinate, and determine equitable distribution of monitoring sites. For WBE to be used to its full potential during COVID-19 and beyond, show us the data.

/pdf/show-us-the-data-global-covid-19-wastewater-monitoring-2ikk8jg5xp.pdf

Vajra Allan

Papers

Show us the Data: Global COVID-19 Wastewater Monitoring Efforts, Equity, and Gaps