Placing sensors in sewer networks: A system to pinpoint new cases of coronavirus

Abstract

We consider a proposed system that would place sensors in a number of wastewater manholes in a community in order to detect genetic remnants of SARS-Cov-2 found in the excreted stool of infected persons. These sensors would continually monitor the manhole’s wastewater, and whenever virus remnants are detected, transmit an alert signal. In a recent paper, we described two new algorithms, each sequentially opening and testing successive manholes for genetic remnants, each algorithm homing in on a neighborhood where the infected person or persons are located. This paper extends that work in six important ways: (1) we introduce the concept of in-manhole sensors, as these sensors will reduce the number of manholes requiring on-site testing; (2) we present a realistic tree network depicting the topology of the sewer pipeline network; (3) for simulations, we present a method to create random tree networks exhibiting key attributes of a given community; (4) using the simulations, we empirically demonstrate that the mean and median number of manholes to be opened in a search follows a well-known logarithmic function; (5) we develop procedures for determining the number of sensors to deploy; (6) we formulate the sensor location problem as an integer nonlinear optimization and develop heuristics to solve it. Our sensor-manhole system, to be implemented, would require at least three additional steps in R&D: (a) an accurate, inexpensive and fast SARS-Cov-2 genetic-remnants test that can be done at the manhole; (b) design, test and manufacture of the sensors; (c) in-the-field testing and fine tuning of an implemented system.

SARS-CoV-2 RNA abundance in wastewater as a function of distinct urban sewershed size

“…Nourinejad et al 26 have advocated for the use of in-sewer SARS-CoV-2 network sensors, and our results suggest that such sensors would be best placed across different population levels rather than in street line locations of similar populations. Additionally, Larson et al 27 suggested that a sampling of 5 to 10 community locations might be required to iteratively find a COVID-19 "patient zero".…”

Wastewater analysis can be a powerful public health tool—if it’s done sensibly

“…In a clinical setting, individual contributions to a positive pooled sample can be retested to identify the source(s) of the positive; this is not so for wastewater samples. Although researchers have proposed in-sewer sensor networks that would isolate positive building outflows (12), such networks would require much cheaper and faster instrumentation and methods for detecting SARS-CoV-2 in wastewater. Moreover, the prospect of tracing genetic signals in wastewater back to individual sources amplifies privacy and ethical concerns surrounding WBE (13).…”

Effect of mandating vaccination on COVID-19 cases in colleges and universities

“…Overall, this report provides the first empirical evidence for several past simulation studies ( Paltiel & Schwartz, 2021 ) showing that achieving a high vaccination rate is an important policy tool for the administrations of institutions of higher education. While institutions of higher education have benefited from several other policies ( Larson et al, 2020 ; Nourinejad et al, 2021 ) including higher test frequencies ( Paltiel, Zheng, et al, 2020 ; Schultes et al, 2021 ), and it is difficult to separate the effect of the mandates from other policies in correlational studies, our difference-in-differences method controls for the historical trends for each university and isolates Fall 2021 policy changes from other policies that were in place before Fall 2021. Moreover, it is likely that institutions with such high vaccination levels had a lower risk perception, leading to more interactions; thus, our estimation points to a lower bound effect of mandating vaccination.…”

“…Overall, this report provides the first empirical evidence for several past simulation studies (Paltiel & Schwartz, 2021) showing that achieving a high vaccination rate is an important policy tool for the administrations of institutions of higher education. While institutions of higher education have benefited from several other policies (Larson et al, 2020;Nourinejad et al, 2021) including higher test frequencies Schultes et al, 2021), and it is difficult to separate the effect of the mandates from other policies in correlational studies, our difference-in-differences method controls for the historical trends for each university and isolates…”