Synopsis of information about the feasibility of detecting SARS-CoV-2 and measuring its concentration in urban sewage
Lockdown has been proven effective in reducing the transmission rate (reproduction number) of SARS-CoV-2, the COVID-19-generating coronavirus. However, lockdown has important negative impact to economy, and plans to relax the social restrictions are starting to be made. Relaxing restrictions must be performed carefully in order to prevent rapid increases in the transmission rates, which may lead to rapid increases of the number of infections, which may become difficult to contain. It is difficult to estimate the impact of relaxing certain restrictions, because any estimates are very uncertain (see, e.g., Flaxman et al, p. 12, fig. 4). Small uncertainties in the rate determining the exponential spread of the virus may lead to large uncertainties in the estimates of the number of infected people after a few weeks. If large-scale accurate testing is not available, the actual effect of relaxing restrictions can be measured only late, when the fraction of infected people that has significant symptoms is reaching hospitals. By this time, the infection may have silently spread in the population and reached a possibly significant percentage of local population, which may be too late to be properly mitigated.
Several preliminary studies indicate the possibility of detecting and measuring viral RNA in sewage, since viral RNA is shed in the stool of infected people (but not in urine). If measuring the concentration of viral RNA in sewage would be possible with relevant precision, this would be a tremendously useful tool to be used as an early warning of rampaging infection as a result of relaxing restrictions, and would allow an efficient management of relaxing restrictions. While pooling testing of typical samples (swabs) is currently explored as a way to make testing more efficient, given the limited number of possible tests, measuring the concentration in sewage is equivalent to pooling at the level of cities or parts of cities.
Since some scientists with a background in several areas related to biology are contesting whether detecting and measuring the concentration of virus in sewage is possible, the aim of this document is to collect preliminary information about the feasibility of this, in order to motivate specialists and decision makers to invest more resources in exploring this.
Wurtzer et al. have detected and measured SARS-CoV-2 in Parisian wastewaters and found that their measures correlate with COVID-19 confirmed cases. The measures anticipate with about 14 days the recorded confirmed cases. They report a quantification limit of 103 equivalent viral genomes per liter and measured concentrations of up to 107 "eq/L", probably equivalent viral genomes per liter. See coverage in Science.
Wu et al. have detected and measured SARS-CoV-2 in Boston wastewaters and found concentrations of up to 105 copies per liter (see, e.g., fig. 3). Biobot, a startup apparently associated with some authors of this study, have launched a pro bono program to map COVID-19 across the US by testing city sewage. See CNN coverage.
Ahmed et al. have detected and measured SARS-CoV-2 in Bristbane wastewaters and found concentrations of 101-102 copies per liter (see p. 8-9: 12 and 1.9 copies/100 mL of untreated wastewater).
Other reports of detection in sewage, without reported concentration, are by Medema et al. and by Lodder & de Roda Husman. See coverage in Nature.
Measures of viral load in stool are: 105-1011, with a peak at 108 copies/L (Zheng et al., Fig. 2,3); 106 copies/L (Chan et al., Table 3).
Wölfel et al also measured this, however the available version of the paper does not include Fig. 2 where data is reported. L. Moulin reports that the paper indicates between 105-107 vRNA/swab, i.e. about 108-1010 copies/L.
Biobot have launched a pro bono program to map COVID-19 across the US by testing city sewage.
Sewers4COVID team was one of the winners of the EUvsVirus hackathon.
This document was initiated by Răzvan Valentin Florian, who thanks Mehdi Khoury (from the Sewers4COVID team), Laurent Moulin (co-author of the Wurtzer et al study), and Alex Burciu for providing pointers to relevant information mentioned here.
This is released under a Creative Commons Attribution International license.