Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study.

Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite samples were collected from wastewater treatment plants of larger towns already covered 65% of the total population that was complemented up to 40 additional grab samples from smaller towns/villages and the specific sites of concern. The N3 gene abundance was quantified by RT-qPCR. The N3 gene copy number (concentration) in wastewater fluctuated in accordance with the SARS-CoV-2 spread within the total population, with N3 abundance starting to increase 1.25 weeks (9 days) (95% CI: [1.10, 1.41]) before a rise in COVID-19 positive cases. Statistical model between the load of virus in wastewater and number of infected people validated with the Alpha variant wave (B.1.1.17) could be used to predict the order of magnitude in incidence numbers in Delta wave (B.1.617.2) in fall 2021. Targeted testing of student dormitories, retirement and nursing homes and prisons resulted in successful early discovery of outbreaks. We put forward a SARS-CoV-2 Wastewater Index (SARS2-WI) indicator of normalized virus load as COVID-19 infection metric to complement the other metrics currently used in disease control and prevention: dynamics of effective reproduction number (Re), 7-day mean of new cases, and a sum of new cases within last 14 days. In conclusion, an efficient surveillance system that combines analysis of composite and grab samples was established in Estonia. There is considerable discussion how the viral load in wastewater correlates with the number of infected people. Here we show that this correlation can be found. Moreover, we confirm that an increased signal in wastewater is observed before the increase in the number of infections. The surveillance system helped to inform public health policy and place direct interventions during the COVID-19 pandemic in Estonia via early warning of epidemic spread in various regions of the country.

Clinically observed deletions in SARS-CoV-2 Nsp1 affect its stability and ability to inhibit translation.

Nonstructural protein 1 (Nsp1) of SARS-CoV-2 inhibits host cell translation through an interaction between its C-terminal domain and the 40S ribosome. The N-terminal domain (NTD) of Nsp1 is a target of recurring deletions, some of which are associated with altered COVID-19 disease progression. Here, we characterize the efficiency of translational inhibition by clinically observed Nsp1 deletion variants. We show that a frequent deletion of residues 79-89 severely reduces the ability of Nsp1 to inhibit translation while not abrogating Nsp1 binding to the 40S. Notably, while the SARS-CoV-2 5' untranslated region enhances translation of mRNA, it does not protect from Nsp1-mediated inhibition. Finally, thermal stability measurements and structure predictions reveal a correlation between stability of the NTD and the efficiency of translation inhibition.