Effectiveness of non-pharmaceutical interventions in nine fields of activity to decrease SARS-CoV-2 transmission (Spain, September 2020-May 2021).

Background: We estimated the association between the level of restriction in nine different fields of activity and SARS-CoV-2 transmissibility in Spain, from 15 September 2020 to 9 May 2021. Methods: A stringency index (0-1) was created for each Spanish province (n = 50) daily. A hierarchical multiplicative model was fitted. The median of coefficients across provinces (95% bootstrap confidence intervals) quantified the effect of increasing one standard deviation in the stringency index over the logarithmic return of the weekly percentage variation of the 7-days SARS-CoV-2 cumulative incidence, lagged 12 days. Results: Overall, increasing restrictions reduced SARS-CoV-2 transmission by 22% (RR = 0.78; one-sided 95%CI: 0, 0.82) in 1 week, with highest effects for culture and leisure 14% (0.86; 0, 0.98), social distancing 13% (0.87; 0, 0.95), indoor restaurants 10% (0.90; 0, 0.95) and indoor sports 6% (0.94; 0, 0.98). In a reduced model with seven fields, culture and leisure no longer had a significant effect while ceremonies decreased transmission by 5% (0.95; 0, 0.96). Models R 2 was around 70%. Conclusion: Increased restrictions decreased COVID-19 transmission. Limitations include remaining collinearity between fields, and somewhat artificial quantification of qualitative restrictions, so the exact attribution of the effect to specific areas must be done with caution.

Wastewater early warning system for SARS-CoV-2 outbreaks and variants in a Coruña, Spain.

Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 103 and 106 SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8-36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.

Modeling the number of people infected with SARS-COV-2 from wastewater viral load in Northwest Spain.

The quantification of the SARS-CoV-2 RNA load in wastewater has emerged as a useful tool to monitor COVID-19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW Spain), where wastewater from a treatment plant was analyzed to track the epidemic dynamics in a population of 369,098 inhabitants. Viral load detected in the wastewater and the epidemiological data from A Coruña health system served as main sources for statistical models developing. Regression models described here allowed us to estimate the number of infected people (R2 = 0.9), including symptomatic and asymptomatic individuals. These models have helped to understand the real magnitude of the epidemic in a population at any given time and have been used as an effective early warning tool for predicting outbreaks in A Coruña municipality. The methodology of the present work could be used to develop a similar wastewater-based epidemiological model to track the evolution of the COVID-19 epidemic anywhere in the world where centralized water-based sanitation systems exist.