ABSTRACT
SARS-CoV-2 surveillance is crucial to identify variants with altered epidemiological properties. Wastewater-based epidemiology (WBE) provides an unbiased and complementary approach to sequencing individual cases. Yet, national WBE surveillance programs have not been widely implemented and data analyses remain challenging. We deep-sequenced 2,093 wastewater samples representing 95 municipal catchments, covering >57% of Austria's population, from December 2020 to September 2021. Our Variant Quantification in Sewage pipeline designed for Robustness (VaQuERo) enabled us to deduce variant abundance from complex wastewater samples and delineate the spatiotemporal dynamics of the dominant Alpha and Delta variants as well as regional clusters of other variants of concern. These results were cross validated by epidemiological records of >130,000 individual cases. Finally, we provide a framework to predict emerging variants de novo and infer variant-specific reproduction numbers from wastewater. This study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without dense individual monitoring.
ABSTRACT
How to safely maintain open schools during a pandemic is still controversial. We aim to identify those measures that effectively control the spread of SARS-CoV-2 in Austrian schools. By control we mean that each source case infects less than one other person on average. We use Austrian data on 616 clusters involving 2,822 student-cases and 676 teacher-cases to calibrate an agent-based epidemiological model in terms of cluster size and transmission risk depending on age and clinical presentation. Considering a situation in which the B1.617.2 (delta) virus strain is dominant and parts of the population are vaccinated, we quantify the impact of non-pharmaceutical intervention measures (NPIs) such as room ventilation, reduction of class size, wearing of masks during lessons, vaccinations, and school entry testing by SARS-CoV2-antigen tests. In the tracing data we find that 40% of all clusters involved no more than two cases, and 3% of the clusters only had more than 20 cases. The younger the students, the more likely we found asymptomatic cases and teachers as the source case of the in-school transmissions. Based on this data, the model shows that different school types require different combinations of NPIs to achieve control of the infection spreading: If 80% of teachers and 50% of students are vaccinated, in primary schools, it is necessary to combine at least two of the above NPIs. In secondary schools, where contact networks of students and teachers become increasingly large and dense, a combination of at least three NPIs is needed. A sensitivity analysis indicated that poorly executed mitigation measures might increase the cluster size by a factor of more than 17 for primary schools and even higher increases are to be expected for the other school types. Our results suggest that school-type-specific combinations of NPIs together with vaccinations are necessary to allow for a controlled opening of schools under sustained community transmission of the SARS-CoV-2 delta variant. However, large clusters might still occur on an infrequent, however, regular basis.
ABSTRACT
Background: A key question concerning coronavirus disease 2019 (COVID-19) is how effective and long lasting immunity against this disease is in individuals who were previously infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to evaluate the risk of SARS-CoV-2 re-infections in the general population in Austria. Methods This is a retrospective observational study using national SARS-CoV-2 infection data from the Austrian epidemiological reporting system. As the primary outcome, we aim to compare the odds of SARS-CoV-2 re-infections of COVID-19 survivors of the first wave (February to April 30, 2020) versus the odds of first infections in the remainder general population by tracking polymerase chain reaction (PCR)-confirmed infections of both groups during the second wave from September 1 to November 30, 2020. Re-infection counts are tentative, since it cannot be excluded that the positive PCR in the first and/or second wave might have been a false positive. Results We recorded 40 tentative re-infections in 14,840 COVID-19 survivors of the first wave (0.27%) and 253,581 infections in 8,885,640 individuals of the remaining general population (2.85%) translating into an odds ratio (95% confidence interval) of 0.09 (0.07 to 0.13). Conclusions We observed a relatively low re-infection rate of SARS-CoV-2 in Austria. Protection against SARS-CoV-2 after natural infection is comparable to the highest available estimates on vaccine efficacies. Further well-designed research on this issue is urgently needed for improving evidence-based decisions on public health measures and vaccination strategies.