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 Austrias 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. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/21267633v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1044af0org.highwire.dtl.DTLVardef@d3fe2borg.highwire.dtl.DTLVardef@1d3bfa1org.highwire.dtl.DTLVardef@c9fc95_HPS_FORMAT_FIGEXP M_FIG C_FIG
ABSTRACT
Several systemic factors indicate, that worldwide herd immunity against COVID-19 will probably not be achieved in 2021. Vaccination programs are limited by availability of doses, the number of people already infected is still too low to have a disease preventing impact and new emerging variants of the virus seem to partially neglect developed antibodies from previous infections. Nevertheless, after one year of COVID-19 observing high numbers of reported cases in most European countries, we might expect that the immunization level should have an impact on the spread of SARS-CoV-2. We used an agent-based simulation model to reproduce the COVID-19 pandemic in Austria to estimate the immunization level of the population as of February 2021. We ran several simulations of an uncontrolled epidemic wave with varying initial immunization scenarios to assess the effect on the effective reproduction number. We also used a classic differential equation SIR-model to cross-validate the simulation model. As of February 2021, 14.7% of the Austrian population has been affected by a SARS-CoV-2 infection which causes a 9% reduction of the effective reproduction number and a 24.7% reduction of the prevalence peak compared to a fully susceptible population. This estimation is now recomputed on a regular basis to publish model based analysis of immunization level in Austria also including the fast growing effects of vaccination programs. This provides substantial information for decision makers to evaluate the necessity of NPI-measures based on the estimated impact of natural and vaccinated immunization.
ABSTRACT
We generate synthetic data documenting COVID-19 cases in Austria by the means of an agent-based simulation model. The model simulates the transmission of the SARS-CoV-2 virus in a statistical replica of the population and reproduces typical patient pathways on an individual basis while simultaneously integrating historical data on the implementation and expiration of population-wide countermeasures. The resulting data semantically and statistically aligns with an official epidemiological case reporting data set and provides an easily accessible, consistent and augmented alternative. Our synthetic data set provides additional insight into the spread of the epidemic by synthesizing information that cannot be recorded in reality.
