3 research outputs found

    Integrating Wastewater-Based Epidemiology and Mobility Data to Predict SARS-CoV-2 Cases

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    Wastewater-based epidemiology has garnered considerable research interest, concerning the COVID-19 pandemic. Restrictive public health interventions and mobility limitations are measures to avert a rising case prevalence. The current study integrates WBE monitoring strategies, Google mobility data, and restriction information to assess the epidemiological development of COVID-19. Various SARIMAX models were employed to predict SARS-CoV-2 cases in Liechtenstein and two Austrian regions. This study analyzes four primary strategies for examining the progression of the pandemic waves, described as follows: 1—a univariate model based on active cases; 2—a multivariate model incorporating active cases and WBE data; 3—a multivariate model considering active cases and mobility data; and 4—a sensitivity analysis of WBE and mobility data incorporating restriction policies. Our key discovery reveals that, while WBE for SARS-CoV-2 holds immense potential for monitoring COVID-19 on a societal level, incorporating the analysis of mobility data and restriction policies enhances the precision of the trained models in predicting the state of public health during the pandemic

    Expanding the Pathogen Panel in Wastewater Epidemiology to Influenza and Norovirus

    No full text
    Since the start of the 2019 pandemic, wastewater-based epidemiology (WBE) has proven to be a valuable tool for monitoring the prevalence of SARS-CoV-2. With methods and infrastructure being settled, it is time to expand the potential of this tool to a wider range of pathogens. We used over 500 archived RNA extracts from a WBE program for SARS-CoV-2 surveillance to monitor wastewater from 11 treatment plants for the presence of influenza and norovirus twice a week during the winter season of 2021/2022. Extracts were analyzed via digital PCR for influenza A, influenza B, norovirus GI, and norovirus GII. Resulting viral loads were normalized on the basis of NH4-N. Our results show a good applicability of ammonia-normalization to compare different wastewater treatment plants. Extracts originally prepared for SARS-CoV-2 surveillance contained sufficient genomic material to monitor influenza A, norovirus GI, and GII. Viral loads of influenza A and norovirus GII in wastewater correlated with numbers from infected inpatients. Further, SARS-CoV-2 related non-pharmaceutical interventions affected subsequent changes in viral loads of both pathogens. In conclusion, the expansion of existing WBE surveillance programs to include additional pathogens besides SARS-CoV-2 offers a valuable and cost-efficient possibility to gain public health information

    Expanding the Pathogen Panel in Wastewater Epidemiology to Influenza and Norovirus

    No full text
    Since the start of the 2019 pandemic, wastewater-based epidemiology (WBE) has proven to be a valuable tool for monitoring the prevalence of SARS-CoV-2. With methods and infrastructure being settled, it is time to expand the potential of this tool to a wider range of pathogens. We used over 500 archived RNA extracts from a WBE program for SARS-CoV-2 surveillance to monitor wastewater from 11 treatment plants for the presence of influenza and norovirus twice a week during the winter season of 2021/2022. Extracts were analyzed via digital PCR for influenza A, influenza B, norovirus GI, and norovirus GII. Resulting viral loads were normalized on the basis of NH4-N. Our results show a good applicability of ammonia-normalization to compare different wastewater treatment plants. Extracts originally prepared for SARS-CoV-2 surveillance contained sufficient genomic material to monitor influenza A, norovirus GI, and GII. Viral loads of influenza A and norovirus GII in wastewater correlated with numbers from infected inpatients. Further, SARS-CoV-2 related non-pharmaceutical interventions affected subsequent changes in viral loads of both pathogens. In conclusion, the expansion of existing WBE surveillance programs to include additional pathogens besides SARS-CoV-2 offers a valuable and cost-efficient possibility to gain public health information
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