Federica Cariti

Bio: Federica Cariti is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Population. The author has an hindex of 3, co-authored 3 publications receiving 87 citations.

Detection of SARS-CoV-2 variants in Switzerland by genomic analysis of wastewater samples

Abstract: The SARS-CoV-2 lineages B.1.1.7 and 501.V2, which were first detected in the United Kingdom and South Africa, respectively, are spreading rapidly in the human population. Thus, there is an increased need for genomic and epidemiological surveillance in order to detect the strains and estimate their abundances. Here, we report a genomic analysis of SARS-CoV-2 in 48 raw wastewater samples collected from three wastewater treatment plants in Switzerland between July 9 and December 21, 2020. We find evidence for the presence of several mutations that define the B.1.1.7 and 501.V2 lineages in some of the samples, including co-occurrences of up to three B.1.1.7 signature mutations on the same amplicon in four samples from Lausanne and one sample from a Swiss ski resort dated December 9 - 21. These findings suggest that the B.1.1.7 strain could be detected by mid December, two weeks before its first verification in a patient sample from Switzerland. We conclude that sequencing SARS-CoV-2 in community wastewater samples may help detect and monitor the circulation of diverse lineages.

Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high

Abstract: Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this limitation. Here we investigated how the dynamics of new COVID-19 infections estimated based on wastewater monitoring or confirmed cases compare to true COVID-19 incidence dynamics. We focused on the first pandemic wave in Switzerland (February to April, 2020), when test positivity ranged up to 26%. SARS-CoV-2 RNA loads were determined 2-4 times per week in three Swiss wastewater treatment plants (Lugano, Lausanne and Zurich). Wastewater and case data were combined with a shedding load distribution and an infection-to-case confirmation delay distribution, respectively, to estimate incidence dynamics. Finally, the estimates were compared to reference incidence dynamics determined by a validated compartmental model. Incidence dynamics estimated based on wastewater data were found to better track the timing and shape of the reference infection peak compared to estimates based on confirmed cases. In contrast, case confirmations provided a better estimate of the subsequent decline in infections. Under a regime of high-test positivity rates, WBE thus provides critical information that is complementary to clinical data to monitor the pandemic trajectory.

Evaluation of Sampling, Analysis, and Normalization Methods for SARS-CoV-2 Concentrations in Wastewater to Assess COVID-19 Burdens in Wisconsin Communities

Abstract: Wastewater surveillance for SARS-CoV-2 provides an approach for assessing the infection burden across a sewer service area. For these data to be useful for public health, measurement variability and the relationship to case data need to be established. We determined SARS-CoV-2 RNA concentrations in the influent of 12 wastewater treatment plants from August 2020 to January 2021. Technical replicates for N1 gene concentrations showed a relative standard deviation of 24%, suggesting it is possible to track relatively small (similar to 30%) changes in SARS-CoV-2 concentrations over time. COVID-19 cases were correlated significantly (rho >= 0.70) to wastewater SARS-CoV-2 RNA concentrations across large and small service areas, with weaker relationships (rho >= 0.59) in two communities. SARS-CoV-2 concentrations normalized to per capita slightly improved correlations to COVID-19 incidence, but normalizing to a spiked recovery control (BCoV) or a fecal marker (PMMoV or HF183) reduced correlations for a number of plants. Daily sampling demonstrated that a minimum of two samples collected per week were needed to maintain accuracy in trend analysis. The differences in the strength of SARS-CoV-2 relationships to COVID-19 incidence and the effect of normalization on these data among communities demonstrate that rigorous validation should be performed at individual sites where wastewater surveillance programs are implemented.