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. 2024 Jun 6;21(6):741.
doi: 10.3390/ijerph21060741.

Wastewater-Based Epidemiology for SARS-CoV-2 in Northern Italy: A Spatiotemporal Model

Matilde Fondriest  1 , Lorenzo Vaccari  1 , Federico Aldrovandi  2 , Laura De Lellis  3 , Filippo Ferretti  4 , Carmine Fiorentino  4 , Erica Mari  1   4 , Maria Grazia Mascolo  1 , Laura Minelli  5 , Vincenza Perlangeli  4 , Giuseppe Bortone  1 , Paolo Pandolfi  4 , Annamaria Colacci  1 , Andrea Ranzi  1
Affiliations

Wastewater-Based Epidemiology for SARS-CoV-2 in Northern Italy: A Spatiotemporal Model

Matilde Fondriest et al. Int J Environ Res Public Health. .

Abstract

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring the SARS-CoV-2 prevalence in a city in northern Italy from October 2021 to May 2023. Based on a previously used deterministic model, this study proposed a variation to account for the population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated using healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred during the period considered, demonstrating the ability of the model to predict the relevant fluctuations in the number of cases. The population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied to compare the virus load values across cities with different population demographics and sewer network structures, improving the comparability of the WBE data for effective surveillance and intervention strategies.

Keywords: COVID-19; SARS-CoV-2; biodegradation; early-warning system; public health; sewer network; spatiotemporal model; wastewater; wastewater-based epidemiology.

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Conflict of interest statement

Laura De Lellis was employed by the company Hera Tech Srl. Laura Minelli was employed by the company Water Directorate, Hera SpA. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Map of the study area (orange) divided into census sections and statistical areas (delineated in gray). Representation of the wastewater treatment plant (WWTP) (red triangle), sewer network (blue), catchment area (light blue), names, and boundaries of the municipalities (black).
Figure 2
Figure 2
(A) Map of biodegradation in the study area, the WWTP (red triangle). (B) Frequency distribution of biodegradation in the study area. Biodegradation is expressed as a 1 − e−kϴi percentage, calculated with k = 0.101 (T = 16 °C).
Figure 3
Figure 3
Predicted (blue) and reported (orange) infection rate IR(t) across the entire study area and the uncertainty interval (RSD) (light blue) associated with the predicted IR(t). Values of total predicted and reported COVID-19 cases over the single wave (delimitated by dashed vertical lines) in the entire study area.
Figure 4
Figure 4
Tests: Daily reported tests across the entire study area per 100,000 inhabitants averaged with a simple moving average (SMA) over 7 days. Positivity rate: Weekly average of positive cases among tests conducted. To calculate the positivity rate, the date on which the test was conducted was taken as the reference date for both tests and cases. Reported cases: reported daily COVID-19 cases over 100,000 inhabitants averaged with a simple moving average (SMA) over 7 days (reported IR(t)). Hospitalizations: weekly sum of COVID-19 hospitalizations. Both reported cases and hospitalizations are represented based on the symptom onset date if symptomatic or the date of the test in asymptomatic cases.
Figure 5
Figure 5
Maps of predicted total cases (A) and reported total cases (B) during the first wave in the different grouped areas.
Figure 6
Figure 6
Box plot of the daily average reported and predicted infection rates (IRj), along with the lower and upper uncertainty bounds associated with the daily average predicted IRj. The IRj is expressed as daily average cases per 1000 inhabitants over the wave and in the grouped area (for each box plot, one data point for each grouped area and for each wave is represented).
Figure 7
Figure 7
Percentage of SARS-CoV-2 variant lineages over time obtained from regional surveys.
See this image and copyright information in PMC

References

    1. Corchis-Scott R., Geng Q., Seth R., Ray R., Beg M.R., Biswas N., Charron L., Drouillard K.D., D’Souza R., Heath D.D., et al. Averting an Outbreak of SARS-CoV-2 in a University Residence Hall through Wastewater Surveillance. Microbiol. Spectr. 2021;9:e00792-21. doi: 10.1128/spectrum.00792-21. - DOI - PMC - PubMed
    1. Bertels X., Demeyer P., Van Den Bogaert S., Boogaerts T., Van Nuijs A.L.N., Delputte P., Lahousse L. Factors influencing SARS-CoV-2 RNA concentrations in wastewater up to the sampling stage: A systematic review. Sci. Total Environ. 2022;820:153290. doi: 10.1016/j.scitotenv.2022.153290. - DOI - PMC - PubMed
    1. Li X., Zhang S., Shi J., Luby S.P., Jiang G. Uncertainties in estimating SARS-CoV-2 prevalence by wastewater-based epidemiology. Chem. Eng. J. 2021;415:129039. doi: 10.1016/j.cej.2021.129039. - DOI - PMC - PubMed
    1. Weidhaas J., Aanderud Z.T., Roper D.K., VanDerslice J., Gaddis E., Ostermiller J., Hoffman K., Jamal R., Heck P.E., Zhang Y., et al. Correlation of SARS-CoV-2 RNA in wastewater with COVID-19 disease burden in sewersheds. Sci. Total Environ. 2021;775:145790. doi: 10.1016/j.scitotenv.2021.145790. - DOI - PMC - PubMed
    1. Robotto A., Lembo D., Quaglino P., Brizio E., Polato D., Civra A., Cusato J., Di Perri G. Wastewater-based SARS-CoV-2 environmental monitoring for Piedmont, Italy. Environ. Res. 2022;203:111901. doi: 10.1016/j.envres.2021.111901. - DOI - PMC - PubMed