Effect of SARS-CoV-2 shedding rate distribution of individuals during their disease days on the estimation of the number of infected people. Application of wastewater-based epidemiology to the city of Thessaloniki, Greece.

During the COVID-19 pandemic, wastewater-based epidemiology has proved to be an important tool for monitoring the spread of a disease in a population. Indeed, wastewater surveillance was successfully used as a complementary approach to support public health monitoring schemes and decision-making policies. An essential feature for the estimation of a disease transmission using wastewater data is the distribution of viral shedding rate of individuals in their personal human wastes as a function of the days of their infection. Several candidate shapes for this function have been proposed in literature for SARS-CoV-2. The purpose of the present work is to explore the proposed function shapes and examine their significance on analyzing wastewater SARS-CoV-2 shedding rate data. For this purpose, a simple model is employed applying to medical surveillance and wastewater data of the city of Thessaloniki during a period of Omicron variant domination in 2022. The distribution shapes are normalized with respect to the total virus shedding and then their basic features are investigated. Detailed analysis reveals that the main parameter determining the results of the model is the difference between the day of maximum shedding rate and the day of infection reporting. Since the latter is not part of the distribution shape, the major feature of the distribution affecting the estimation of the number of infected people is the day of maximum shedding rate with respect to the initial infection day. On the contrary, the duration of shedding (total number of disease days) as well as the exact shape of the distribution are by far less important. The incorporation of such wastewater surveillance models in conventional epidemiological models - based on recorded disease transmission data- may improve predictions for disease spread during outbreaks.

Relating SARS-CoV-2 shedding rate in wastewater to daily positive tests data: A consistent model based approach.

During the COVID-19 pandemic, wastewater-based epidemiology (WBE) has been engaged to complement medical surveillance and in some cases to also act as an early diagnosis indicator of viral spreading in the community. Most efforts worldwide by the scientific community and commercial companies focus on the formulation of protocols for SARS-CoV-2 analysis in wastewater and approaches addressing the quantitative relationship between WBE and medical surveillance are lacking. In the present study, a mathematical model is developed which uses as input the number of daily positive medical tests together with the highly non-linear shedding rate curve of individuals to estimate the evolution of global virus shedding rate in wastewater along calendar days. A comprehensive parametric study by the model using as input actual medical surveillance and WBE data for the city of Thessaloniki (~700,000 inhabitants, North Greece) during the outbreak of November 2020 reveals the conditions under which WBE can be used as an early warning tool for predicting pandemic outbreaks. It is shown that early warning capacity is different along the days of an outbreak and depends strongly on the number of days apart between the day of maximum shedding rate of infected individuals in their disease cycle and the day of their medical testing. The present data indicate for Thessaloniki an average early warning capacity of around 2 days. Moreover, the data imply that there exists a proportion between unreported cases (asymptomatic persons with mild symptoms that do not seek medical advice) and reported cases. The proportion increases with the number of reported cases. The early detection capacity of WBE improves substantially in the presence of an increasing number of unreported cases. For Thessaloniki at the peak of the pandemic in mid-November 2020, the number of unreported cases reached a maximum around 4 times the number of reported cases.

A physicochemical model for rationalizing SARS-CoV-2 concentration in sewage. Case study: The city of Thessaloniki in Greece.

Detection of SARS-CoV-2 in sewage has been employed by several researchers as an alternative early warning indicator of virus spreading in communities, covering both symptomatic and asymptomatic cases. A factor that can seriously mislead the quantitative measurement of viral copies in sewage is the adsorption of virus fragments onto the highly porous solids suspended in wastewater, making them inaccessible. This depends not only on the available amount of suspended solids, but also on the amount of other dissolved chemicals which may influence the capacity of adsorption. On this account, the present work develops a mathematical framework, at various degrees of spatial complexity, of a physicochemical model that rationalizes the quantitative measurements of total virus fragments in sewage as regards the adsorption of virus onto suspended solids and the effect of dissolved chemicals on it. The city of Thessaloniki in Greece is employed as a convenient case study to determine the values of model variables. The present data indicate the ratio of the specific absorption (UV254/DOC) over the dissolved oxygen (DO) as the parameter with the highest correlation with viral copies. This implies a strong effect on viral inaccessibility in sewage caused (i) by the presence of humic-like substances and (ii) by virus decay due to oxidation and metabolic activity of bacteria. The present results suggest days where many fold corrections in the measurement of viral copies should be applied. As a result, although the detected RNA load in June 2020 is similar to that in April 2020, virus shedding in the city is about 5 times lower in June than in April, in line with the very low SARS-CoV-2 incidence and hospital admissions for COVID-19 in Thessaloniki in June.