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.