Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants.

(MOTIVATION): Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases. Consequently, WBE was gradually becoming a key tool for epidemic surveillance and often the most reliable data source, as the intensity of clinical testing for COVID-19 drastically decreased by the third year of the pandemic. Recent results suggests that the model-based fusion of wastewater measurements with clinical data and other indicators is essential in future epidemic surveillance. (METHOD): In this work, we developed a wastewater-based compartmental epidemic model with a two-phase vaccination dynamics and immune evasion. We proposed a multi-step optimization-based data assimilation method for epidemic state reconstruction, parameter estimation, and prediction. The computations make use of the measured viral load in wastewater, the available clinical data (hospital occupancy, delivered vaccine doses, and deaths), the stringency index of the official social distancing rules, and other measures. The current state assessment and the estimation of the current transmission rate and immunity loss allow a plausible prediction of the future progression of the pandemic. (RESULTS): Qualitative and quantitative evaluations revealed that the contribution of wastewater data in our computational epidemiological framework makes predictions more reliable. Predictions suggest that at least half of the Hungarian population has lost immunity during the epidemic outbreak caused by the BA.1 and BA.2 subvariants of Omicron in the first half of 2022. We obtained a similar result for the outbreaks caused by the subvariant BA.5 in the second half of 2022. (APPLICABILITY): The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well.

SARS-CoV-2 variant detection from wastewater: rapid spread of B.1.1.7 lineage in Hungary.

Wastewater-based epidemiology (WBE) is a recognised tool for tracking community transmission of COVID-19. From the second half of 2020, the emergence of new, highly infective, more pathogenic or vaccine-escape SARS-CoV-2 variants is the major public health concern. Variant analysis in sewage might assist the early detection of new mutations. Weekly raw sewage samples from 22 wastewater treatment plants (WWTPs) in Hungary (representing 40% of the population) were analysed between December 2020 and March 2021 for signature mutations N501Y and del H69/V70 of B.1.1.7 lineage by melting point genotyping and RT-digital droplet PCR (RT-ddPCR). The latter method proved to be more efficient in parallel detection of different variants and also provides quantitative information. Wastewater surveillance indicated that the B.1.1.7 variant first emerged in Budapest in early January 2021 and rapidly became dominant in the entire country. Results are in close agreement with the available clinical data (Pearson's correlation coefficient, R = 0.9153). RT-ddPCR was confirmed to be a reliable tool for tracking emerging variant ratios in wastewaters. It is a rapid and cost-effective method compared to whole-genome sequencing, but only applicable for the detection of known mutations. Efficient variant surveillance might require the combination of multiple methods.

Ahead of the second wave: Early warning for COVID-19 by wastewater surveillance in Hungary.

Wastewater based epidemiology is a potential early warning tool for the detection of COVID-19 outbreak. Sewage surveillance for SARS-CoV-2 RNA was introduced in Hungary after the successful containment of the first wave of the pandemic to forecast the resurge of infections. Three wastewater treatment plants servicing the entire population (1.8 million) of the capital, Budapest were sampled weekly. 24 h composite (n = 44) and grab samples (n = 21) were concentrated by an in-house flat sheet membrane ultrafiltration method. The efficiency and reproducibility of the method was comparable to those previously published. SARS-CoV-2 RNA was quantified using RT-qPCR of the N gene. The first positive signal in sewage was detected 2 weeks before the rise in case numbers. Viral concentration and volume-adjusted viral load correlated to the weekly new cases from the same week and the rolling 7-day average of active cases in the subsequent week. The correlation was more pronounced in the ascending phase of the outbreak, data was divergent once case numbers plateaued. Wastewater surveillance was found to be effective in predicting the second wave of the outbreak in Hungary. Data indicated that even relatively low frequency (weekly) sampling is useful and at the same time, cost effective tool in outbreak detection.