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

• Published in: Water research (Oxford) 2023-08, Vol.241, p.120098-120098, Article 120098
• Main Authors: Polcz, Péter, Tornai, Kálmán, Juhász, János, Cserey, György, Surján, György, Pándics, Tamás, Róka, Eszter, Vargha, Márta, Reguly, István Z., Csikász-Nagy, Attila, Pongor, Sándor, Szederkényi, Gábor
• Format: Article
• Language: English
• Subjects: Dynamical system; Epidemic model; Optimization; Parameter estimation; Wastewater-based epidemiology
• ISSN: 0043-1354; 1879-2448
• DOI: 10.1016/j.watres.2023.120098

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. 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. 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. The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well. [Display omitted] •Viral load in wastewater improves epidemic reconstruction and short-term predictions.•A SEIR-type model with immunization, waning, and viral load was proposed.•Wastewater measurements were combined with clinical data to estimate model constants.•Immunity loss and effective immunization was estimated as time-varying coefficients.