A Multi-City COVID-19 Categorical Forecasting Model Utilizing Wastewater-Based Epidemiology

Abstract

The COVID-19 pandemic highlighted shortcomings in forecasting models, such as unreliable inputs/outputs and poor performance at critical points. As COVID-19 remains a threat, it is imperative to improve current forecasting approaches by incorporating reliable data and alternative forecasting targets to better inform decision-makers. Wastewater-based epidemiology (WBE) has emerged as a viable method to track COVID-19 transmission, offering a more reliable metric than reported cases for forecasting critical outcomes like hospitalizations. Recognizing the natural alignment of wastewater systems with city structures, ideal for leveraging WBE data, this study introduces a multi-city, wastewater-based forecasting model to categorically predict COVID-19 hospitalizations.