"From Waste to Wisdom: Utilizing Wastewater Data and Virus Variant Modeling for Improving Epidemic Forecasting"
The ongoing COVID-19 pandemic has highlighted the importance of early detection and accurate forecasting of infectious disease outbreaks. Recent research has shown that incorporating wastewater data and virus variant modeling into mathematical models of epidemics can significantly improve our ability to achieve these goals. In this paper, we present a novel approach to epidemic modeling that utilizes both wastewater data and virus variant analysis. Specifically, we propose a mathematical model that combines a compartmental model of disease transmission with a model of two viral strains, allowing us to track the spread of different strains over time. We then apply this model to real-world data from a community in the United States and demonstrate its ability to accurately forecast the trajectory of the epidemic and identify potential hotspots for targeted intervention. Our results suggest that the incorporation of wastewater data and virus variant modeling can provide valuable insights into the transmission dynamics of infectious diseases and inform more effective public health interventions. Overall, these studies highlight the potential of this approach to revolutionize the field of epidemic modeling and improve our ability to control the spread of infectious diseases.
Additional authors: Tin Phan, Los Alamos National Laboratory; Samantha Brozak, Arizona State University; Yang Kuang, Arizona State University; Fuqing Wu, The University of Texas Health Science Center at Houston; Anna Gitter, The University of Texas Health Science Center at Houston; Amy Xiao, Massachusetts Institute of Technology; Kristina D. Mena, The University of Texas Health Science Center at Houston.