Mathematical Modeling and Wastewater-Based Epidemiology

J. Cricelio Montesinos-López (), Maria L. Daza–Torres (), Yury E. García () and Miriam Nuño ()
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J. Cricelio Montesinos-López: University of California, Department of Public Health Sciences
Maria L. Daza–Torres: University of California, Department of Public Health Sciences
Yury E. García: University of California, Department of Public Health Sciences
Miriam Nuño: University of California, Department of Public Health Sciences

A chapter in Handbook of Visual, Experimental and Computational Mathematics, 2026, pp 1449-1464 from Springer

Abstract: Abstract Wastewater-based epidemiology (WBE) is a method to monitor the prevalence of pathogens in a community or regions at large using wastewater (WW) concentrations. During disease outbreaks, WW provides a rapid and effective early indicator of high-risk localities. WBE is a cost-effective surveillance tool, mainly as large-scale community testing efforts are unsustainable long-term. However, using WW data to guide public health decision-making requires understanding factors contributing to uncertainty in disease prevalence estimation and developing actionable metrics. Besides, utilization of confirmed cases to determine disease prevalence in a community can provide biased information given that observed cases depend on tests conducted. Test positivity rate (TPR) is a better indicator for disease spread than confirmed cases because it considers both tests conducted and cases detected. This chapter presents two methods that can be used to estimate COVID-19 (coronavirus disease 2019) prevalence from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA levels in WW. The first approach uses a linear regression model to estimate cases (dependent variable) from WW data (independent variable), choosing an “adequate testing period,” a testing period in which the rate of change in testing is greater than the rate of change in cases. In the second approach, to reduce the bias introduced by clinical testing, the TPR is directly modeled via a beta regression, using WW data through an adaptive scheme incorporating changes in virus dynamics. The reproductive number is estimated for the City of Davis (California), using both approaches.

Keywords: Wastewater-based epidemiology (WBE); COVID-19; Test positivity rate (TPR); Linear regression; Beta regression; Bayesian inference (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-16368-4_29

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