ABSTRACT
Demand shocks—unobservable, sudden changes in customer behavior—are a common source of forecast error in airline revenue management systems. The COVID-19 pandemic has been one example of a highly impactful macro-level shock that significantly affected demand patterns and required manual intervention from airline analysts. Smaller, micro-level shocks also frequently occur due to special events or changes in competition. Despite their importance, shock detection methods employed by airlines today are often quite rudimentary in practice. In this paper, we develop a science-based shock detection framework based on statistical hypothesis testing which enables fast detection of demand shocks. Under simplifying assumptions, we show how the properties of the shock detector can be expressed in analytical closed form and demonstrate that this expression is remarkably accurate even in more complex environments. Simulations are used to show how the shock detector can successfully be used to identify positive and negative shocks in both demand volume and willingness-to-pay. Finally, we discuss how the shock detector could be integrated into an airline revenue management system to allow for practical use by airline analysts. © 2022, The Author(s), under exclusive licence to Springer Nature Limited.
ABSTRACT
The COVID-19 pandemic has highlighted the potential role that wastewater-based epidemiology can play in assessing aggregate community health. However, efforts to translate Sars-CoV-2 gene copy numbers obtained from wastewater samples into meaningful community health indicators are nascent. In this study, Sars-CoV-2 nucleocapsid (N) genes (N1 and N2) were quantified weekly using reverse transcriptase droplet digital PCR from two municipal wastewater treatment plants for approximately six months. Four biomarkers (ammonia, biological oxygen demand, creatinine, and human mitochondrial gene NADH dehydrogenase subunit 5) were quantified and used to normalize Sars-CoV-2 gene copy numbers. These were correlated to case data. Mitochondrial and creatinine normalization methods showed the strongest correlations throughout the studying indicating that human-specific biomarkers were better at normalizing wastewater data than ammonia or BOD. The human-specific biomarkers have different physical properties and corresponding behavior. As such, it may be important to use a suite of biomarkers to better align with the specific behavior of the epidemiological agent of interest. Copyright © 2021 Water Environment Federation