A0957
Title: Tolerance interval for COVID-19 data forecasting
Authors: Hsiuying Wang - National Yang Ming Chiao Tung University (Taiwan) [presenting]
Abstract: Tolerance intervals (TIs) are widely used in manufacturing engineering, clinical research, and the pharmaceutical industry. These statistical tools help establish control chart limits for monitoring quality characteristics and setting upper bounds on key quantities, ensuring effective decision-making. Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first emerged in December 2019 and rapidly escalated into a global pandemic. The outbreak posed significant challenges for public health systems, requiring robust data-driven methods to track infection trends and guide response efforts. The TI method is applied to develop a control chart for monitoring daily COVID-19 case counts and establishing upper limits on reported cases. By incorporating statistical limits, this approach provides a structured framework for detecting significant deviations in case numbers, enabling authorities to assess infection trends and implement timely interventions. Real-world data examples demonstrate the effectiveness of these methods, highlighting their potential to enhance pandemic management.
