Understanding variation in reported covid-19 deaths with a novel Shewhart chart application

Area of Science:

• Epidemiology
• Statistical Process Control
• Public Health Surveillance

Background:

• Effective epidemic monitoring requires distinguishing meaningful changes from expected variability.
• Lack of real-time assessment tools hinders recognition of improving or worsening epidemic conditions.
• Policymakers and healthcare providers need reliable methods to interpret daily outcome variations.

Purpose of the Study:

• To develop a novel Shewhart chart for visualizing and analyzing variations in reported epidemic deaths.
• To create a tool that aids in understanding epidemic trends during public health crises like the coronavirus disease 2019 (COVID-19) pandemic.
• To provide a practical method for real-time assessment of epidemic conditions.

Main Methods:

• Developed a hybrid C-chart and I-chart to detect exponential growth in reported deaths.
• Utilized reported deaths as the unit of analysis due to variability in case reporting and testing.
• Assessed chart performance through simulations and case studies to define technical parameters.

Main Results:

• The hybrid chart successfully detected the onset of exponential growth in reported deaths.
• The chart identified early indicators signaling the conclusion of the exponential growth phase.
• Demonstrated the chart's applicability to other critical pandemic-related measures with available high-quality data.

Conclusions:

• The novel hybrid chart offers a practical tool for visualizing and learning from daily reported deaths during epidemics.
• Timely and reliable signals of epidemic waxing or waning are crucial and have significant implications.
• Shewhart charts should be integrated as a standard method for real-time epidemiological data analysis during pandemics.