Estimating the case fatality ratio for COVID-19 using a time-shifted distribution analysis

Area of Science:

• Epidemiology
• Public Health
• Biostatistics

Background:

• Accurate estimation of the case fatality ratio (CFR) for COVID-19 is crucial for public health response.
• Early outbreak data presents challenges for precise CFR calculation due to reporting delays and diagnostic uncertainties.
• Existing methods struggle with the dynamic nature of novel infectious diseases.

Purpose of the Study:

• To introduce a straightforward method for calculating COVID-19's case fatality ratio (CFR) using publicly available time-series data.
• To determine the time delay between case and death reporting and estimate the CFR.
• To provide a transparent and reliable tool for assessing disease severity and healthcare system performance.

Main Methods:

• Developed Time-Shifted Distribution (TSD) analysis, correlating temporal case and death reporting.
• Applied TSD to early COVID-19 outbreak data from multiple countries.
• Incorporated excess mortality and seroprevalence data to refine CFR estimates into infection fatality ratio (IFR).

Main Results:

• TSD analysis reliably estimates CFR and case-death reporting delays post-exponential growth phase.
• Calculated CFR varied widely (0.2%–20%) across different countries.
• Infection fatality ratio (IFR) estimates were generally 0.5%–0.8% for moderate outbreaks and 1%–3% for severe outbreaks.

Conclusions:

• Time-Shifted Distribution (TSD) analysis offers a simple, transparent, and reliable method for estimating disease fatality ratios.
• The method aids in understanding disease dynamics and evaluating public health surveillance systems.
• Refined IFR estimates provide a more accurate picture of COVID-19's true mortality across diverse outbreak severities.