Related Experiment Video
Updated: Dec 26, 2025

03:53
Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
1.7K
Case-Fatality Risk Estimates for COVID-19 Calculated by Using a Lag Time for Fatality
Emerging Infectious Diseases
|March 14, 2020
Summary
The case-fatality risk for coronavirus disease varied globally, with lower estimates potentially reflecting the true risk. A range of 0.25% to 3.0% is considered for this infectious disease.
Area of Science:
- Epidemiology
- Infectious Disease Research
Background:
- Coronavirus disease (COVID-19) emerged as a significant global health threat.
- Accurate estimation of case-fatality risk (CFR) is crucial for understanding disease impact and guiding public health responses.
Purpose of the Study:
- To estimate the case-fatality risk of coronavirus disease (COVID-19) in various geographical settings.
- To provide a range for the potential true case-fatality risk based on available data.
Main Methods:
- Analysis of reported coronavirus disease cases and fatalities.
- Calculation of case-fatality risk percentages for different regions, including China, specific provinces, and international locations.
- Consideration of data from a cruise ship outbreak.
Main Results:
- Estimated case-fatality risk in China was 3.5%, and 0.8% excluding Hubei Province.
- In 82 other countries/territories, the estimated risk was 4.2%.
- A cruise ship outbreak showed a case-fatality risk of 0.6%.
Conclusions:
- Case-fatality risk estimates for coronavirus disease vary significantly by location.
- Lower estimates may more accurately represent the true risk, with a suggested range of 0.25%-3.0%.
Related Concept Videos
Hazard Rate
351
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
351
Causality in Epidemiology
1.4K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.4K
Assumptions of Survival Analysis
325
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
325
Actuarial Approach
243
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
243
Steps in Outbreak Investigation
429
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
429
Censoring Survival Data
460
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
460

