Related Experiment Video
Updated: Jun 14, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Science-based exit from stringent countermeasures against COVID-19: Mortality prediction using immune landscape
Taishi Kayano1,2, Misaki Sasanami1, Hiroshi Nishiura1,2
1Kyoto University School of Public Health, Yoshida-Konoe-cho, Sakyo-ku, Kyoto 606-8501, Japan.
Background:
Stringent public health and social measures against COVID-19 infection were implemented to avoid an overwhelming hospital caseload and excessive number of deaths, especially among elderly people. We analyzed population-level immunity and predicted mortality, calculated as the potential number of deaths on a given calendar date in Japan, to develop a science-based exit strategy from stringent control measures.
Methods:
Immune proportions were inferred by age group using vaccination coverage data and the estimated number of naturally infected individuals. Immunity against symptomatic illness and death were estimated separately, allowing for inference of the immune fraction that was protected against either COVID-19-related symptomatic infection or death. By multiplying the infection fatality risk by age group for the immune fraction, the potential number of deaths was obtained.
Results:
Accounting for a second and third dose of messenger RNA vaccine in the present-day population, approximately 155,000 potential deaths would be expected among people aged ≥ 60 years if all individuals were infected at the very end of 2022. A fourth dose (i.e., second booster) with a coverage identical to that of the third dose could reduce mortality by 60%. In all examined settings, the largest number of deaths occurred among people aged 80 years and older.
Conclusions:
Our estimates can help policymakers understand the mortality impact of the COVID-19 epidemic in a quantitative manner and the critical importance of timely immunization so as to assist in decision making.
Related Concept Videos
Cancer Survival Analysis
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Vaccinations
Assumptions of Survival Analysis
Steps in Outbreak Investigation
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

