Rethinking Case Fatality Ratios for COVID-19 from a data-driven viewpoint

by   Phoebus Rosakis, et al.

The case fatality ratio (CFR) for COVID-19 is difficult to estimate. One difficulty is due to ignoring or overestimating time delay between reporting and death. We claim that all of these cause large errors and artificial time dependence of the CFR. We find that for each country, there is a unique value of the time lag between reported cases and deaths versus time, that yields the optimal correlation between them is a specific sense. We find that the resulting corrected CFR (deaths shifted back by this time lag, divided by cases) is actually constant over many months, for many countries, but also for the entire world. This optimal time lag and constant CFR for each country can be found through a simple data driven algorithm. The traditional CFR (ignoring time lag) is spuriously time-dependent and its evolution is hard to quantify. Our corrected CFR is constant over time, therefore an important index of the pandemic in each country, and can be inferred from data earlier on, facilitating improved early estimates of COVID-19 mortality.



There are no comments yet.


page 1

page 2

page 3

page 4


Estimating Global and Country-Specific Excess Mortality During the COVID-19 Pandemic

Estimating the true mortality burden of COVID-19 for every country in th...

Explainable AI Framework for COVID-19 Prediction in Different Provinces of India

In 2020, covid-19 virus had reached more than 200 countries. Till Decemb...

The impact of undetected cases on tracking epidemics: the case of COVID-19

One of the key indicators used in tracking the evolution of an infectiou...

Optimal Ensemble Construction for Multi-Study Prediction with Applications to COVID-19 Excess Mortality Estimation

It is increasingly common to encounter prediction tasks in the biomedica...

On the intrinsic dimensionality of Covid-19 data: a global perspective

This paper aims to develop a global perspective of the complexity of the...

COVID-19 transmission risk factors

We analyze risk factors correlated with the initial transmission growth ...

Cross-lingual Transfer Learning for COVID-19 Outbreak Alignment

The spread of COVID-19 has become a significant and troubling aspect of ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.