Global between-countries variance in SARS-CoV-2 mortality is driven by reported prevalence, age distribution, and case detection rate

Objective

To explain the global between-countries variance in number of deaths per million citizens ( nD _pm ) and case fatality rate ( CFR ) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

Design

Systematic analysis.

Data sources

Worldometer, European Centre for Disease Prevention and Control, United Nations

Main outcome measures

The explanators of nD _pm and CFR were mathematically hypothesised and tested on publicly-available data from 88 countries with linear regression models on May 1 ^st 2020. The derived explanators – age-adjusted infection fatality rate ( IFR _ad j ) and case detection rate ( CDR ) – were estimated for each country based on a SARS-CoV-2 model of China. The accuracy and agreement of the models with observed data was assessed with R ² and Bland-Altman plots, respectively. Sensitivity analyses involved removal of outliers and testing the models at five retrospective and four prospective time points.

Results

Globally, IFR _adj estimates varied between countries, ranging from below 0.2% in the youngest nations, to above 1.3% in Portugal, Greece, Italy, and Japan. The median estimated global CDR of SARS-CoV-2 infections on April 16 ^th 2020 was 12.9%, suggesting that most of the countries have a much higher number of cases than reported.

At least 93% and up to 99% of the variance in nD _pm was explained by reported prevalence expressed as cases per million citizens ( nC _pm ), IFR _adj , and CDR. IFR _ad j and CDR accounted for up to 97% of the variance in CFR , but this model was less reliable than the nD _pm model, being sensitive to outliers ( R ² as low as 67.5%).

Conclusions

The current differences in SARS-CoV-2 mortality between countries are driven mainly by reported prevalence of infections, age distribution, and CDR . The nD _pm might be a more stable estimate than CFR in comparing mortality burden between countries.