Author(s)  
Amos Golan
Tinatin Mumladze
Danielle Wilson
Elissa Cohen
Troy McGuinness
William Mooney
Jisung Moon

The possibility of reoccurring waves of the novel coronavirus that triggered the 2020 pandemic makes it critical to identify underlying policy-relevant factors that could be leveraged to decrease future COVID-19 death rates. We examined variation in a number of underlying, policy- relevant, country-level factors and COVID-19 death rates across countries. We found three such factors that significantly impact the survival probability of patients infected with COVID-19. In order of impact, these are universal TB (BCG) vaccination, air pollination deaths, and a health-related expenditure. We quantify each probability change by age and sex. To deal with small sample size and high correlations, we use an information-theoretic inferential method that also allows us to introduce priors constructed from independent SARS data.

Publication Type  
Working Paper
File Description  
First Version, May 22, 2020
JEL Codes  
I14: Health and Inequality
D82: Asymmetric and Private Information; Mechanism Design
Keywords  
BCG vaccine
coronavirus
COVID-19
health expenditure
inference
information theory
policy
pollution level
COVID