Estimation of Risk Factor’s Contribution to mortality from COVID-19 in Highly Populated European Countries

Background: The outbreak of the COVID-19 epidemic and excess mortality attributed to worldwide raised need develop a simple applicable mathematical model for predicting in different countries, as well point out risk factors mortality, and, particular, demographic factors. Methods: A linear was developed based on data (population density, percentage population over age 65 degree urbanity) clinical (number days since first case diagnosed each country) from 10 highly populated (over 8.5 million people) randomly selected European countries (Austria, Hungary, Portugal, Sweden, Czech Republic, Belgium, Netherlands, Romania, Italy, France). regression applied, using IBM SPSS version 20 software. Results: proposed predicts among countries. This is found be correlated (R2=0.821, p=0.042) with actual (reported) number deaths country. Percentage above 65, density appear at state were positively whereas urbanity negatively mortality. Conclusions: population’s exposure COVID 19 are potential dying pandemic, whereas, considered protective factor. However, it should remembered that this medium large populations only continental Europe. Moreover, "first wave" pandemic. Further study evaluate accuracy "second not