The aim of this work was to detect counties in Croatia with a high risk of infection with the coronavirus in the first half of 2021 with the help of spatial statistics methods. For the purpose of assessing the risk of infection, we use the standardized mortality ratio and three different empirical Bayesian estimators. We used the death rate to estimate mortality. We also observe the influence of various covariables on mortality. We come to the following conclusion. In terms of morbidity, Primorsko-Goranska County has the highest risk, followed by Međimurje and Varaždin. As for mortality, Karlovac County has the highest risk, followed by Varaždin County, the City of Zagreb, Ličko-Senjeska and Osječko-Baranjska. Guided by the age distribution of the population, we tried to show that the population over 60 is a statistically significant variable for increased mortality from corona, but we failed to achieve the convergence of the Markov chain. After that, we presented spatial air pollution in the first half of 2021. The model we implemented indicated statistical significance with the convergence of the Markov chain. In counties where air pollution was the highest, we find the same main pollutant, PM2.5. Obviously, as these tiny PM2.5 particles cause problems in the respiratory system, in combination with the coronavirus, more deaths occur.