Bangladesh is one of the most densely populated countries in the world struggling to prevent COVID-19 (coronavirus disease 2019). This study employed correlation, cluster analysis, and multiple linear regression analyses using district-wise COVID-19 infection and socioeconomic data. It is observed that there is a strong positive correlation ( r = 0.876, P < .001) between population density and COVID-19, explaining a 60% variation in Bangladesh. The relationship between urbanization and COVID-19 is also positively strong ( r = 0.802, P < .001). Urban settlements have a higher risk of spreading diseases due to the enormous population density. For future planning to prevent COVID-19 and other related infectious diseases, population density should be considered a risk factor.
【저자키워드】 COVID-19, Bangladesh, population density, population density and COVID-19, urbanization and COVID-19, 【초록키워드】 coronavirus disease, Diseases, Variation, risk factor, COVID-19 infection, Cluster, correlation, disease, Analysis, Multiple linear regression, urban, higher risk, positive correlation, country, Prevent, 【제목키워드】 Population, Factor, density, Like,