COVID-19 infections in the districts of Oslo

Belonging to certain ethnic groups, socioeconomic status and cramped living conditions are assumed to affect the risk of infection with SARS-CoV-2. We wanted to examine correlations between a selection of sociodemographic variables and infection rates in Oslo's districts.

Aggregated data on districts obtained from Oslo City Government's statistics database were collated with cumulative figures for PCR-confirmed cases of SARS-CoV-2 as of 3 December 2020. We selected some variables from the living conditions indicators that showed a strong correlation with infection rates. The composite variable 'socioeconomic status' included income, education and labour market attachment. 'Household density' included the proportion of people in cramped living conditions and multi-family households. We performed an unadjusted and adjusted standard multiple linear regression analysis of the impact of immigrant ratio, socioeconomic status and household density on infection rates.

Immigrant ratio, socioeconomic status and household density were all associated with infection rates in the districts. Pearson's correlation coefficients (95 % CI) were 0.97 (0.93 to 0.99), -0.93 (-0.97 to -0.86) and 0.88 (0.77 to 0.98) respectively, all with p <0.001. In the adjusted model, immigrant ratio was still associated with the infection rate, B = 3.95 (2.16 to 5.73), p <0.001, however there was no longer a statistically significant association between socioeconomic status or household density and infection rates.

Immigrant ratio seems to be an important risk factor for infection in Oslo. Our analysis suggests that the correlation may be due to factors other than low socioeconomic status and high household density.