Understanding the excess COVID-19 burden among immigrants in Norway
Bibliographic record
Abstract
BACKGROUND: We aim to use intermarriage as a measure to disentangle the role of exposure to virus, susceptibility and care in differences in burden of COVID-19, by comparing rates of COVID-19 infections between immigrants married to a native and to another immigrant. METHODS: Using data from the Norwegian emergency preparedness, register participants (N=2 312 836) were linked with their registered partner and categorized based on own and partner's country of birth. From logistic regressions, odds ratios (OR) of COVID-19 infection (15 June 2020-01 June 2021) and related hospitalization were calculated adjusted for age, sex, municipality, medical risk, occupation, household income, education and crowded housing. RESULTS: Immigrants were at increased risk of COVID-19 and related hospitalization regardless of their partners being immigrant or not, but immigrants married to a Norwegian-born had lower risk than other immigrants. Compared with intramarried Norwegian-born, odds of COVID-19 infection was higher among persons in couples with one Norwegian-born and one immigrant from Europe/USA/Canada/Oceania (OR 1.42-1.46) or Africa/Asia/Latin-America (OR 1.91-2.01). Odds of infection among intramarried immigrants from Africa/Asia/Latin-America was 4.92. For hospitalization, the corresponding odds were slightly higher. CONCLUSION: Our study suggests that the excess burden of COVID-19 among immigrants is explained by differences in exposure and care rather than susceptibility.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".