High SARS-CoV-2 seroincidence but low excess COVID mortality in Sierra Leone in 2020–2022
Bibliographic record
Abstract
While SARS-CoV-2 infection appears to have spread widely throughout Africa, documentation of associated mortality is limited. We implemented a representative serosurvey in one city of Sierra Leone in Western Africa, paired with nationally representative mortality and selected death registration data. Cumulative seroincidence using high quality SARS-CoV-2 serological assays was 69% by July 2021, rising to 84% by April 2022, mostly preceding SARS-CoV-2 vaccination. About half of infections showed evidence of neutralizing antibodies. However, excess death rates were low, and were concentrated at older ages. During the peak weeks of viral activity, excess mortality rates were 22% for individuals aged 30-69 years and 70% for those over 70. Based on electronic verbal autopsy with dual independent physician assignment of causes, excess deaths during viral peaks from respiratory infections were notable. Excess deaths differed little across specific causes that, a priori, are associated with COVID, and the pattern was consistent among adults with or without chronic disease risk factors. The overall 6% excess of deaths at ages ≥30 from 2020-2022 in Sierra Leone is markedly lower than reported from South Africa, India, and Latin America. Thus, while SARS-CoV-2 infection was widespread, our study highlights as yet unidentified mechanisms of heterogeneity in susceptibility to severe disease in parts of Africa.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".