Omicron B.1.1.529 variant infections associated with severe disease are uncommon in a COVID-19 under-vaccinated, high SARS-CoV-2 seroprevalence population in Malawi
Bibliographic record
Abstract
Abstract Background The B.1.1.529 (Omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the fourth COVID-19 pandemic wave across the southern African region, including Malawi. The seroprevalence of SARS-CoV-2 antibodies and their association with epidemiological trends of hospitalisations and deaths are needed to aid locally relevant public health policy decisions. Methods We conducted a population-based serosurvey from December 27, 2021 to January 17, 2022, in 7 districts across Malawi to determine the seroprevalence of SARS-CoV-2 antibodies. Primary sampling units (PSU) were selected using probability proportionate to the number of households based on the 2018 national census, followed by second-stage sampling units that were selected from listed households. A random systematic sample of households was selected from each PSU within the 7 districts. Serum samples were tested for antibodies against SARS-CoV-2 receptor binding domain using WANTAI SARS-CoV-2 Receptor Binding Domain total antibody commercial enzyme-linked immunosorbent assay (ELISA). We also evaluated COVID-19 epidemiologic trends in Malawi, including cases, hospitalizations and deaths from April 1, 2021 through April 30, 2022, collected using the routine national COVID-19 reporting system. Results Serum samples were analysed from 4619 participants (57% female; 65% aged 14 to 50 years), of whom 1018 (22%) had received a COVID-19 vaccine. The overall assay-adjusted seroprevalence was 86.3% (95% confidence interval (CI), 85.1% to 87.5%). Seroprevalence was lowest among children <13 years of age (66%) and highest among adults 18 to 50 years of age (82%). Seroprevalence was higher among vaccinated compared to unvaccinated participants (96% vs. 77%; risk ratio, 6.65; 95% CI, 4.16 to 11.40). Urban residents were more likely to test seropositive than those living in rural settings (91% vs. 78%; risk ratio, 2.81; 95% CI, 2.20 to 3.62). National COVID-19 data showed that at least a two-fold reduction in the proportion of hospitalisations and deaths among the reported cases in the fourth wave compared to the third wave (hospitalization, 10.7% (95% CI, 10.2 to 11.3) vs 4.86% (95% CI, 4.52 to 5.23), p<0.0001; deaths, 3.48% (95% CI, 3.18 to 3.81) vs 1.15% (95% CI, 1.00 to 1.34), p<0.0001). Conclusion We report reduction in proportion of hospitalisations and deaths from SARS-CoV-2 infections during the Omicron variant dominated wave in Malawi, in the context of high SARS-CoV-2 seroprevalence but low COVID-19 vaccination coverage. These findings suggest that COVID-19 vaccination policy in high seroprevalence settings may need to be amended from mass campaigns to targeted vaccination of at-risk populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".