Influenza-associated hospitalisation and mortality rates among global Indigenous populations; a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: More than 50 million influenza infections and over 100,000 deaths from influenza occur annually. While Indigenous populations experience an inequitable influenza burden, the magnitude of this inequity has not previously been estimated on a global scale. This study compared rates of influenza-associated hospitalisation and mortality between Indigenous and non-Indigenous populations globally. METHODS: A systematic review and meta-analysis was conducted including literature published prior to 13 July 2021. Eligible articles either reported a rate ratio (RR) comparing laboratory-confirmed influenza-associated hospitalisation and/or mortality between an Indigenous population and a corresponding benchmark population, or reported sufficient information for this to be calculated using publicly available data. Findings were reported by country/region and pooled by country and period (pandemic/seasonal) when multiple studies were available using a random-effects model. The I2 statistic assessed variability between studies. RESULTS: Thirty-six studies (moderate/high quality) were included; all from high or high-middle income countries. The pooled influenza-associated hospitalisation RR (HRR) for indigenous compared to benchmark populations was 5·7 (95% CI: 2·7-12·0) for Canada, 5·2 (2.9-9.3) for New Zealand, and 5.2 (4.2-6.4) for Australia. Of the Australian studies, the pooled HRR for seasonal influenza was 3.1 (2·7-3·5) and for pandemic influenza was 6·2 (5·1-7·5). Heterogeneity was slightly higher among studies of pandemic influenza than seasonal influenza. The pooled mortality RR was 4.1 (3·0-5.7) in Australia and 3·3 (2.7-4.1) in the United States. CONCLUSIONS: Ethnic inequities in severe influenza persist and must be addressed by reducing disparities in the underlying determinants of health. Influenza surveillance systems worldwide should include Indigenous status to determine the extent of the disease burden among Indigenous populations. Ethnic inequities in pandemic influenza illustrate the need to prioritise Indigenous populations in pandemic response plans.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.000 | 0.006 |
| 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) | 0.000 | 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".