Impact of disease severity, age, sex, comorbidity, and vaccination on secondary attack rates of SARS-CoV-2: a global systematic review and meta-analysis
Bibliographic record
Abstract
Understanding the key drivers of SARS-CoV-2 transmission is essential for shaping effective public health strategies. However, transmission risk is subject to substantial heterogeneity related to disease severity, age, sex, comorbidities, and vaccination status in different population settings and regions. We aimed to quantify the impact of these factors on secondary attack rates (SARs) of SARS-CoV-2 across diverse population settings and regions, and identify key determinants of transmission to inform targeted interventions for improving global pandemic response. To retrieve relevant literature covering the duration of the COVID-19 pandemic, we searched Ovid MEDLINE, Ovid Embase, Web of Science, and the Cochrane COVID-19 Study Register between January 1, 2020 and January 18, 2024 to identify studies estimating SARs of SARS-CoV-2, defined as the proportion of close contacts infected. We pooled SAR estimates using a random-effects model with the Freeman-Tukey double arcsine transformation and derived Clopper-Pearson 95% confidence intervals (CIs). Risk of bias was assessed using a modified Newcastle–Ottawa scale. This study was registered with PROSPERO, CRD42024503782. A total of 159 eligible studies, involving over 19 million close contacts and 6.8 million cases from 41 countries across five continents, were included in the analysis. SARs increased with disease severity in index cases, ranging from 0.10 (95% CI: 0.06–0.14; I 2 = 99.65%) in asymptomatic infection to 0.15 (95% CI: 0.09–0.21; I 2 = 92.49%) in those with severe or critical conditions. SARs by age were lowest at 0.20 (95% CI: 0.16–0.23; I 2 = 99.44%) for close contacts under 18 years and highest at 0.29 (95% CI: 0.24–0.34; I 2 = 99.65%) for index cases aged 65 years or older. Among both index cases and close contacts, pooled SAR estimates were highest for Omicron and lowest for Delta, and declined with increasing vaccine doses. Regionally, North America had the highest SAR at 0.27 (95% CI: 0.24–0.30; I 2 = 99.31%), significantly surpassing SARs in Europe (0.19; 95% CI: 0.15–0.25; I 2 = 99.99%), Southeast Asia (0.18; 95% CI: 0.13–0.24; I 2 = 99.24%), and the Western Pacific (0.11; 95% CI: 0.08–0.15; I 2 = 99.95%). Among close contacts with comorbidities, chronic lung disease and hypertension were associated with the highest SARs. No significant association was found between SARs and the sex of either index cases or close contacts. Secondary attack rates varied substantially by demographic and regional characteristics of the studied populations. Our findings demonstrate the role of booster vaccinations in curbing transmission, underscoring the importance of maintaining population immunity as variants of SARS-CoV-2 continue to emerge. Effective pandemic responses should prioritise tailored interventions that consider population demographics and social dynamics across different regions.
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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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.042 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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 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".