From: COVID-19 outbreaks surveillance through text mining applied to electronic health records
Age Groups | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
18-24 | 25-34 | 35-44 | 45-54 | 55-64 | ≥65 | TOTAL | ||||||||
\(\tau_c\) | \({\widehat p}_{i,j}\) | \(\tau_c\) | \({\widehat p}_{i,j}\) | \(\tau_c\) | \({\widehat p}_{i,j}\) | \(\tau_c\) | \({\widehat p}_{i,j}\) | \(\tau_c\) | \({\widehat p}_{i,j}\) | \(\tau_c\) | \({\widehat p}_{i,j}\) | \(\tau_c\) | \({\widehat p}_{i,j}\) | |
Wave 1 | 96 | 0.69 | 92 | 0.77 | 67 | 0.80 | 66 | 0.80 | 61 | 0.81 | 73 | 0.71 | 72 | 0.82 |
Wave 2 | 85 | 0.59 | 26 | 0.77 | 23 | 0.90 | 22 | 0.95 | 22 | 0.94 | 18 | 0.90 | 25 | 0.93 |
Wave 3 | 25 | 0.91 | 17 | 0.88 | 12 | 0.89 | 11 | 0.82 | 16 | 0.82 | 18 | 0.86 | 17 | 0.88 |