Table 1.
Poisson Regression for PM 2.5, CO, O3, and NO2 relation with the number of cases and deaths in Delhi.
| Cases | Estimate(β) | Std. Error | Z Value | Exp(β) | Pr(>|Z |) |
|---|---|---|---|---|---|
| (Intercept) | 6.469e + 00 | 3.859e-03 | 1676.25 | 644.7784026 | <2e-16 *** |
| PM 2.5 | −1.282e-03 | 2.198e-05 | −58.34 | 0.9987188 | <2e-16 *** |
| CO | 7.632e-03 | 6.422e-05 | 118.85 | 1.0076614 | <2e-16 *** |
| O3 | 4.462e-03 | 4.145e-05 | 107.64 | 1.0044719 | <2e-16 *** |
| NO2 | 4.240e-02 | 1.163e-04 | 364.63 | 1.0433136 | <2e-16 *** |
| Deaths | Estimate(β) | Std. Error | Z Value | Exp(β) | Pr(>|Z |) |
| (Intercept) | 2.5395135 | 0.0292915 | 86.698 | 12.6735034 | <2e-16 *** |
| PM 2.5 | −0.0002536 | 0.0001665 | −1.523 | 0.9997464 | 0.128 |
| CO | −0.0072579 | 0.0006331 | −11.465 | 0.9927684 | <2e-16 *** |
| O3 | 0.0109769 | 0.0002778 | 39.508 | 1.0110374 | <2e-16 *** |
| NO2 | 0.0284741 | 0.0009546 | 29.828 | 1.0288834 | <2e-16 *** |
“Std. Error = Standard Error; β = Coefficient Estimates; Exp(β) = Exponentiated Values. ¥Controlled for temporal trends [date, day of week and weekends]. ⁎ Statistically significant at 5% level of significance”.