Table 2. Gompertz distribution: Parameter estimation (before and after lockdown).
| (1) | (2) | (3) | |
|---|---|---|---|
| During Lockdown | Immediately After Lockdown | Few months after Lockdown | |
| B (upper asymptote) | 257405.67*** | 434546.42*** | 429394.34*** |
| (11167.77) | (7816.18) | (7521.98) | |
| β(growth rate of infection) | 0.0269*** | 0.0212*** | 0.0214*** |
| (41.52) | (52.58) | (52.69) | |
| K (point of inflection) | 22069.27*** | 22088.76*** | 22088.16*** |
| (1.46) | (0.97) | (0.95) | |
| Log-likelihood | -669.04 | -1470.70 | -1483.81 |
| N | 86 | 153 | 154 |
Standard errors in parentheses.
* p < 0.05
** p < 0.01
*** p < 0.001.
It is the cumulative cases at time t, B is the upper asymptote. β is the growth rate of infection, K is the point of inflection. The cumulative cases are estimated through three parameters: B and β, K, and applying a non-linear regression. Once we estimate the parameters with non-linear regression, we can predict It which is infection cases. Higher β indicates higher growth of infection.