Table 1 Model formulation for the nonlinear models fitted to the COVID-19 outbreak data. Note that Y(t) is the daily expected cumulative number of cases and Y(t) = μ(t) + ε(t)
Model | |
|---|---|
Richards | \( \mu (t)=\alpha \left(1+k\exp {\left(-\gamma \left(t-\eta \right)\right)}^{-\frac{1}{k}}\right) \) |
3 Parameter logistic | \( \mu (t)=\frac{\alpha }{1+\mathit{\exp}\left(-\gamma \left(t-\eta \right)\right)} \) |
4 Parameter logistic | \( \mu (t)=\beta +\frac{\alpha -\beta }{1+\mathit{\exp}\left(-\gamma \left(t-\eta \right)\right)} \) |
Gompertz | \( \mu (t)={\alpha}_0+\left(\alpha -{\alpha}_0\right)\exp \left(-\exp \left(-\gamma \left(t-\eta \right)\right)\right) \) |
Weibull | \( \mu (t)={\alpha}_0+\left(\alpha -{\alpha}_0\right)\exp \left(-\left(\frac{t}{\eta}\right)k\right) \) |