  The Nonlinear Grey Bernoulli Model NGBM(1, 1) is a recently developed grey
model which has various applications in different fields, mainly due to its
accuracy in handling small time-series datasets with nonlinear variations. In
this paper, to fully improve the accuracy of this model, a novel model is
proposed, namely Rolling Optimized Nonlinear Grey Bernoulli Model RONGBM(1, 1).
This model combines the rolling mechanism with the simultaneous optimization of
all model parameters (exponential, background value and initial condition). The
accuracy of this new model has significantly been proven through forecasting
Vietnam's GDP from 2013 to 2018, before it is applied to predict the total
COVID-19 infected cases globally by day.
