Anticipating the novel coronavirus disease (COVID-19) pandemic

Taranjot Kaur; Sukanta Sarkar; Sourangsu Chowdhury; Sudipta Kumar Sinha; Mohit Kumar Jolly; Partha Sharathi Dutta

The World Health Organisation lately reports new cases being reported into several new countries across the globe [30] [31] [32] . Our study can provide an insight to tackle the ongoing pandemic and its associated growth curve in the context of the timing and strength of the interventions. We use the data of the number of COVID-19 cases in nine different countries to investigate some statistical patterns in the growth curves. The number of cases covers a small fraction of the population during the initiation of the epidemic, and the fraction remains nearly stagnant for around 20 days from the arrival of the first case. After the threshold of around 20 days, the number of cases starts increasing rapidly, and in a relatively shorter span a significant fraction of the population can be affected. This trend is analogous to the idea that the growth curve remains close to one stable state for sufficient time and, crossing a time threshold invokes a sudden shift/transition to another stable state, where a significant fraction of the population gets affected. In our work, we employ statistical indicators of critical slowing down to check if such transitions can be signaled beforehand and how the anticipation of such transitions can help mitigate such crisis at a policy level.