Anticipating the novel coronavirus disease (COVID-19) pandemic

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

Sensitivity Analyses. The predictability of each of the indicator depends upon the datasets investigated as well as the choices made for processing the data. Thus, it is essential to check the efficacy of our results to such choices. In particular, we analyse the sensitivity of our observations to the choice of rolling window size and degree of smoothing (filtering bandwidth) used during the calculation of indicators and detrending/filtering the data sets, respectively. We estimate the return rate using window sizes ranging from 40% to 90% of the time-series length in an increment of 2 points and for bandwidths ranging from 5% to 100% with the increment of 2 points. We quantify the robustness of the outcomes towards the range of window sizes and bandwidth using the distribu-tion of the Kendall-Ï„ test statistic.