Possibilities of exponential or Sigmoid growth of Covid19 data in different states of India

SUPRIYA MONDAL; Sabyasachi Ghosh

After the extrapolation of disaster side of last growth trend, a hopeful possibility is sketched via Sigmoid function, which can also be extrapolated from same existing data. We consider the two guess values 10 4 and 10 5 , where total cases might be saturated due to undertaking interventions. Then we have plotted two Sigmoid-type profile in time axis. With respect to existing data for available beds in Govt. hospitals, JK, HR, PB are in little high risk zone in comparison to others as the rough values of their no. of beds remain lower than saturation number of Sigmoid functions. Interestingly, their high risk might be reduced by their ongoing undertaking interventions, for which their last trend of exponential growth have very small slope parameters. On the other hand WB, TN, AP due to their large values of Govt. hospital beds, seems to be in low risk zone but in the same time we should not ignore their high risk possibility because of their large slope parameter, noticed in their data. As we know that Sigmoid-type profile in total cases can create a peak structure in new case profile, which means that after a certain time, increasing trend of new cases can be converted to decreasing trend. To get saturation in total cases of 10 4 and 10 5 , maximum states have to face the turning from increasing to decreasing trend in new cases around April or May. However, this time for HR and PB might be relaxed to June or August due to their lower slope parameters.