We have attempted to interpret existing n-cov positive data in India with respect to other countries -Italy, USA, China and South Korea. We have mainly zoomed in the exponential growth in a particular zone of time axis, which is well followed in the data profile of India and Italy but not in others. A deviation from exponential growth to Sigmoid function is analyzed in the data profile of China and South Korea. Projecting that pattern to time dependent data of total number and new cases in India, we have drawn three possible Sigmoid functions, which saturate to cases 10 4 , 10 5 , 10 6 . Ongoing data has doubtful signal of those possibilities and future hope is probably in extension of lock-down and additional imposition of interventions.All rights reserved. No reuse allowed without permission.
We have attempted to understand existing covid19 data of India, where growth of total and new cases with time in different states are kept as focal points. Identifying the last trend of exponential growth, mainly noticed in month of March, we have zoomed in its disaster possibilities by straight forward extrapolation of exponential growth. As a hopeful extrapolation, the existing data might be considered low time-axis values of Sigmoid-type function, whose growth might be saturated to values of 10 4 or 10 5 . To fulfill this expectation, a turning from increasing to decreasing trend in new case data should be noticed around April-May, which definitely demand extension of present lock-down with additional interventions.
Understanding first and second wave of covid19 Indian data along with its few selective states,
we have realized a transition between two Sigmoid pattern with twice larger growth parameter
and maximum values of cumulative data. As a result of those transition, time duration of
second wave shrink to half of that first wave with four times larger peak values. It is really
interesting that the facts can be easily understood by simple algebraic expressions of Sigmoid
function. After understanding the crossing zone between first and second wave curves, a third
wave Sigmoid pattern is guessed.
We have worked on imported covid19 cases of India, detected after declaration of lock down.
They are marked as hidden travelers, who are detected later during 1-2 weeks period of lock down.
We have investigated the impact of those travelers on selective 15 states, having large number cases.
Among them 5 states have faced a noticeable effect on their data profile, although its overall effect
in country level is quite negligible. Searching the Sigmoid trends of all 15 states, we have identified
3 categories depending upon latest data of new case with respect to the peak value of Sigmoid
functions. Based on our optimistic predicted curves, ongoing lock down period might be enough for
getting marginal values of new cases for KL, HR, JK, TN and AP but the reamining of 15 states
might need a third phase of lock down or alternative preventive measures.
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