Previously submitted to: JMIR Public Health and Surveillance (no longer under consideration since Sep 02, 2020)
Date Submitted: Sep 2, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A Statistical Analysis of the Most Affected Countries by COVID-19
ABSTRACT
Background:
It is almost more than six months elapsed since the crisis of COVID-19 pandemic has hit the globe. It becomes utterly crucial for policy formulation to know up to which period and up to what magnitude the disease will impact us.
Objective:
Aim of this study is to predict the saturation level of COVID-19 cases in USA, Brazil, India, Russia, Italy and UK.
Methods:
Trend analysis is used to fit exponential trend line to the weekly cumulative positive cases. Forecasted growth constants obtained by fitting power series trend to the observed values and prediction of weekly cumulative cases done. Growth constant value of 0.0039 (Doubling time 180 days), observed mean, median and maximum reported COVID-19 cases per million for countries with more than 90% recovery is used to obtain saturation levels.
Results:
Italy and UK reached saturation with growth constant values 0.0007 and 0.0025. Brazil and USA projected to achieve saturation by 26 September 2020 and 19 December 2020 with 8.24 and 9.17 million cases. India and Russia expected to reach the saturation by 16 January 2021and 27 February 2021 with 56.72 and 3.86 million cases.
Conclusions:
The USA and Russia are predicted to reach saturation due to decrease in growth constant value. Growth constant values for Brazil and India are high and these countries are estimated to reach saturation by infecting the maximum reported per million population. It is therefore eternally essential to take more proactive decisions and to test more and isolate patients effectively to contain COVID-19. Clinical Trial: Nil
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