So far, the world’s second-most populous country, India appears to have dodged the bullet by reducing the estimated millions of Coronavirus cases with a significantly tiny figure of 100k+, as of 19 May. What could be the possible reasons for the nation having things under control? Were the range of lockdowns helpful in flattening the curve after all?
Crux of the Matter
Speedy Decision-Making By Authorities The Oxford COVID-19 Government Response Tracker (OxCGRT), used data from 73 countries to report the commendable work of the Indian government in tackling the pandemic. It noted the government’s swift action, emergency policy-making, emergency investment in healthcare, fiscal measures, investment in vaccine research, and active response to the situation and scored India with a “100” for its strictness.
Impact of Lockdowns From introducing Lockdown 1.0 to taking swift decisions in 4.0, India announced a nationwide lockdown when the country had reported 519 coronavirus cases. Subsequently all international commercial flights were banned from landing in India and all passenger train services in the country were suspended.
Comparing this with other nations, Italy waited until it had 9,200 + cases while the UK had about 6,700 before both went into lockdowns. Thus while India took 106 days to reach the 80,000-mark, Italy, Spain, Germany and the US took 44-66 days to reach the same. So the sooner the people were self quarantined the lesser the point of contacts were established.
What Do The Figures Say About The Impact Of Lockdowns?
Journey from 1.0 to 4.0 in terms of doubling time
Doubling time refers to the time taken for a parameter to double in value. So if the doubling time of the number of new cases increases steadily over a period of time, it indicates that it is taking more time for new cases to emerge and thus the transmission rate of infection has declined. So if doubling time is 2, it means, day 1’s 10 cases become 20 on day 2 cases and 40 on day 3 and so on.
A large rise or dip in the number of total cases can give an incorrect impression of the severity of the spread of the disease. Therefore, doubling time is often calculated using a metric of 5-day, 7-day, or 10-day average of cases, in order to capture data trends over longer stretches of time.
In terms of a 5-day average calculated for India, On March 12, the first death was reported and when the death rate reached 10, on March 24, India announced the first Lockdown with a doubling time of 3 days. In the subsequent lockdown 2.0 declared on 14 April, the growth rate of the pandemic slowed down to a doubling time of 7 days by 18 April.
Then in lockdown 3.0 extended from May 1 to May 17, this very doubling time improved to 13.6 days, as reported on the last day of lockdown by the Health Ministry. Furthermore the country was divided into 3 zones namely Green Zone, Red Zone, Orange Zone in the third lockdown, that signified the relaxations implemented in each of them accordingly. Currently the country is in phase 4 of the nationwide lockdown which involves restarting of day to day lives of citizens.
To each doubling time projection, existed their own total cases
Case Projection: The estimated number of active coronavirus cases based on prior data values Actual Cases: The number of coronavirus cases calculated and updated on a daily, real-time basis
If that doubling time of 3 days from lockdown 1.0 continued for 2 months from March 17 to May 19, there would have been 150 million projected cases till date i.e more than 10% of the 1.3 billion Indian population!
Similarly if the doubling time of 7 days obtained on 11 April, the day of 7.5k active cases, continued for an approximate time of 30 days, 2.5 Lakh projected cases would have existed today in India.
However as of 19 May, India stands at a relatively optimistic figure of 1.1+ Lakh actual cases which directly signifies how the lockdowns imposed in the nation have made things come under control. The flattening of the coronavirus curve occurred when it could have gone far worse and steeper, as portrayed by blue and red curves respectively in the aforementioned graph.
Figures A and B confirm the same observations, wherein the former estimates are in stark contrast with the slowed-down latter doubling rate of actual cases (total, active and deaths).
As inferred from the stacked graph above, the active rate has decreased in the time frame of March to May along with an increase in recovery rate, that portrays an overall positive representation of the decline of infection in the country’s cases.
Zooming in on the red, straight lined fatality rate in the graph plotted w.r.t y-axis shooting up to ~3.5%, the measure saw an all-time low on 21 March and after witnessing a subtle rise from late March to mid-April. Thereby it remained constant at approximately 3%, with the latest figure stating a decline after 19 May.
It has been noted that the actual fatality rate signifies the total number of deaths reported by authorities globally due to novel coronavirus, refers to the demise of severely affected, hospitalized patients.
State-wise Test statistics in India
Number of Tests conducted globally
How To Maintain The Winning Curve? According to experts, India must continue to test, identify, and isolate the cases early to limit the spread of the disease even after the nationwide lockdown comes to a complete end. The hotspots should be updated on a daily basis in terms of the active and recovery cases and localise necessary lockdownmeasures accordingly.
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The 1994 plague in India was an outbreak of bubonic and pneumonic plague in south-central and western India from 26 August to 18 October 1994. A total of 693 cases and 56 deaths were reported. The center of the plague was Surat, Gujarat.