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Data insights: Comprehending the COVID-19 data

India is grappling with the second wave of COVID-19 which has left a question mark on the healthcare infrastructure of the country. The number of positive cases have multiplied exponentially, with cases being reported from urban as well as rural areas. Rural areas have poor health infrastructure as compared to urban areas. But during the second wave the 3 metros of India were worst hit, Pune, Mumbai and Delhi. The healthcare infrastructure crippled; even in developed metros due to high number of cases, overflowing patients from other cities, poor nursing staff, lack of doctors, lack of oxygen, lack of hospital beds, lack of medicines etc. The seriously infected patients from rural areas started coming to urban areas for higher medical assistance. This created artificial scarcity hence implying panic. The doctors are working at their full capacity, even overtime. A lot of healthcare workers have gone under therapy to cope with stress generated due to workload and rampant deaths. This precipice could be witnessed in shamshan ghats across the country. People were waiting in queue  to cremate their loved ones who lost the battle to Covid-19. To avoid queues people started cremating more than one dead body on a single pyre. For instance in Beed district of Maharashtra a total of 8 bodies were cremated on one pyre. The crematorium grounds due to queues started becoming a hatching ground for Covid 19. There were reports from Balrampur and various other districts of Uttar Pradesh where dead bodies, which were suspected to be covid positive were thrown in the river. 

Now cases are on decline and states have slowly started loosening lockdown restrictions. This move towards unlocking is closely watched by the government to keep an eye on rising infection rates.

Covid 19 is the most data rich pandemic in history throughout the world. So whenever we look at data few questions are to be asked to make sense of it :

  • Does the low number of cases reported in newspapers mean a decline in pandemic?
  • What indicator should be focused on to track the rising number of infections?
  • Test-trace-treat, is it the right strategy?
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From all the data that is collected 3 aspects are focused – daily number of tests, identified positives and deaths. From these 3 focus subjects 2 important quantities are created: test positivity and CFR or case fatality rate. Test positivity is the ratio between identified positives to the number of tests conducted. CFR is the ratio between deaths to identified positives. The deaths are likely from identified positives and hence are used to measure CFR. These ratios help us to understand the decline or flare up of the pandemic. 

Test-trace-treat strategy: how it works?

Suppose Mr A went to the market to buy vegetables. He came home and after some time started developing symptoms of Covid 19. He goes for an RT- PCR test and is identified as Corona positive. The next stage would be health workers speaking to Mr A to find out everyone that he has been in contact with lately. Suppose Mr A has been in contact with 15 people and spent less time with 10 of them. Those 10 people are low-risk patients and the rest five high-risk patients due to the amount of time spent. In an utopian situation all these 15 people would have been isolated, checked and tested. But due to constraints of time, money and workforce only the 5 high-risk people are checked and isolated. Now the pandemic won’t spread any further as all high risk patients have been isolated. If only high risk patients are tested, the test positivity ratio is going to be high. But if all the 15 people in this universe are tested the test positivity ratio will be low, due to bigger numbers in denominator. This implies that the pandemic will soon be under control. Test positivity ratio fails to give insights when the infection has spread throughout the population, it is impossible to detect the chain of infection. It means that Mr A went to market when he was tested positive, he spread the infection to God knows who, the test positivity won’t be low even if the number of tests are increased. Also Coronavirus has many asymptomatic cases hence test positivity as an indicator may not help at all. This is a bad situation as it indicates the wide spread of infection. Test positivity though can help in identifying decline of the pandemic. When the infection rate starts declining the number of tests done will decline, the test positivity may likely stay constant or may decline. Meanwhile if the test positivity ratio increases it means that the infection is on the rise again.

What to do when test positivity insights don’t help?

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When test positivity as an indicator fails to give useful insights due to asymptotic cases or widespread infection, experts turn to CFR. To understand CFR another ratio is used called IFR or infection fatality rate. CFR is the ratio between death to identified positives. Where as IFR is the ratio between deaths to the total number of infected persons – identified and unidentified. IFR is usually much lower than CFR because of the large number of population in the denominator (identified positive persons). Let us work out some math to understand how IFR and CFR work.

Let us say that IFR for COVID-19 0.3%. This means that out of every 2000 people 6 people are likely to die. If the CFR is 1%, out of 600 individuals 6 people die or are likely to die. This implies that around 1400 covid positive patients are unidentified. This can be due to widespread infection, asymptomatic cases, constraints of time energy and healthcare workers. If the CFR would have been 2% then 12 people would have likely died. This would mean that the underlying population of 2800 are the infected but undetected people. This implies that the higher the CFR ratio the more is the undetected infected population. Undetected Infected populations are likely to increase the infection hence worsening the situation.

So what does this mean?

High test positivity and high CFR – The number of daily tests being conducted need to be increased. The government can do door to door surveys to identify the infected people before the disease turns rampant. Referring to the above example, higher the CFR rate is the ratio of undetected infected people.

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High test positivity and low CFR – this means that the infection has spread widely but the healthcare infrastructure is responding, and the number of deaths are low. But as we have seen, the government diminished  the numbers of deaths to avoid panic in Gujrat. High test positivity may also mean that there is under reporting of deaths.                    

Low test positivity and low CFR – this is the good news that we have all been waiting for since the last  two years. This indicator means that it is under control.

Low test positivity and high CFR – such phenomena do not exist. This points towards tampering information. The test positivity is artificially kept low.         

Case study : Pune city

Pune was one of the three metros that was hit badly during the first wave of COVID-19. Health infrastructure crippled due to patients pouring in from all directions of the country. The government used CFR, IFR and test positivity ratios to successfully identify positive persons, isolate and treat them. The IFR ratios also helped in identifying the unidentified infected persons, which further helped in containing the spread of infections.  The model also highlights the necessity for transparent data sharing between all the levels of administration. Such a pandemic demands joint action by the government, administration and its people helping in every way. Let’s do our bit while it’s still time.

“Because if a pandemic couldn’t bring us together then I wonder what would?”

Aishwarya Ingle

I am a person who believes in freedom of human mind. A free mind is highly creative and imaginative. Imagination is not a cloth that is to neatly folded in a box, but it is fire. It can light an entire jungle or a single matchstick, it depends upon the free environment.

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