Coronavirus Impact Index to Expose Data Fraud by Governments

Coronavirus Impact Index. Developed by Rakesh Raman
Coronavirus Impact Index. Developed by Rakesh Raman

Coronavirus Impact Index to Expose Data Fraud by Governments

A simple form of this model can be immediately used to calculate the probable impact of coronavirus in each country.

By Rakesh Raman

It has been observed during the past few months that the devastation being caused by coronavirus on the world population has been increasing dramatically. The political rulers in different countries have been largely responsible for the widespread misery and deaths.

These politicians have been telling blatant lies to hide their own failures in dealing with the pandemic. While the number of coronavirus patients and deaths is far more than what is being reported, the political crooks are deliberately releasing and using fake data to announce their decisions to impose lockdowns or to lift restrictions.

In some cases, the dishonest government officials are not attributing the cause of deaths to coronavirus even when the patients die of the Covid-19 infection. The governments downplay the impact of the disease in order to cover up their failures and win accolades from the citizens by deceiving them with wrong data.

As the coronavirus pandemic is expected to wreak more havoc around the world, there is a need to empirically measure the impact of the pandemic so that the decisions taken by the governments in different countries could be analyzed properly in order to minimize the effect of the virus.

With this objective, I propose a preliminary measurement model to create a Coronavirus Impact Index (CII) for individual countries.

It is based on the population of a country, countable coronavirus tests per million of population, types of tests, probability of getting a test, number of contacts traced per infected person, quarantine as a percentage of traced contacts, number of recovered cases, durability of recovery, and the recurrence of infection in recovered cases.

The model also takes into account the healthcare infrastructure in the country. This includes the number of hospitals, doctors, beds, ICU facilities, personal protective equipment, test kits, ventilators, and so on.

The data collected on all these parameters will be audited by independent agencies to calculate the Coronavirus Impact Index (CII).

A simple form of this model can be immediately used to calculate the probable impact of coronavirus in each country. It will depend on the population of the country, auditable tests conducted, number of positive cases, and number of deaths. The mathematical process of calculation is given below.

Coronavirus Contagion and Death Probability in a Country

Coronavirus Contagion Probability = (Number of positive cases / Number of tests) x Population
Coronavirus Death Probability = (Number of deaths / Number of positive cases) x Infected Population

We can use this mathematical process for different countries. Let us apply this formula on the U.S. where the data accuracy is relatively better than other countries and India which is on the other extreme where fake data is being circulated blatantly. 

U.S. Case

If the number of positive cases in the U.S. is 1.5 million and the number of tests done is 10 million in a population of 330 million, then the Coronavirus Contagion Probability in the U.S. is (1.5 / 10) x 330 = 49.5. In other words, there is a probability that 49.5 million people in the U.S. are infected at present if the tests are done on the entire population.

Similarly, assuming that the number of deaths is 75,000, the Coronavirus Death Probability in the U.S. is (75000 / 1500000 ) x 49500000 = 2,475,000. In other words, there is a probability that at the current level of infection, 2.47 million people are expected to die in the U.S.

Note: The infection to death duration can vary from a few weeks to a few months.

The same model can be used to know the impact of the infection in states, provinces, or districts within a country.

India Case

Now, let us take the case of India where a large-scale data fraud is happening with the aim to understate the impact of coronavirus, although the country of 1.4 billion people has become the epicenter of the pandemic. The following calculation is based on the understated government data that actually cannot be trusted.

Coronavirus Contagion Probability in India is (65000 / 5000000) x 1400000000 = 1820000. In other words, there is a probability that currently 1.8 million people are infected. 

In fact, independent research reports have also stated that at present the number of Covid-19 cases in India is estimated to be 1.3 million, although the government claims that there are fewer cases.

Coronavirus Death Probability in India is (2000 / 65000) x 1820000 = 56,000. In other words, 56,000 people have already died in India, although the government claims that only 2,000 persons have died.

In view of these mathematical facts, the governments, media organizations, and other stakeholders are urged to quantify the impact of Covid-19 instead of just relying on the sketchy data released by the government agencies. The correct use of data will help you take the right decisions in order to combat the pandemic.

By Rakesh Raman, who is a national award-winning journalist and social activist. He is the founder of a humanitarian organization RMN Foundation which is working in diverse areas to help the disadvantaged and distressed people in the society. He also creates and publishes a number of digital publications and research reports on different subjects. These publications include the “Covid Health Bulletin” that covers global coronavirus news and views.

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