According to Dr Anil Kumar, Deputy Director General (Public Health), Directorate General of Health Services of the Ministry of Health and Family welfare, the pandemic in India will be over in mid-September.

In his article published in Epidemiology International Journal, Kumar, along with co-author and Deputy Assistant Director General (Leprosy) of Directorate General of Health Services, Health Ministry, Rupali Roy, have predicted that the pandemic would extinguish in India in mid-September.

Their prediction is based on Bailey’s model where Relative Removal Rate (BMRRR) is considered for reaching a conclusion.

Speaking to IANS, Dr Kumar said, “There is a well-known model called Bailey’s Model. It is based on Relative Removal Rate which means how many cases are entering the pool and how many are going out of the pool. When the number of infected is equal to the number of removed patients, the coefficient will reach 100% threshold, then this pandemic will be over.”

In this model, the removal rate is calculated which is the percentage of removed persons in the infected population. Further, a regression analysis has been done to show the linear relationship between the total infection rate and the total recovery rate.

“This model is applicable on any infectious disease. Whatever you do, you will be reaching 100 per cent one day. The relative removal rate means all those who have got infection will be either cured or dead. when we did the study on May 19, it was 42% but now it is around 50 per cent and in the middle of september, it will be 100 percent,” said Kumar.

According to this mathematical calculation, taking the rate to higher and higher level is reflection of moving forward in the right direction and success of control measures being taken. The linear regression analysis has been used in this study and it is showing that the linear line is reaching 100 in the middle of September, 2020.

“So it may be interpreted that at that point of time, the number of the infected will be equal to the number of removed patients, and that’s why the coefficient will reach 100% threshold,” said the study.

“This is a very good model to support analysis and interpretation of State and District data (whenever the number of cases is high) and it will also help in relevant decision-making in control activities of COVID 19 pandemic,” said the study.

“This will further help the government to take long-term disease prevention and intervention programs,” it said.

However Kumar said all the mathematical models are not absolute and it depends upon the quality of data available.

“All states have different policies in reporting the number of cases. Some are reporting only severe cases, while some are reporting both severe and mild cases. A few states conduct less tests, thus report less cases. Therefore it is very important to report correct data for more accurate results,” said Kumar.

Talking about the implementation of lockdown in the country, Kumar said the lockdown could have yielded even better results.

“We could not achieve what we could have. However the idea of lockdown was very good, but due to various reasons, it was not so effective. Lockdown is more of an administrative decision, but the real measure needs to be taken at community level,” Kumar told IANS. “Otherwise, we can not get benefit of it, he added.

“If you allow transmission to occur and no measures are taken at community level, then it will be very difficult to control the outbreak,” Kumar said.

When asked what percentage of the population will get the infection in India, Kumar said the study does not predict the number of cases in the country. “No one can predict how much the population will get affected — it depends upon so many things such as, from now on, how people are going to maintain distancing and how public health measures will be taken in future.

“It also depends upon how different governments are going to act,” Kumar said, adding it is very much possible to prevent so many corona cases from occurring in the country.

“There should be uniformity in applying public health measures at the community level throughout the country. My model does not suggest the number of cases. I have only predicted when this will be over. The prediction depends upon the surveillance system and quality of data.”

(IANS)