The novel coronavirus disease (COVID-19) pandemic will not end before October 2020 in India, according to a study by the Indian Institute of Technology (IIT), Kharagpur.
There will be more than 700,000 COVID-19 cases when the disease outbreak will near its end in the country, according to projections from a logistical model deployed for the study by Abhijit Das, a computer science and engineering faculty at IIT-Kharagpur.
The trend indicated the disease will remain in the country for several months: It is unlikely for the disease outbreak to decrease before the end of September.
The projections, however, were not completely stable and reliable due to limitations in modelling, warned Das.
A calculation — keeping the seven-day rolling average of cases — said Maharashtra, the state affected the most by COVID-19, was expected to have its peak in June.
The expected number of cases in the state will be more than 160,000 till the pandemic ends, the study said.
Delhi will overtake Maharashtra and cross 250,000 cases, with the pandemic expected to end in the state by November, according to the study. For Tamil Nadu, the end may come by October with nearly 130,000 cases.
Uttar Pradesh — which currently has nearly 16,000 cases — is expected to proceed towards the end by November with more than 40,000 cases.
Madhya Pradesh and West Bengal may see the end of the pandemic in September and October, with more than 13,000 and 30,000 cases respectively.
The study, however, has an important limitation.
The results produced by the predictor are unreliable, despite several attempts to improve the performance of the model, according to the study. It cited considerable changes in the spread of the pattern of the disease in the country over time.
“This may be attributed to various causes, like different mobility patterns of the Indian people in different phases of lockdown, large-scale migration of laborers, change in diagnostic facilities, evolution of the SARS-CoV-2 virus that causes COVID-19, and so on,” said the study.
These causes are beyond the control of the logistic model (or any other prediction model), the study pointed out. Future projections may, thus, change with time.