WHO blames mass gathering events for India’s virus spread
Ministry reports 3,62,727 new COVID-19 cases and 4,120 deaths in 24 hours; Cambridge Judge Business School forecasts that infections will see a decline by May 23
The World Health organisation (WHO) has blamed several religious and political mass gathering events for fuelling India’s dramatic surge in new cases and deaths.
The spread of B1617 and other variants (B117), coupled with low adherence to public health and social measures were other factors for the resurgence of Coronavirus cases in India.
“A recent risk assessment of the situation in India conducted by WHO found that resurgence and acceleration of COVID-19 transmission in India had several potential contributing factors, including increase in the proportion of cases of SARS-COV-2 variants with potentially increased transmissibility; several religious and political mass gathering events which increased social mixing,” the global health agency said in its weekly epidemiological update on the pandemic on Tuesday.
The exact contributions of each of these factors on increased transmission in India are not well understood, the WHO said.
The WHO’S SARS-COV-2 Virus Evolution Working Group on Tuesday determined that viruses within the lineage B1617, first reported in India in October 2020, are a variant of concern. The B1617 variant was, till now, deemed a “variant of interest” by the WHO. It now has been added to the list of other COVID-19 “variants of concern” -- UK (B117), South African (B1351) and Brazilian (P1) variants.
The B1617 variant was declared as a variant of concern based on early evidence of higher rates of transmission, including its observed rapid increases in prevalence in 44 countries, the WHO said.
“The prevalence of several VOCS (variant of concern) including B117 and B1617 sublineages increased concurrent to the surge in COVID-19 cases reported in India,” the WHO update stated.
According to the update, approximately 0.1 per cent of positive samples in India have been sequenced and uploaded to open-access database GISAID ( Global Initiative on Sharing Avian Influenza Data) to identify SARS-COV-2 variants.
While B117 and B16171 variants have begun to wane in recent weeks, a marked increase in the proportion of viruses sequenced as B16172 has been observed over the same period. “Since the identification of these variants through late April 2021, B16171 and B16172 accounted for 21 per cent and 7 per cent of sequenced samples from India, respectively,” said the UN health agency.
It added that preliminary analyses using sequences submited to GISAID suggest that B16171 and B16172 have a substantially higher growth rate than other circulating variants in India.
Besides India, the UK has reported the largest number of cases sequenced as B1617 sub-lineages, the update said.
India on thursday reported 3,62,727 new c ovid -19 cases and 4,120 fatalities, the Union Ministry of Health and Family Welfare said. In the past 21 days India’s daily COVID tally has plateaued over the three-lakh-mark and over 3,000 casualties for a fortnight. India’s total tally of COVID-19 cases now stands at 2,37,03,665 with 37,10,525 active cases and 2,58,317 deaths so far.
A new tracker by Cambridge Judge Business School forecasts that the number of new COVID cases in India has peaked, and will see a declining trend over the two-week forecast period to May 23. But, the tracker said, there is substantial variation among States and Union Territories in their trajectories. Cases will continue to increase over the next two weeks in Assam, Himachal Pradesh, Jammu and Kashmir, Manipur, Meghalaya, Mizoram, Nagaland, Odisha, Puducherry, Punjab, Tamil Nadu and Tripura.
A new CJBS COVID-19 Tracker for India, developed by Cambridge Judge Business School and the National Institute of Economic and Social Research in India working with Health Systems Transformation Plaform in India, provides forecasts of the pandemic’s trajectory based on a recently developed model.
These forecasts are based on a structural time series model that uses historical data in estimation, but adapts to the trend emerging in the most recent period. The model is described in a paper in Harvard Data Science Review by Andrew Harvey, Emeritus Professor of Econometrics at the Faculty of Economics of the University of Cambridge, and Paul Katuman, Reader in Economics at Cambridge Judge Business School, entitled “Time series models based on growth curves with applications to forecasting coronavirus.”