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India’s coronavirus cases will cross 15,000-mark-a-day by mid-June, predicts China; explains why

India is likely to witness a steady rise in Covid-19 cases in June with the daily increase crossing 15,000-a-day by the middle of the month, a global forecast model for the coronavirus pandemic prepared by Chinese researchers has predicted.

Established by Lanzhou university in northwest China’s Gansu province, the “Global Covid-19 Predict System” makes daily forecasts for 180 countries.

The research group’s forecast model for India for June 2 had predicted 9,291 new confirmed cases in India; Indian government official data put the increase — the biggest yet for a single day — at 8,909 cases in the last 24 hours.

From Wednesday onwards, the model predicts 9676, 10,078, 10,498 and 10,936 daily new cases for the next four days.

Another example: India on Friday reported 7,467 new cases of the coronavirus disease for May 28 (Thursday).

“For May 28, we had predicted 7,607 new cases of Covid-19 in India, which is close to the reported number. Our prediction is at an initial stage. Error analysis will soon be updated on our website,” Huang Jianping, director of Lanzhou University’s Collaborative Innovation Center of Western Ecological Safety, who is heading the project told HT.

By June 15, India could see more than 15,000 new confirmed cases of Covid-19 every day.

India has recorded more than 8,000 cases for three consecutive days with the total number of infections now at over 2,00,000.

The same system predicts that the US will see a daily increase of 30,000 new cases in June and major countries in Europe will witness a continuous drop in new daily cases.

The dynamic forecasting model, which was unveiled online last week, takes into account the impact of climate and environmental conditions, population densities as well as control measures implemented by governments.

“The spread of the virus is affected by many factors, including population density, quarantine measures, and of course the environmental factors,” Huang said.

“Different factors contribute differently in different regions in the world.

Meteorological factors can affect the spread of the virus. We believe it is necessary to consider the impact of temperature and humidity, although the degree of their influence varies in different regions,” Huang, the project leader, said.

“For India, the high population density reduces the social distance and is conducive to the development of pandemic. The influence of temperature is limited, compared with other factors,” he said.

Experts say that the number of new cases in India will rise as the government gradually eases the lockdown.

“Before the release of the system, repeated verification and debugging were carried out. There are many factors affecting the development of the Covid-19, and we will continue to adjust and improve it according to the actual situation,” Huang said.

The Centre’s prediction model is based on statistical epidemiology model and in the data in the model construction such as the number of confirmed cases and the death toll are from US’s Johns Hopkins University.

Meteorological data such as temperature and humidity were taken from the European Centre for Medium-Range Weather Forecasts (ECMWF) and NASA.

According to the research, usually the temperature most conducive for the spread of the novel coronavirus is between 5 degrees Celsius and 15 degrees Celsius, with 60 percent of the Covid-19 cases around the world reported within the temperature scope.

“Our previous study found that 60 percent of the confirmed cases of Covid-19 occurred in places where the air temperature ranged from 5 °C to 15 °C, with a peak in cases at 11.54 °C and approximately 73.8 percent of the confirmed cases were concentrated in regions with absolute humidity of 3 g/m3 to 10 g/m3.”

The content of nitrogen dioxide in the atmosphere is taken into account as it is related to vehicular exhaust.

According to Huang, if the nitrogen dioxide content is less in the atmosphere, it means non-pharmaceutical measures like lockdowns and restrictions on transport have been effective.



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