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Spikes in Coronavirus cases in China coincide with important political events, raises question on the authenticity of data: Report

Recently, it had emerged that number asymptomatic Coronavirus positive persons were not included the official data of the pandemic released by the govt.

Ever since the Wuhan Coronavirus outbreak hit the world, its origin China has been under the cloud for its role in the pandemic. China had misled the world about the severity of the virus in the beginning, which led to the widespread distribution of the virus across the world, and now Chinese numbers of COVID-19 infections have come under question.

While the coronavirus continues an uncontrolled run across Europe and North America, China controlled it well by March, according to data released by the Communist govt in the country. Recently, it had emerged that number asymptomatic Coronavirus positive persons were not included the official data of the pandemic released by the govt. And now an analysis by The Economist shows that the Coronavirus data of China has close relations with political decision in the country.

According to the analysis done by The Economist, two peculiar trends are seen in the Chinese Coronavirus data. First, the data are highly volatile, across different provinces, the numbers of positive cases jump abruptly one day and then come down heavily the next day. Although such irregularity is seen with most countries, it is seen more frequently in the case of China. This suggests on some days, positive cases which were not reported earlier were added to the official data, and those days saw a huge jump in the number of cases.

On 24th March, Chinese Prime Minister Li Keqiang had warned local officials not to hide new coronavirus cases, after no cases of local transmission was reported in the country for several days. Li, the country’s second-in-command, urged local governments Monday to “seek truth from facts” and be “open and transparent” in releasing information on the epidemic. This proves that local authorities were under-reporting new cases of Covid-19, and they were forced to add those numbers on the orders of the central leadership later.

The second trend noticed by the Economist study shows that each incident of spike in new cases is related to some important political decisions in the respective provinces. For example, the Hubei province, the epicentre of the pandemic, saw 27% increase in new infections on 9 February, and the rise was 20% and 22% on the next two days. But on 12th February, the number of new Covid-19 cases in the province went up by a whopping 742%. Although Chinese govt had said that this had happened due to revisions to the government’s methodology for counting cases, those revisions were made a week earlier. More importantly the spike in cases on 12th February happened just a day after the Communist party chiefs of Hubei province and Wuhan city were sacked.

Similar trend was seen in other regions also. On January 27th officials in Zhejiang province announced the opening of 335 clinics and a 1,000-bed hospital to accommodate a surge of Covid-19 patients. The next day, new cases nearly tripled to 123, before declining sharply in the next few days. The new cases in Shandong province saw a spike on 20 February after the chief of the provincial justice department was sacked, and they came back to previous levels.

While most incidents of sharp rise in new cases happened just after important decisions were made in the respective regions, on one day this happened on national level. On February 3rd, almost every Coronavirus-hit province saw a massive jump in the number of new cases. On the very same day, Chinese premier Xi Jinping had asked the authorities battling the virus to “face up to existing problems” and “release authoritative information in a timely manner”.

These co-incidences suggest that all is not well with the Coronavirus data released by China, just as their information on the virus was not correct, there is doubt over their data also.

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OpIndia Staffhttps://www.opindia.com
Staff reporter at OpIndia

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