Nearly 78% of COVID-19 patients in India are under 50: IDSP data

60% have at least one co-morbidity, says govt. body

In India, 60% of COVID-19 patients had at least one co-morbidity and nearly 78% were under 50, says data from the Integrated Disease Surveillance Programme (IDSP), a Health Ministry body that’s tasked with monitoring disease outbreaks across the country.

The data is only a fraction — less than 1,00,000 — of the confirmed positive cases that today exceeds over 6,50,000, but is based on hospital data and offers glimpses into the unique characteristics of the spread of the disease.

Limited role

For instance, while co-morbidities are known to be a major risk factor for death, well-known risk factors — hypertension and diabetes — appeared to play a limited role as far as testing positive for the disease is concerned. Only 8% of the 16,155, whose data was publicised by the IDSP, were diabetic and 9% were hypertensive.

Previous studies have shown that the overall prevalence of hypertension was 29% and of diabetes around 11%.

Nearly 30% of those whose co-morbidities were publicised were categorised as ‘others’.

Experts say there were a wide range of co-morbidities among those who tested positive and frequently it was difficult to tease out the contribution of the virus in worsening health. “Cancers, a history of a bypass, hepatic disorders, kidney ailments come in the category of others,” said Sujeet Kumar Singh, Director, National Centre for Disease Control. The IDSP is a unit of NCDC.

“We now have enough cases to call for a deeper analysis of the peculiar characteristics of the pandemic. It isn’t enough to rely on Western or international data alone to understand Indian disease peculiarities.”

Laying out the symptoms recorded by hospitals of 19,813 patients, fever was the dominant symptom but noted only in 26% of the cases; cough in 19%.

A significant 21% were slotted as “other symptoms”, meaning they displayed conditions beyond sore throat, diarrhoea, pain, headache and vomiting. “This is surveillance data from hospitals. Many times they lack necessary detail but going ahead we hope that at least in major clinical centres, more detailed case histories are presented.”

The virus would affect populations differently and “differences in strains” did play a major role in explaining the severity and spread, Mr. Singh said. Previous studies have found that as of early June, there were at least 11 sub-types of SARS-CoV-2, six of which were identified in India.

Patient demography

When the demographics of nearly 83,000 patients were analysed, 37% were identified as urban and only 13% as rural. The rest were categorised as “not specified”.

Mr. Singh said migration and different definitions of classification by the authorities of a person’s residence status were a reason for the large number of ‘unspecified’.

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