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New study finds gaps in India's COVID-19 testing data collection

Last Updated : 31 May 2020, 08:43 IST
Last Updated : 31 May 2020, 08:43 IST
Last Updated : 31 May 2020, 08:43 IST
Last Updated : 31 May 2020, 08:43 IST

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Even as India ramps up its COVID-19 testing regimen, a study has discovered gaps in how the testing teams collect data. These shortfalls are said to be limiting efforts to draw interpretations about how the pandemic is progressing.

The study discovered that certain critically important data such as “patient category” or “date of symptom onset” is missing from many case entries. The study utilized anonymized data from January 22 to April 30, during which 1,021,518 people were tested for the SARS-Cov-2 virus.

“It is safe to say that the proportion of missing entries is high. These could be for two reasons. One, is that the kinds of cases we are getting no long fit into the six patient categories currently in existence, or second, that the data is not being properly entered into the system by data entry personnel,” explained Dr Tarun Bhatnagar, of the ICMR School of Public Health and one of the authors of the study.

Statistically, the study found that for every 100 symptomatic contacts tested, 10 came back as positive. Among a similar sample of asymptomatic contacts, five would test positive. Among SARI cases, six out of every 100 cases test positive, the study discovered.
Statistically, the study found that for every 100 symptomatic contacts tested, 10 came back as positive. Among a similar sample of asymptomatic contacts, five would test positive. Among SARI cases, six out of every 100 cases test positive, the study discovered.

The six existing categories are - symptomatic international travellers, symptomatic contacts, asymptomatic contacts, symptomatic healthcare workers, hospitalized SARI cases, asymptomatic healthcare workers in contact with confirmed cases without adequate protection and ILI cases in hotspots.

Remarkably, 5,78,816 people (56.7%) of those tested for COVID-19 in India, do not fall into the above testing categories. In Karnataka, this percentage is 50.86% translating to 24,500 people who cannot be categorized.

The inability to place everyone who is tested into a category makes it difficult to analyse how the disease is spreading among those who came into contact with an infected person and among those who do not have a known contact history.

“To be clear, the data accumulated is massive, we have the information of more than a million people, but the gaps in information creates difficulties when we want to look to how the disease is being transmitted. The mode of transmission in a large number of cases are muddled,” Dr Bhatnagar said.

Other Findings

The study also discovered that symptomatic contacts of confirmed COVID-19 cases account for the largest group to test positive (10.3%), followed by those with Severe Acute Respiratory Infection (SARI) (6.1%).

However, the largest categorized group to be tested were asymptomatic contacts (two lakh individuals) of coronavirus-positive cases, out of which 5.1% tested positive. Those with an international travel history had a positivity rate of 3%, while tested symptomatic healthcare workers had a positivity rate of 4.6%.

It also turns out that states vary with regard to the number of positive case contacts traced, which is an indicator of surveillance measures. Tripura led the pack with 328 contacts generated per positive case, while Jharkhand was at the bottom of the table with 1.3 contacts per positive case.

It also turns out that states vary with regard to the number of positive case contacts traced, which is an indicator of surveillance measures. Tripura led the pack with 328 contacts generated per positive case, while Jharkhand was at the bottom of the table with 1.3 contacts per positive case.

The study also discovered that men and adults are more prone to catching the disease than other age or gender demographics. “Immunological studies are required to tell us why this is so,” Dr Bhatnagar said.

The study was published in the Indian Journal of Medical Research (IJMR).

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Published 31 May 2020, 06:52 IST

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