New study claims coronavirus can spread rapidly at home

WION Web Team
New Delhi, Delhi, India Published: Jun 18, 2020, 05:03 PM(IST)

File photo Photograph:( Reuters )

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The study found that while the average patient had just a 2.4 per cent likeliness to infect someone they did not live with, that figure rose to 17.1 per cent, among cohabitants

A new study has claimed that the likelihood of novel coronavirus infecting the people who live with the patient in his home is much more than to a patient who live with other people. 

Researchers based in China and the US used data of 350 COVID-19 patients and about 2,000 of their close contacts in the city of Guangzhou, China and evaluated the virus' "secondary attack rate", the probability that a patient transmits the disease to someone else. 

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The study found that while the average patient had just a 2.4 per cent likeliness to infect someone they did not live with, that figure rose to 17.1 per cent, among cohabitants. 

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The results of the study also suggested that the probability of household infection was highest among people who are in their 60s, and lowest among under-20s. 

The total probability of infecting a kin or live-in partner with COVID-19 is twice as high if compared with SARS, and three times high if compared with MERS. 

Surprisingly, the research also found out that asymptomatic people have a higher probability, 39 per cent to spread the virus to the people who live with him as compared to people who have coronavirus symptoms. 

"Although the effect of case isolation seems moderate, the high infectivity of the virus during the incubation period suggests quarantine of asymptomatic contacts could have prevented more onward transmissions," Qin-Long Jing from the Guangzhou Center for Disease Control and Prevention said. 

The researchers, who used data collated in January and February but have been updated to reflect the latest developments, claimed that their findings could help a great deal in helping reduce the infections as the pandemic progresses. 

(With AFP inputs)

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