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India Currents gave me a voice in days I was very lost. Having my articles selected for publishing was very validating – Shailaja Dixit, Narika, Fremont
To be sure of the safety and efficacy of Covid-19 screening technology that he was considering for his employees, Tech Mahindra CEO CP Gurnani, suggested testing it on himself and his household members. That decision may have saved him and his family from having to be admitted to hospital —as actors Amitabh and Abhishek Bachchan were last week. As it turned out, everyone in the house received a clean bill of health, except the two sons of his cook who were diagnosed as high risk.
As the Bachchans too must have done, Gurnani had had his domestic staff take all necessary precautions, remaining distant and wearing masks. His cook’s sons did not show any visible sign of infection, yet were potential Covid-19 carriers.
The fact is that the testing techniques in common use are inadequate, and social distancing isn’t always possible. RT-PCR (reverse transcription polymerase chain reaction) tests have ‘false negative’ rates of 20-67%, depending on when they are taken. Also, temperature screening and contact tracing fail to identify the presymptomatic spreaders who, according to mathematical modeling, could be responsible for half of the infections. When Delhi health minister Satyendar Jain showed symptoms, his first RT-PCR results came back negative. But they were positive the very next day.
The technology and techniques I had persuaded Gurnani and Tech Mahindra to pilot — and that I had a hand in developing — are based on understanding an individual’s risk and performing monthly testing. The reality is that even though Covid-19 can be devastating for a few, not everyone who gets infected will have serious symptoms. We can identify the people at high risk with reasonable accuracy based on studies from around the world and data from India. And we can give them special treatment.
For example, it is well established that men above 65, whose health is chronically compromised by diabetes, cardiovascular disease, or obesity, are at higher risk of severe outcomes. Further, severity can be predicted by a number of tests, including those for hypertension, diabetes, and obesity, and measures of lactate dehydrogenase (LDH) and D-dimer.
Businesses in the US have considered offering these types of tests. But the costs and logistics of doing so are usually prohibitive, with the most basic tests costing more than $100 apiece, and requiring the shipment of samples to labs. A single comprehensive screening for an individual could cost over $1,000, and is usually not covered by insurance plans. It can take days to get basic test results.
This is where India has an advantage over the West: it has developed screening devices, such as HealthCube, which can conduct a range of biochemical and physiological tests for a tiny fraction of the US cost. These include 12-lead electrocardiograms (ECG), tests for blood pressure, oxygen saturation, blood glucose, hemoglobin and cholesterol, and rapid diagnostic tests for infectious diseases.
With HealthCube, an entire regimen of tests, including a test for Covid-19 antibodies and severity markers, can be performed for less than Rs1,000 within minutes. The technology has received Europe’s CE certification.
The Covid-19 risk screening program underway at Tech Mahindra on the HealthCube platform uses patient risk factors — age, gender, medical conditions, potential exposure, recent travel or being in a crowded place, public health data, aggregations from previous screenings, patient symptoms, etc — to compute a risk score for patients. Those at high risk are checked for markers, such as D-dimer and troponin, which are elevated in those who develop the severe disease (which indicate heart ailments). These tests are followed up by teleconsultations and further testing, as appropriate.
With more data and testing, the artificial intelligence (AI) algorithms become increasingly accurate, and people are given an individualized screening and testing protocol based on their risk factors, rather than being treated like machines that need temperature checks.
Antibody tests have been controversial largely because the first generation of tests performed worldwide were mostly from China and were low quality and defective. There have also been doubts about whether all Covid-19 patients develop antibodies and, even if they do, how long the immunity lasts.
The newer generations of tests, made outside China, are highly accurate. Swiss pharma giant Roche, for example, claims that 14 days after infection, its test can detect antibodies with 99.8% specificity and 100% sensitivity. HealthCube claims that its India-made tests have 98% specificity and 96% sensitivity. These are both a huge leap from the 5.4% accuracy of the tests that China first sold to India.
There is substantial evidence that within 19 days after symptom onset, 100% of patients test positive for Covid-19 antibodies. And as Harvard epidemiologist Marc Lipsitch explained in the New York Times, ‘After being infected with SARS-CoV-2, most individuals will have an immune response, some better than others. That response, it may be assumed, will offer some protection over the medium term — at least a year — and then its effectiveness might decline.’ Even half a year will buy us time to understand and develop better approaches to prevention and treatment — and administer vaccines to those at high risk.
Gurnani told me that his personal experience, and the testing Tech Mahindra has conducted on a few hundred employees, have convinced him to offer the full health screening to the entire India Tech Mahindra employee base — including third-party employees, who typically can’t afford the test and are the most vulnerable because they stay in crowded places. He says that he puts his employees’ health above any business needs and cannot allow even one person to be at unnecessary risk.
Gurnani’s ambition is to show India — and the world — how to safely and sensibly open businesses and economies.
Vivek Wadhwa is a distinguished fellow and professor, Carnegie Mellon University’s College of Engineering, Silicon Valley.
This article was republished with permission from the author and can be originally found here.