Like many countries, India has struggled to grasp the extent to which its population is affected by the COVID-19 pandemic. The country’s testing efforts have largely focused on at-risk individuals, including those with influenza-like symptoms, people who have had contact with an individual testing positive for COVID-19, and health care professionals.
This approach to testing does not give health officials and researchers an accurate representation of how many people in India are actually infected, according to a Lancet Global Health commentary authored by S V Subramanian, professor of population health and geography at Harvard T.H. Chan School of Public Health.
Subramanian suggested that in the absence of universal testing, India should leverage the infrastructure of its existing National Family Health Survey (NFHS) to randomly test a cross-section of individuals that is more representative of India’s population, as opposed to focusing only on at-risk individuals. Subramanian noted that the country previously took a similar approach to better understand the prevalence of HIV in India.
“For more than 25 years the NFHS has served India well, providing reliable estimates of various population, health, and nutrition indicators,” Subramanian wrote. “Layering a COVID-19- focused data-collection effort onto the NFHS infrastructure would keep operational costs low, with the major expense being laboratory costs for testing samples.”
Read The Lancet Global Health article: Use of the Demographic and Health Survey framework as a population surveillance strategy for COVID-19