“Testing for Covid-19 is mainly being done among at-risk individuals (e.g. those with influenza-like symptoms, people who have had contact with an individual testing positive for Covid-19, healthcare professionals, or those with a travel history to an affected region),1 thus an accurate value for how many individuals are truly infected is not known. Since at-risk individuals are not representative of the general population, it is impossible to obtain the true prevalence of Covid-19 in the population. Yet, establishing this value is vital to understand the morbidity and mortality risk in the population.
“A random-sample-based population surveillance framework is urgently needed. We propose using the well-established Demographic and Health Survey (DHS) framework as a solution to ascertain the true prevalence of Covid-19. We use as an example the National Family Health Survey (NFHS), India’s version of the DHS that is led by the International Institute of Population Sciences under the Ministry of Health and Family Welfare.
“The NFHS has state-of-the-art infrastructure with a ready sampling framework. For more than 25 years the NFHS has served India well, providing reliable estimates of various population, health, and nutrition indicators. 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…”
SOURCE: Lancet Global Health, by S V Subramanian, K S James, 29 April 2020