Covid-19: To get an accurate estimate of the spread, India must ensure random community testing
In the fight against the coronavirus pandemic (Covid-19), policymakers are fighting blind, because we do not know the extent of the infections in the population or the mortality rate due to it. It is possible to track the number of deaths, the cases that required hospitalisation and those who have tested positive for the virus at hospitals, but those numbers present a limited picture of the pandemic. Our response to this crisis depends critically on figuring out how fast the disease is spreading outside of hospitals, in the community, and how likely the virus is to kill individuals who have been infected. The only way to obtain this information is through random testing in the population.
Existing methods of measuring the disease’s prevalence are likely to give inaccurate results. India, like most countries, has a shortage of testing kits. As a result, it prioritises the testing of the individuals who have severe symptoms and show up at the hospital. It misses those who have symptoms, but not severe enough to go to the hospital, and those who are asymptomatic — lack of cough, fever or trouble in breathing — but, nonetheless, are carriers who can infect others.
There are good reasons to think that many individuals are asymptomatic, which means that true caseload is under-measured. For example, the city of Vò (Italy) tested all its inhabitants, and found as many as 50% of individuals were asymptomatic. On the Diamond Princess cruise ship, 18% of the infected population showed no symptoms, while in Iceland, 50% of those who tested positive were asymptomatic. A recently released report from Maharashtra suggests that 85% of cases in the state were asymptomatic, similar to the recent findings from China, published in The British Medical Journal. They suggest that we will never be able to measure the true prevalence of Covid-19 by testing only high-risk populations.
We lack the essential information to fight this disease because of such data limitations. Harvard economist James Stock has identified the lack of accurate infection rates as the central information gap behind efforts to combat the coronavirus. Consider the true mortality rate due to Covid-19. This is calculated by taking the number of deaths from the virus and dividing by the total number of infections it has caused. For any level of deaths from Covid-19, the higher the infection rate, the lower is the death rate. The mortality rate is, in turn, essential to calibrate our response. If the mortality rate from the virus is very high, it calls for doubling down on suppression methods to avoid mass deaths. A lower mortality rate does not mean the situation is any less troubling—but it tells us that the disease is more prevalent in the population than currently thought, and it demands mitigation rather than suppression approach in response.
While we have estimates on the number of deaths, we are flying blind in estimating the denominator of the fatality rate. If, in fact, many people are walking around with Covid-19 and perhaps do not even know of their infection status — as some doctors suggest — we need to adopt a very different approach to address this crisis. At the time of writing, India has 4,067 coronavirus cases and 109 deaths, implying a 2.7% mortality rate, without considering future mortality of the currently sick. If the fraction of asymptomatic cases was 20%, this would imply a true fatality rate of 2.1%. However, if it were more like 80%, the true fatality rate would be considerably lower at 0.5%. Where India is on this mortality spectrum will greatly influence how we think about and combat this disease – and that’s why estimating this number accurately is an urgent priority.
Measuring infections accurately will also allow for targeted efforts to combat the spread of the disease. Otherwise, we will not know how many hospital beds, ventilators and doctors we will need in different areas in the coming weeks. We cannot determine whether the lockdown has been effective, how long it should continue, or if certain places can safely be released from the lockdown without sparking an outbreak.
To its credit, the Indian Council for Medical Research (ICMR), at the very start of the pandemic, tested 826 patients who were admitted in hospitals with severe acute respiratory illness but no travel history. This was a valuable effort, showing that, at the early stages of the pandemic, the coronavirus had not yet spread through the community in India. The situation has since changed. There is now a wealth of evidence across countries, including in India itself, that Covid-19 can be found not just in those with severe symptoms, but also among individuals who display little or no symptoms.
While ICMR has just expanded its testing criteria beyond symptomatic cases to include asymptomatic individuals with prior contacts with confirmed cases and antibody testing in hotspots, these efforts still fall short of true random testing across the entire country.
The only way to determine the true mortality and infection rates is random testing in the community — identify individuals randomly from the population, rather than from in and around hospitals and hotspots, and test them in the field so we can determine the precise prevalence. Closing this information gap will be critical to making well-informed decisions on how best to combat this disease. Countries like Austria and Germany have begun random testing of the population. India must do so immediately, either nationally, or, if the capacity is a constraint, at least sub-nationally.
Arpit Gupta is an assistant professor of finance at NYU Stern School of Business. Anup Malani is a professor at the University of Chicago Law School and Pritzker School of Medicine, and Reuben Abraham is CEO of IDFC Institute, Mumbai
The views expressed are personal