However, such estimates of R0 are subject to error, due to the difficulty in choosing a “suitable” model for a new and unknown disease, and also due to the inadequate number of tests, leading to lots of asymptomatic patients remaining undetected. Then, again, the 95 per cent confidence interval of the all-India pre-lockdown R0 is (2.86, 3.78). Thus, even if the model and data are unsatisfactory, there is a 5 per cent chance that the true value will be outside that interval. And there might be a small yet clear 1-2 per cent chance that the actual R0 is too high, but the model and data have failed to estimate it. It is the standard statistical interpretation of any estimate. Consequently, there may always be towns or districts where the epidemic will erupt alarmingly, even if the estimated relevant R0 seems under control.
Let’s examine the cases of some states. Delhi’s estimated pre-lockdown R0 was quite high. However, in the four lockdown stages it was 2, 1.60, 1.51, and 1.74, respectively. Thus, a lockdown can reduce R0, although it increased a bit in lockdown 4.0. In Tamil Nadu, the pre-lockdown R0 (4.20) was surpassed in lockdown 1.0 (8.12). However, it decreased thereafter; the next three R0 values are: 1.82, 1.87, and 1.44. Thus, it seems that the lockdown was quite helpful for Tamil Nadu. The pre-lockdown R0 in Maharashtra was 1.71, and it was 1.76, 1.44, 1.42, and 2.39 in the four stages of lockdown — it’s quite high even at the end of lockdown 4.0. However, it could possibly be much more if there were no lockdown. At the end of lockdown 4.0, R0 for Tamil Nadu is very similar to the national value. While R0 for Goa (1.40) is less than the national value, the values for West Bengal (1.70), Rajasthan (1.63), Karnataka (1.55), and Punjab (1.82) are all above the national average.
Thus, it is clear that R0 values in some states were reasonably under control during the lockdown period, and the values are alarmingly high in some states. Similar variations will persist even if we look at the data for different towns and districts within a state. Importantly, as per present trends, there is no sign that the outbreak will become extinct soon. R0 values in the unlocking period have not stabilised yet. They may, however, increase as the unlocking rolls on — the “curve” that had flattened due to the prolonged lockdown may become steep again, if we do not adhere to health guidelines. There is a trade-off between health and the economy everywhere in the world. Thus, while unlocking, it would be wise to look at the variations within the country, and act accordingly. The Netherlands termed their lockdown an “intelligent lockdown”; let us “unlock” intelligently.
The writer is professor of statistics, Indian Statistical Institute, Kolkata