Estimation of Undetected Covid-19 Infections in India

Mukhopadhyay, Siuli; Chakraborty, Debraj

Background and Objectives: While the number of detected COVID-19 infections are widely available, an understanding of the extent of undetected COVID- 19 cases is urgently needed for an effective tackling of the pandemic and as a guide to lifting the lockdown. The aim of this work is to estimate and predict the true number of COVID-19 (detected and undetected) infections in India for short to medium forecast horizons. In particular, using publicly available COVID-19 infection data upto 16th April 2020, we predict the true number of infections in India during and upto the end of the formal lockdown period (21st April 2020). Methods: The high death rate observed in most COVID-19 hit countries is suspected to be a function of the undetected infections existing in the population. An estimate of the age weighted infection fatality rate (IFR) of the disease of 0.41%, specifically calculated by taking into account the age structure of Indian population, is already available in the literature. In addition, the recorded case fatality rate (CFR= 0.70%) of Kerala, the only state in India to report single digit new infections over the second week of April, is used as a second estimate of the IFR. These estimates are used to formulate a relationship between deaths recorded and the true number of infections. The estimated undetected and detected cases time series based on these two IFR estimates are then used to fit a discrete time multivariate infection model to predict the total infections at the end of the formal lockdown period. Results: In two consecutive fortnights during the lockdown, it was noted that the rise in detected infections has decreased by 2.7 times. For an IFR of 0.41%, the rise in undetected infections decreased by 3.2 times and the predicted number of total infections in India is 3.14 lakhs. While for an IFR of 0.70%, the rise in undetected cases decreased by 3.3 times and the total number of infections predicted on 21st April is 1.75 lakhs. Interpretation and Conclusions: The behaviour of the undetected cases over time effectively illustrates the effects of lockdown and increased testing. From our estimates, it is found that the lockdown has brought down the undetected to detected cases ratio, and has consequently dampened the increase in the number of total cases. However, even though the rate of rise in total infections has fallen, the lifting of the lockdown should be done keeping in mind that 1.75 to 3 lakhs undetected cases will already exist in the population on 21st April.