There have been widespread allegations that Covid deaths have been over-estimated in the second wave of the pandemic in India. Data from certain towns has been produced, showing under estimation by a factor of 10 to 100 times. This note compares the two waves and uses the difference to put an upper limit on the underestimation.
Scholar from across the World have argued that COVID cases and deaths have been underestimated across the World and that the degree of underestimation is greater in developing countries than in developed counties. This note does not address this broader issues but focuses on the potential increase in the degree of under-estimation during the second wave relative to the first wave.
Figure 1, plots the cumulative cases and deaths, with the cases on the left hand scale and deaths on the right-hand scale. The curve of cases is lower than the curve of deaths in the first wave, but vice versa in the second wave. More under-counting during the second wave, is a possible explanation for this change in pattern.
Figure: India COVID cases and Deaths
We assume that the first wave ended on the date at which the rate of growth of cases reached a trough on 14th February 2021. For simplicity, the cases and deaths up to February 15th are attributed to the first wave and after that to the second wave. The data is presented in columns 4 & 5 of the table. We then calculate the Test positivity rate as the ratio of Cases to Tests and the fatality rate as the ratio of deaths to cases. These are shown in columns 2 and 3. It is clear that the test positivity rate in the second wave(12.7%) is more than double that in the first wave (5.3%). In contrast the fatality rate in the first wave (>1.4%) is about 1.5 times that in the second wave. This differential Is used to estimate the potential under-counting. On this basis the total number of deaths as of 26th May is estimated to b 2.4 lakhs relative to the official estimate of 1.6 lakhs (columns 6 & 5).
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