A Comparison of the Leading Indicators of COVID-19 Deceased Rates in New Delhi, India during the First Quarter of the Novel Coronavirus Pandemic in 2020

This paper analyzes the 5-, 14- and 21-day cumulative positivity rate vis-à-vis the COVID-19 deceased rate of each time period for the first four months of COVID-19 from April 2020 to September 2020 in New Delhi, India with the intention of getting insight into the relationship between the two and to evaluate the leading indicators of COVID-19 deceased rates using MATLAB programming language.Most news reports and media typically quote the 14-day positivity rate to know where Delhi is on the “curve” of corona virus COVID-19 cases. The 5-day positivity rate is marginally to slightly positively correlated with the deceased rate at +0.02 whereas the 14-day positivity rate has a negative correlation of -0.06 with the deceased rate. The higher negative correlation of the 21-day positivity rate of –0.12 with the deceased rate indicates that there are more recoveries over the subsequent 7-day period after 14 days which is also in-line with medical and health professionals who advocate a 14-day quarantine to recover from the virus if the population has tested positive. Statistical correlation and regression Analysis of Variants (ANOVA) analysis indicates that the 21-day positivity rate is negatively correlated to the deceased rate at -0.12 with an R2 (coefficient of determination) of 1.3% compared to correlation coefficients of –0.06 and +0.02 and R2 of 0.28% and 0.03% respectively for the 14-day and 5-day cumulative positivity rates.The 21-day rate is most relevant leading indicator in comparison with the 14-day and 5-day rate and is statistically significant at the 75% Confidence Interval. This implies a Regression equation of Deceased rate over 21 days = 0.0248 - 6.66% x 21 Day Positivity Rate + ErrorThis implies that corona hotspots should ideally quarantine for a longer 21-day period rather than the 14-day period typically advocated especially in areas where there is a stress on the healthcare facilities to avoid burdening the hospitals for non-critical cases.The paper suggests further avenues to explore this relationship including a split of the type of tests namely RT-PCR vs RAT antigen tests as RAT yields a higher 53% of false negatives vis-a-vis the COVID-19 deceased rate and an analysis over a longer time period of say 12 months to analyze the relationship of the delta (change) of the positivity rate and the delta of the deceased rate with statistical significance testing at the 95% and 99% confidence intervals. Longer period analysis would give further insight into leading indicators of rising and decreasing infections which could be used by government and health practitioners so as to proactively increase number of vaccines, health practitioners and hospital ICU beds in advance of a surge in infections and deceased rates