On Containment Plan Amid COVID-19 in Red Zone Districts of India: Using Clinical Life Table and Cure Fraction Model
Background and Objective: Ministry of Health and Family Welfare, Government of India took many measures to arrest the spread of COVID-19 disease. This research is intended to shed light on number of confirmed cases with respect to population density of the affected districts, to study the proportion of positives among total sample tested, to construct clinical life table of general population w.r.t. number of daily positive cases and to estimate the long-term survivors among general population.
Materials and Methods: Simple scatter plot has been used to see relation between population density and number of cases in different districts of India, cluster analysis technique is used for making cluster of Districts having similar features. Clinical life table is prepared for general population of affected Districts, and mixture & non-mixture cure fraction models used to estimate the proportion of long-term survivors (disease free survival) of general population.
Result: Median daily proportion of positives are found to be below 0.05. In 79 identified hot spot Districts average population is very high (36.29 lakhs) with population density of 3404 per square kilometre. Even among those Districts there are huge inter cluster differences w.r.t. number of cases and population density. Clinical life table is constructed for general population of 429 affected Districts, increasing pattern in hazard is found even though study period is small. Long term survivors of disease is simulated and found to be 99.812%.
Conclusion: Government ought to make cluster of Districts among red zone Districts, clustering should be based on number of cases and population density. Different containment strategy may be prepared for each cluster of Districts.
How to cite this article:
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