A multistate ecological study comparing evolution of cumulative cases (trends) in top eight COVID-19 hit Indian states with regression modeling

Abstract

Background: The global pandemic of coronavirus disease – 2019 (COVID-19) has wrecked the very fabric of mankind putting its survival at stake. The prior knowledge of trends of cumulative cases helps in management of disease epidemic by optimized allocation of logistics and human resources. Materials and Methods: An ecological study was undertaken to compare the standardized trends of cumulative cases of top eight highly COVID-19 affected states of India with linear regression modeling. The data were sourced from Kaggle repository and Unique Identification Authority of India. The coefficients of regression of linear regression models of all the eight states were compared using analysis of covariance (ANCOVA). Results: It was observed that evolution of COVID-19 was the highest in the state of Gujarat (b = 0.186, P < 0.001) followed by Madhya Pradesh (b = 0.166, P < 0.001), Maharashtra (b = 0.159, P < 0.001), Delhi (b = 0.156, P = 0.02), Rajasthan (b = 0.136, P = 0.98), Uttar Pradesh (b = 0.117, P < 0.001), Tamil Nadu (b = 0.091, P < 0.001), and Andhra Pradesh (b = 0.076, P < 0.001) respectively. Conclusion: It is seen that ranking of states on the basis of trends of evolution and the absolute number of cumulative cases are different. The trends of evolution assist public health authorities and governmental agencies in providing right picture of evolution and help in decision making process during management of epidemic. The following core competencies are addressed in this article: Medical knowledge, Practice-based learning and improvement, Systems-based practice.