Statistical Model for COVID-19 in Different Waves of South Indian States.

ABSTRACT

Background: COVID-19 has resurfaced in India, where it is rapidly spreading and wreaking havoc in rural areas. An effort has been undertaken to assess the levels and patterns of COVID-19 active cases in the southern states of India. To trace and reason out anomalous trends in the COVID-19 curve so that particular actions such as lockdown, de-lockdown, and healthcare improvisation can be implemented at the appropriate time. Methods: The data has retrieved from the government websites through a platform called Kaggle. The entire duration of COVID - 19 were classified into three compartments Phase one, Resting phase, and Phase two. The Case Fatality Rate in south Indian states was analysed corresponding to the phases, and a compartmental model for COVID-19 dynamics in the region was proposed. Results: The quadratic regression model was fitted and found to be the best model for the phases except for the resting phase. Phase one was comparatively less fitted when compared to phase two. In most of the south Indian states, the active cases in phase one were almost more than four times that of phase two. The average CFR value in phase one was lower than the subsequent phase in all of the southern Indian states. In phase one, Telangana, Karnataka, and Tamil Nadu had the highest CFR (4.77,4.22, and 3.71, respectively), whereas Lakshadweep and Kerala had the lowest CFR (0.27 and 0.71, respectively). In the resting phase, the CFR stabilized in all states and reached a value between 0.2 to 2. The trend was similar in phase two also, CFR of Lakshadweep, Kerala, Telangana, and Andhra Pradesh (0.143, 0.416,0.553, 0.803) were very low, while the CFR of Andaman and Nicobar Islands, Karnataka, and Tamil Nadu (1.237, 1.306, 1.490) were very high. Conclusion: The first and second phases of the COVID-19 virus in south Indian states had different characteristics. A District-level working group with the autonomy to respond to rapidly changing local situations must be empowered to tackle the next phase. The upcoming phases could be more peaked in less time and could be a hectic situation for the health care system.