RESUMEN
Background: In this paper, an attempt has been made to estimate the Case Fatality Ratio (CFR) for coronavirus disease of India and a few selected countries. And also, it highlighted the pros and cons of obtaining crude and adjusted CFR of COVID-19 pandemic. Material(s) and Method(s): Data extracted from the WHO situation report and the University of Oxford website have been used for this analysis. The CFR and its 95% confidence interval were computed, trend and bar plot was used for graphical representation. Result(s): The worldwide crude CFR stands 6.73% (95% CI 6.69 to 6.76) based on 21, 83, 877 confirmed and 1,46,872 death cases(as on 17th April, 2020). Belgium was the highest CFR at 13.95% as compared to others. However, India's CFR was found to be around 3.26% (as on 17th April, 2020). Conclusion(s): In conclusion, the estimation and interpretation of CFR are critical in response to ongoing COVID-19. The initial CFR estimates are subject to change, still, it is useful for healthcare planning over the coming months. Moreover, the precise and robust estimates of CFR will be available only at the end of the epidemic.Copyright © 2021 Bentham Science Publishers.
RESUMEN
The novel coronavirus disease (COVID-19) has shaken the entire world in its devastating annihilation of humanity. The alarming increase in number of confirmed COVID cases in India requires an urgent step to monitor and control this spread. Thus, it is inevitable to develop a model which can predict future confirmed and death cases. Time series models are significant in predicting the impact of the COVID-19 outbreak. In this paper we have developed an Auto Regressive Integrated Moving Average (ARIMA) model to predict the number of COVID 19 cases for India and Odisha. The model prediction suggests that an increasing trend would be continuing for both Odisha and India as whole for next two weeks. The forecasted values are in good agreement with actual cases in both the scenario. These findings would be useful for government in formulating policy related to health care systems so that the system and medical professions can better prepared to combat the pandemic.