The swiftly growing and overwhelming epidemic in India has intensified the question: What will the trend and magnitude of impact of the novel coronavirus disease 2019 (COVID-19) be in India in the near future? To answer the present question, the study requires ample historical data to make an accurate forecast of the blowout of expected confirmed cases. All at once, no prediction can be certain as the past seldom reiterates itself in the future likewise. Besides, forecasts are influenced by a number of factors like reliability of the data and psychological factors like perception and reaction of the people to the hazards arising from the epidemic. The present study presents a simple but powerful and objective, that is, autoregressive integrated moving average (ARIMA) approach, to analyse the temporal dynamics of the COVID-19 outbreak in India in the time window 30 January 2020 to 16 September 2020 and to predict the final size and trend of the epidemic over the period after 16 September 2020 with Indian epidemiological data at national and state levels. With the assumption that the data that have been used are reliable and that the future will continue to track the same outline as in the past, underlying forecasts based on ARIMA model suggest an unending increase in the number of confirmed COVID-19 cases in India in the near future. The present article suggests varying epidemic’s inflection point and final size for underlying states and for the mainland, India. The final size at national level is expected to reach 25,669,294 in the next 230 days, with infection point that can be expected to be projected only on 23 April 2021. The study has enormous potential to plan and make decisions to control the further spread of epidemic in India and provides objective forecasts for the confirmed cases of COVID-19 in the coming days corresponding to the respective COVID periods of the underlying regions.

印度迅速增长和压倒性的流行病加剧了一个问题：在不久的将来，印度新型冠状病毒病2019（COVID-19）的影响趋势和程度将是什么？为了回答当前的问题，该研究需要大量的历史数据来对预期的确诊病例进行准确的预测。总而言之，无法确定任何预测，因为过去很少会在未来重申自己。此外，预测还受许多因素的影响，例如数据的可靠性和心理因素，例如人们对流行病危害的感知和反应。本研究提出了一种简单但功能强大且客观的方法，即自回归综合移动平均值（ARIMA）方法，分析印度2020年1月30日至2020年9月16日的时间窗内COVID-19暴发的时间动态，并利用印度国家和州的流行病学数据预测2020年9月16日以后该流行病的最终规模和趋势水平。假设使用的数据可靠，并且未来将继续跟踪与过去相同的轮廓，则基于ARIMA模型的基本预测表明，印度确诊的COVID-19病例数在不断增加。不久的将来。本文建议基础州和印度大陆的流行病拐点和最终规模各不相同。预计在接下来的230天内，国家一级的最终规模将达到25,669,294，