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Predicting the COVID-19 Cases in India

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Intelligent Communication, Control and Devices

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1341))

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Abstract

COVID-19 has challenged the scientific community to its core and researchers, government and healthcare workers are working persistently to fight the pandemic. Data driven prediction for disease spread is a vital information which assists policymakers to plan their moves against the pandemic. In this paper, we have compared the performance of the two most important time-series forecasting methods: Prophet and ARIMA for predicting the COVID-19 cases in India, considering the effect of disease spread imposed by unlocking regulation of the government. The performance parameters comparison shows that predictions obtained from Prophet are more accurate and may assist the government agencies and health care professionals for effective planning in post lockdown. The prediction model also includes the constraints and factors exhibited by the phased lockdown and unlocked strategies followed by the government of India, the prediction models designed in the initial days of April–July 2020 did not give the accurate predictions for September–October as there had been major changes in the public movement-related policies by the government. The current prediction model holds true as the public movement in India is almost back to normal (excluding the operation of educational institutes of India).

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun, India

    Arpit Jain & Abhinav Sharma

  2. Department of Applied Mathematics and Computational Sciences, PSG College of Technology, Coimbatore, India

    S. Nitisha Bharathi

Authors
  1. Arpit Jain
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  2. Abhinav Sharma
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  3. S. Nitisha Bharathi
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Corresponding author

Correspondence to Abhinav Sharma .

Editor information

Editors and Affiliations

  1. Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

    Sushabhan Choudhury

  2. Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

    R. Gowri

  3. Institute for Intelligent Systems, University of Johannesburg, Johannesburg, Gauteng, South Africa

    Babu Sena Paul

  4. Department of Computer Science and Information Engineering, Asia University, Taichung, Vietnam

    Dinh-Thuan Do

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Jain, A., Sharma, A., Nitisha Bharathi, S. (2021). Predicting the COVID-19 Cases in India. In: Choudhury, S., Gowri, R., Sena Paul, B., Do, DT. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 1341. Springer, Singapore. https://doi.org/10.1007/978-981-16-1510-8_30

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