Forecasting COVID-19 impact in India using pandemic waves Nonlinear Growth Models

  1. Pavan Kumar
  2. Ram Kumar Singh
  3. Chintan Nanda
  4. Himangshu Kalita
  5. Shashikanta Patairiya
  6. Yagya Datt Sharma
  7. Meenu Rani
  8. Akshaya Srikanth Bhagavathula

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Abstract

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) started in China and devastated a vast majority of countries. In India, COVID-19 cases are steadily increasing since January 30, 2020, and the government-imposed lockdown across the country to curtail community transmission. COVID-19 forecasts have played an important role in capturing the probability of infection and the basic reproduction rate. In this study, we predicted some trajectories of trajectories associated with COVID-19 in the coming days in India using an Auto-regression integrated moving average model (ARIMA) and Richard’s model. By the end of April 2020, the incidence of new cases is predicted to be 5200 (95% CI: 4650 to 6002) through the ARIMA model versus be 6378 (95% CI: 4904 to 7851) Richard model. We estimated that there would be a total of 197 (95% CI: 118 to 277) deaths and drop down in the recovery rates will reach around 501 (95% CI: 245 to 758) by the end of April 2020. These estimates can help to strengthen the implementation of strategies to increase the health system capacity and enactment of social distancing measures all over India.

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    SciScore for 10.1101/2020.03.30.20047803: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

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    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

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  2. Version published to 10.1101/2020.03.30.20047803v2 on medRxiv
  3. Version published to 10.1101/2020.03.30.20047803v1 on medRxiv