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Data analytics and knowledge management approach for COVID-19 prediction and control.

Iqbal Hasan1,2, Prince Dhawan3, S A M Rizvi2

  • 1National Informatics Centre, Delhi Secretariat, IP Estate, New Delhi, 110003 India.

International Journal of Information Technology : an Official Journal of Bharati Vidyapeeth'S Institute of Computer Applications and Management
|June 22, 2022
PubMed
Summary

A new digital framework and ARIMA model improved COVID-19 surveillance and control in Delhi-NCR. This strategy led to significant reductions in Coronavirus Disease (COVID-19) cases and deaths.

Keywords:
ARIMACOVID-19 pandemicData analyticsForecastingSARS-CoV-2

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Area of Science:

  • Public Health
  • Epidemiology
  • Health Informatics

Background:

  • Coronavirus Disease (COVID-19) remains a global health threat, necessitating innovative digital solutions for prediction and control.
  • Effective data management and real-time surveillance are crucial for combating infectious disease outbreaks.
  • The Delhi-National Capital Region (NCR) faced significant challenges in managing the COVID-19 pandemic.

Purpose of the Study:

  • To develop and implement a strategic technical solution for COVID-19 surveillance and control in Delhi-NCR.
  • To elucidate the Delhi COVID-19 Data Management Framework and the integrated Command and Control Center (iCCC) mechanism.
  • To forecast COVID-19 spread using time-series data for informed policy-making.

Main Methods:

  • Development of the Delhi COVID-19 Data Management Framework.
  • Implementation of an integrated Command and Control Center (iCCC) with administrative, medical, and field operation modules.
  • Application of the Auto-Regressive Integrated Moving Average (ARIMA) model for time-series forecasting of COVID-19 spread.

Main Results:

  • The iCCC repository provided essential time-series data for analysis.
  • ARIMA modeling effectively forecasted logistics requirements, active cases, positive patients, and death rates.
  • The generated intelligence enabled real-time policy formulation and implementation by the Delhi government.

Conclusions:

  • The integrated digital solution significantly enhanced COVID-19 surveillance and control capabilities in Delhi-NCR.
  • The strategic framework and forecasting model contributed to a drastic reduction in COVID-19 cases and fatalities.
  • This approach provides a scalable model for managing future public health emergencies.