Defining Causality in Covid-19 and Google Search Trends in Java, Indonesia Cases: A Retrospective Analysis

Authors

  • Afrina Andriani br Sebayang Department of Mathematics, Institut Teknologi Bandung, Bandung, 40132, West Java, Indonesia
  • Enrico Antonius Department of Mathematics, Institut Teknologi Bandung, Bandung, 40132, West Java, Indonesia
  • Elisabeth Victoria Pravitama Department of Mathematics, Institut Teknologi Bandung, Bandung, 40132, West Java, Indonesia
  • Jonathan Irianto Department of Mathematics, Institut Teknologi Bandung, Bandung, 40132, West Java, Indonesia
  • Shannen Widijanto Department of Mathematics, Institut Teknologi Bandung, Bandung, 40132, West Java, Indonesia
  • Muhammad Syamsuddin Department of Mathematics, Institut Teknologi Bandung, Bandung, 40132, West Java, Indonesia

DOI:

https://doi.org/10.5614/cbms.2021.4.2.1

Keywords:

Covid-19, google trend data, causality, granger causality, correlation

Abstract

The Coronavirus disease 2019 (Covid-19) has led all countries around the world to the unpredicted situation. It is such a crucial to investigate novel approaches in predicting the future behaviour of the outbreak. In this paper, Google trend analysis will be employed to analyse the seek pattern of Covid-19 cases. The first method to investigate the seek information behaviour related to Covid-19 outbreak is using lag-correlation between two time series data per regional data. The second method is used to encounter the cause-effect relation between time series data. We apply statistical methods for causal inference in epidemics. Our focus is on predicting the causal-effect relationship between information-seeking patterns and Google search in the Covid-19 pandemic. We propose the using of Granger Causality method to analyse the causal relation between incidence data and Google Trend Data.

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Published

2021-12-31

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