Communication in Biomathematical Sciences
Vol. 4 No. 2 (2021)

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

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)



Article Info

Publish Date
31 Dec 2021

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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Journal Info

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Publisher

Subject

Social Sciences

Description

Full research articles in the area of Applications of Mathematics in biological processes and ...