Tracing Diagnosis COVID-19 Analysis on Google by COVID-19 Cases in Indonesia

Gabriela Eliza Fabrianne Tamba (1) , Rizma Adlia Syakurah (2)
(1) Faculty of Public Health, Universitas Sriwijaya , Indonesia
(2) Faculty of Public Health, Universitas Sriwijaya , Indonesia

Abstract

COVID-19 transmission can be controlled through RT-PCR and RDT-Ag diagnostic tests, yet neither test performs well. This has encouraged people to search information for the COVID-19 pandemic response and exposure fears on Google. Therefore, this study analyzes the correlation between COVID-19 diagnosis tracing on Google and new COVID-19 cases in Indonesia. An explanatory mixed method study design was used. A quantitative study was done using time-lag correlation between the keywords, namely “Antigen”, “Swab” dan “PCR” based on Google Trends™ (https: // trend.Google.com/trends) from 13 July 2020 to November 2021. The search peaks for diagnosis and their geographical distribution were described qualitatively. There is a correlation between COVID-19 diagnosis searches on the keywords Swab (r = 0.787, P-Value    = 0.000) and Antigen (r = 0.378, P-Value    = 0.003) with COVID-19 new positive cases. The cumulative number of daily tests is also correlated with COVID-19 diagnosis searches (r = 0.617, P-Value     = 0.000 (PCR keywords) and r = -0.337, P-Value    = 0.003 (Keywords Swab)). There was also a correlation between searches for COVID-19-related keywords PCR, Swab, and Antigen and the frequency of daily PCR and Antigen tests (P-Value   <0.005). Google Trend has the potential as a monitoring tool for people's diagnosis behavior. Further study of Google Trends is required to strengthen the potential of Google Trends for monitoring COVID-19 cases in Indonesia.

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Authors

Gabriela Eliza Fabrianne Tamba
Rizma Adlia Syakurah
rizma.syakurah@gmail.com (Primary Contact)
1.
Tamba GEF, Syakurah RA. Tracing Diagnosis COVID-19 Analysis on Google by COVID-19 Cases in Indonesia. JIKM [Internet]. 2023 Mar. 31 [cited 2024 Nov. 21];14(1):112-26. Available from: https://ejournal.fkm.unsri.ac.id/index.php/jikm/article/view/1105

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