Methods
This study investigated the correlation between the number of new cases
of COVID-19 and the search index from Google. The aim of this study was
to create an effective and affordable model to predict new cases, which
would enable prompt and correct decision- making regarding public
policies to limit the spread of COVID-19.
Google trend is known as a publicly available web-based tool which
analyse relative search for a particular query. Google trend can
provides the number of relative searches for a particular query within a
particular time and a particular region or worldwide. Terms such as
Coronavirus, handwashing, and face masks in Bahasa were collected from
GT during the period of January 1st 2020 to march
31st , 2020. These search terms represented the
information search for COVID-19 and practice of personal precautions to
prevent disease transmission. Relative search volume (RSV) data were
filtered by geographic regions in Indonesia. The data collected from
Google Trends is adjusted to the time and location, so the comparisons
between queries can be easier. These queries were searched from
2019/12/12 to 2020/04/04 within the seven provinces in Indonesia such
DKI Jakarta, East Java, Yogyakarta Special Province, Central Java, West
Java, Bali and South Sulawesi. These countries were selected because
there were positive COVID-19 cases in these provinces in the beginning
of the outbreak. Besides, since the RSV in the Indonesia and some
provinces is less than “1” for several days, we treated it as RSV
equal to “1” in these days for better reflecting the Indonesian and
people in the selected provinces response to COVID-19 as conducted in
the previous study (Hu et al., 2020). The results then being downloaded
in the format of Common Separated Values, which displayed on a scale
from 0 to 100. GT data then were compared with daily data on COVID-19
cases that were obtained from the website of COVID centre Ministry of
Health Indonesia.