Investigating the impact of search results for fever, headache, cough, diarrhea, and nausea on the incidence of COVID-19 in India using Google Trends

摘要

We read with great interest the work of Lippi et al. (1) and believe their methodology is of great value in the current pandemic for several developing countries that are struggling to contain the pandemic. India is one such country, and it has recently become the epicenter of the pandemic as it became the first country to ever register more than 400,000 new cases of COVID19 in a single day (2). We conducted an electronic search using Google Trends (https://trends.google.com/trends) using the keywords “fever”, “cough”, “headache”, “diarrhea”, and “nausea” between January 1st,2021 to April 29th, 2021 for India. The number of new cases of COVID-19 in India during the same time period was obtained from Our World Data website (https://ourworldindata.org/ coronavirus/country/india?country=~IND). We converted the data to obtain a weekly average and used Spearman’s correlation via Analyse-it (Analyse-it Software Ltd, Leeds, UK) to evaluate the relationship between the keywords and the new cases of COVID19 in India. We then proceeded to study the differences in r-values and 95% confidence interval (C.I) when the search keywords are projected on the number cases at weeks zero, one, two, and three (1).