How do Google searches for symptoms, news and unemployment interact during COVID-19? A Lotka–Volterra analysis of google trends data

Abstract

In this paper I exploit Google searches for the topics “symptoms”, “unemployment” and “news” as a proxy for how much attention people pay to the health and economic situation and the amount of news they consume, respectively. I then use an integrable nonautonomous Lotka–Volterra model to study the interactions among these searches in three U.S. States (Mississippi, Nevada and Utah), the District of Columbia and in the U.S. as a whole. I find that the results are very similar in all areas analyzed, and for different specifications of the model. Prior to the pandemic outbreak, the interactions among health searches, unemployment searches and news consumption are very weak, i.e. an increase in searches for one of these topics does not affect the amount of searches for the others. However, from around the beginning of the pandemic these interactions intensify greatly, suggesting that the pandemic has created a tight link between the health and economic situation and the amount of news people consume. I observe that from March 2020 unemployment predates searches for news and for symptoms. Consequently, whenever searches for unemployment increase, all the other searches decrease. Conversely, when searches for any of the other topics considered increase, searches for unemployment also increase. This underscores the importance of mitigating the impact of COVID-19 on unemployment to avoid that this issue swallows all others in the mind of the people.

Google, Public Health, and Alcohol and Drug Policy

“…Later, there was an increase in health-related search, news, alcohol, and porn, along with unemployment. The same pattern has been observed across three states in the USA (Sotis 2021). These findings reflect the socio-economic and health-related changes happening during the pandemic and help policymakers to plan appropriate strategies.…”

Reliability of Google Trends: Analysis of the Limits and Potential of Web Infoveillance During COVID-19 Pandemic and for Future Research

“…in a fixed timelapse. In this regard, the quantitative analysis of relative search volumes of pre-selected queries was used for several purposes during COVID-19 pandemic: 1) predicting COVID-19 cases ( Ahmad et al, 2020 ; Ayyoubzadeh et al, 2020 ; Jimenez et al, 2020 ; Mavragani and Gkillas, 2020 ; Sulyok et al, 2020 ; Venkatesh and Gandhi, 2020 ; Prasanth et al, 2021 ), 2) studying the web interest in COVID-19 ( Effenberger et al, 2020 ; Hu et al, 2020 ; Rovetta and Castaldo, 2020 ; Springer et al, 2020 ), 3) studying the adoption of infodemic terms and related consequences ( Cinelli et al, 2020 ; Cuan-Baltazar et al, 2020 ; Rovetta and Bhagavathula, 2020 ), 4) studying a full range of users’ psychological-emotional responses ( Husnayain et al, 2020 ; Rovetta and Castaldo, 2020 ; Zattoni et al, 2020 ; Brodeur et al, 2021 ; Zitting et al, 2021 ), 5) studying the impact of mass media and governmental policies on users’ web searches ( Rovetta and Bhagavathula, 2020 ; Sousa-Pinto et al, 2020 ; Huynh Dagher et al, 2021 ), 6) studying the economic-commercial impact ( Brodeur et al, 2021 ; Sotis, 2021 ), 7) studying the spread of COVID-19 symptoms ( Ahmad et al, 2020 ; Jimenez et al, 2020 ; Kluger and Scrivener, 2020 ; Walker et al, 2020 ), 8) studying other various web interests ( Berger et al, 2021 ; Elsaie and Youssef, 2021 ). This type of research is mainly based on the search for statistical cross-correlations between users’ web searches related to specific topics, such as symptoms, drugs, therapies, vaccines, number of infected people, number of deaths, anxiety, fear, stress, etc., and the number of disease contagions and deaths officially registered after a certain timespan.…”

Association of COVID‐19 with lifestyle behaviours and socio‐economic variables in Turkey: An analysis of Google Trends

“…They also stated that unemployment searches increased 269% compared to the pre‐pandemic period. Sotis 22 found that as Google searches for coronavirus and its symptoms increased, searches for ‘unemployment’ increased too.…”

“…Google Trends is one of the most efficient trend analysis tools focusing on the most searched keywords by individuals and it can be used to examine and estimate individuals' interests and behaviours. 1 , 16 Various studies about impacts of COVID‐19 on food security and diet‐related lifestyle behaviours, 16 , 17 and unemployment, 18 , 19 , 20 , 21 , 22 , 23 using Google Trends data, have been conducted. To our knowledge, no study has examined the impacts of COVID‐19 on socio‐economic variables and lifestyle behaviours, by using Google Trends data, comprehensively in Turkey.…”