Public interest in different types of masks and its relationship with pandemic and policy measures during the COVID-19 pandemic: a study using Google Trends data - Yeung, Andy Wai Kan; Parvanov, Emil D.; Horbańczuk, Jarosław Olav; Kletecka-Pulker, Maria; Kimberger, Oliver; Willschke, Harald; Atanasov, Atanas G. (Frontiers in Public Health, 2023)
Google Trends data been used to investigate various themes on online information seeking. It was unclear if the population from different parts of the world shared the same amount of attention to different mask types during the COVID-19 pandemic. This study aimed to reveal which types of masks were frequently searched by the public in different countries, and evaluated if public attention to masks could be related to mandatory policy, stringency of the policy, and transmission rate of COVID-19. By referring to an open dataset hosted at Our World in Data, the 10 countries with the highest total number of COVID-19 cases as of 9th of February 2022 were identified. For each of these countries, the weekly new cases per million population, reproduction rate (of COVID-19), stringency index, and face covering policy were computed from the raw daily data. Google Trends were queried to extract the relative search volume (RSV) for different types of masks from each of these countries. Results found that Google searches for N95 masks were predominant in India, whereas surgical masks were predominant in Russia, FFP2 masks were predominant in Spain, and cloth masks were predominant in both France and United Kingdom. The United States, Brazil, Germany, and Turkey had two predominant types of mask. The online searching behaviour for masks markedly varied across countries. The online searching for masks peaked during the first wave of COVID-19 pandemic and before the government implemented mandatory mask wearing for most of the surveyed countries. The search for masks positively correlated with the government response stringency index but not with the COVID-19 reproduction rate or the new cases per million.