Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study

• Published in: BMC infectious diseases Vol. 22; no. 1; pp. 1 - 806
• Main Authors: Niu, Qian, Liu, Junyu, Zhao, Zixi, Onishi, Miyu, Kawaguchi, Asuka, Bandara, Anuradhi, Harada, Keiko, Aoyama, Tomoki, Nagai-Tanima, Momoko
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 29-10-2022; BioMed Central; BMC
• Subjects: Coronaviruses; Correlation coefficient; Correlation coefficients; COVID-19; Coxsackievirus infections; Cross correlation; Data search; Epidemics; Explanation; Google Trends; Hand-foot-and-mouth disease; Health aspects; HFMD; Infection; Infections; Infectious diseases; Infodemiology; Information management; Information-seeking behavior; Japan; Medical treatment; Pandemics; Public awareness; Public concern; Public health; Risk factors; Search engines; Signs and symptoms; Social aspects; Statistical analysis; Statistics; Technology application; Trends; Viral diseases; Japan; Asia; China
• ISSN: 1471-2334; 1471-2334
• DOI: 10.1186/s12879-022-07790-9

Coronavirus Disease 2019 (COVID-19) pandemic affects common diseases, but its impact on hand, foot, and mouth disease (HFMD) is unclear. Google Trends data is beneficial for approximate real-time statistics and because of ease in access, is expected to be used for infection explanation from an information-seeking behavior perspective. We aimed to explain HFMD cases before and during COVID-19 using Google Trends. HFMD cases were obtained from the National Institute of Infectious Diseases, and Google search data from 2009 to 2021 in Japan were downloaded from Google Trends. Pearson correlation coefficients were calculated between HFMD cases and the search topic "HFMD" from 2009 to 2021. Japanese tweets containing "HFMD" were retrieved to select search terms for further analysis. Search terms with counts larger than 1000 and belonging to ranges of infection sources, susceptible sites, susceptible populations, symptoms, treatment, preventive measures, and identified diseases were retained. Cross-correlation analyses were conducted to detect lag changes between HFMD cases and search terms before and during the COVID-19 pandemic. Multiple linear regressions with backward elimination processing were used to identify the most significant terms for HFMD explanation. HFMD cases and Google search volume peaked around July in most years, excluding 2020 and 2021. The search topic "HFMD" presented strong correlations with HFMD cases, except in 2020 when the COVID-19 outbreak occurred. In addition, the differences in lags for 73 (72.3%) search terms were negative, which might indicate increasing public awareness of HFMD infections during the COVID-19 pandemic. The results of multiple linear regression demonstrated that significant search terms contained the same meanings but expanded informative search content during the COVID-19 pandemic. The significant terms for the explanation of HFMD cases before and during COVID-19 were different. Awareness of HFMD infections in Japan may have improved during the COVID-19 pandemic. Continuous monitoring is important to promote public health and prevent resurgence. The public interest reflected in information-seeking behavior can be helpful for public health surveillance.