ABSTRACT
Objectives: We aimed to predict the number of hand, foot, and mouth disease (HFMD) infections before and during the COVID-19 pandemic using Internet search data. Methods: We obtained actual HFMD cases from the National Institute of Infectious Disease and Internet search data using Google Trends between 2004 and 2021 in Japan. We calculated the Pearson correlation coefficients between actual HFMD cases and the search topic "HFMD" from 2004 to 2021. We conducted a cross-correlation analysis between the actual HFMD cases and 43 HFMD-related search terms before and during the pandemic. We identified the most significant predictors of HFMD infection using stepwise multiple linear regression. Results: We found that actual HFMD cases and Internet search volume peaked around July in most years, except for 2020 and 2021. The search topic "HFMD" presented a strong correlation with actual HFMD cases, but the correlation was weaker in 2004, 2008, and 2020. Results from stepwise multiple linear regression exhibited that the search terms "infect," "daycare," "vomit," "HFMD," "eczema," "pain," and "high fever were the most significant predictors before the pandemic, while "infect," "enterovirus," "herpangina," "kindergarten," "myocarditis," "HFMD," "contact infection," "blister," "high fever" "dermatology," and "plantar" were the most significant predictors during the pandemic. Conclusions: The predictors for HFMD infections before and during the COVID-19 pandemic were different. The awareness of HFMD infection in Japan may improved during the COVID-19 pandemic. Continuous monitoring is important to promote public health and prevent resurgence. Public interest reflected in information-seeking behavior can be helpful for public health surveillance.