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

Hand, foot, and mouth disease (HFMD) is an infectious disease that causes blistering rashes on the mouth, hands, and feet. Most infected individuals recover from HFMD within a few days of infection. Various comorbidities, including myocarditis, neurogenic pulmonary edema, acute flaccid paralysis, and central nervous system complications such as meningitis, cerebellar ataxia, and encephalitis, can also occur [1, 2]. HFMD is distributed worldwide, and outbreaks often occur during the summer and early fall in the United States. Large outbreaks in Cambodia, China, Japan, Korea, Malaysia, Singapore, Thailand, and Vietnam have been reported over the past 2 decades [3, 4]. HFMD is seasonal in temperate Asia with a summer peak, and subtropical Asia with spring and fall peaks, but not in tropical Asia, indicating that temperate Japan has a climatic role [5]. During the summer of 2011, Japan had the largest HFMD epidemic on record, with 347,362 reported cases [6]. Coxsackievirus A6 (CV-A6) infection is responsible for most cases, with co-circulation of coxsackievirus A16 (CV-A16) and enterovirus A71 (EV-A71) [7]. EV-A71 was sporadically detected from October 2014 onward. It became the predominant serotype in 2018, with approximately 70,000 reported cases, following an increase in its spread from the end of 2017 [8]. Since June 2019, a severe outbreak of HFMD has occurred in multiple regions of Japan, attracting public attention [9]. As enteroviruses can spread rapidly by droplet and fomite transmission among children in daycare centers and kindergartens, understanding HFMD outbreaks is vital to public health, particularly during the Coronavirus Disease 2019 (COVID-19) pandemic [10].

Rapid recognition and reporting of HFMD infection are essential, and several studies have constructed models for explaining HFMD infection [11‐15]. Rui et al. explored epidemiological characteristics and calculated the early warning signals of HFMD using a logistic differential equation (LDE) model in seven regions of China [11]. Yu et al. forecasted the number of HFMD cases with wavelet-based hybrid models in Zhengzhou, China [12]. Zhang et al. proposed a landscape dynamic network marker (L-DNM) to detect pre-outbreak signals of HFMD in Tokyo, Hokkaido, and Osaka, Japan [13]. Gao et al. used monthly HFMD infection cases and meteorological data to construct a weather-based early warning model with a generalized additive model across China [14]. Zhao et al. used a meta-learning framework and combines Baidu search queries for real-time estimation of HFMD cases [15]. The above studies used a range of data, including monthly or weekly HFMD infectious cases [11, 12, 14], dynamic information from city networks, horizontal high-dimensional data, records of clinic visits [13], meteorological data [14], and Baidu search queries data [15] which are relatively difficult to access or delayed updates in Japan. Traditional surveillance and reporting systems lag an outbreak by 1 to 2 weeks because of the reporting and verification process. In Japan, the National Institute of Infectious Disease (NIID) has monitored the outbreak of various infectious diseases and issued weekly reports since 1999, but delayed for several weeks [16]. In addition, no studies have focused on changes in HFMD affected by the COVID-19 pandemic by Internet searching data compared with previous studies. As of August 2022, Google search data was considered reliable because its market share in Japan has been over 70% since 2009 [17, 18]. Google Trends data offers real-time and labor-saving information search by the public, which may be valuable for infection surveillance.

The science of distribution and determinants of information in an electronic medium, specifically the Internet, or in a population, to inform public health and policy is defined as “infodemiology” [19]. Google Trends is frequently used in infodemiology research to gauge public interests [20]. Google Trends reflects public information-seeking behavior and allows users to analyze Google search data for specific search terms in any country or region over a selected period [21, 22]. Studies have shown that online query trends correlate with real-life epidemiologic phenomena such as flu [23], sinusitis [24], lifestyle-related disease [25], asthma [26], and pruritus [27]. Researchers have also investigated public interest and information-seeking behaviors in chronic obstructive pulmonary disease (COPD) [28], cancer [29, 30], bariatric surgery [31], kidney stone surgery [32], and suicide [33]. During the COVID-19 pandemic, similar studies using Google Trends search data were conducted to predict COVID-19 infectious cases [34, 35], explore public attitudes toward vaccination [36‐38], identify symptoms caused by pandemics [39‐41], and assess affected medical services [42‐44]. The above studies indicate that Google Trends can assist in gaining a better understanding and analysis of health information-seeking behavior. Information from Google Trends can be used to supplement current infection reports with lag times.

This study aimed to explain HFMD infections using Google Trends data from Japan before and during the COVID-19 pandemic.

This study presented trends and correlations between HFMD cases and RSV of “HFMD” from 2009 to 2021. Cross-correlation analyses were conducted between HFMD cases and search terms for RSV before and during the pandemic period. Additionally, multiple linear regressions were used to identify significant search terms for explaining HFMD cases in the two periods. Our results indicated that HFMD cases and RSV peaked around July in most years, except in 2020 and 2021, and surged after 2011 with peaks every 2 years before 2020. The search topic “HFMD” exhibited strong correlations with HFMD cases except in 2020, when the COVID-19 outbreak occurred. Furthermore, cross-correlation and multiple regression results revealed that the public might have improved their awareness of HFMD infection during the pandemic. To our knowledge, this study is the first to explain HFMD cases using Google search data and to examine changes in information-seeking behavior toward HFMD affected by the COVID-19 pandemic. Google search data can supplement public health surveillance and help authorities respond rapidly to infectious diseases.

From 2009 to 2021, the RSV of “HFMD” coincided with the HFMD cases, except in 2020, which showed similar trends and peaks. In Japan, HFMD peaks generally occur in July [5]. During the COVID-19 pandemic, different from previous HFMD peaks disappeared in 2020 and lagged until November 2021. In 2020, Google Trends search data did not match the “HFMD” cases, with a relatively small peak in July. Despite a small peak in the RSV of the search topic “HFMD,” the volume was much lower than in previous years. In contrast, the Japanese government has implemented several measures to control COVID-19, which might potentially influence the spread of HFMD. Respiratory droplets and contact routes are the main infection routes in HFMD and COVID-19 [49, 50]. Therefore, the population susceptible to HFMD also stays safe by taking standard precautions during COVID-19, such as physical distancing, wearing a mask, regularly washing hands, and coughing into a bent elbow or tissue [51].

Based on the evidence provided by our results, the global pandemic might have enhanced public awareness of HFMD in addition to COVID-19. 73 (72.3%) search terms cross-correlated earlier with HFMD cases during COVID-19, and significant search terms detected in Period 2 contained more informative information. Previous studies demonstrated that the prevalence of respiratory infectious diseases reduced during the COVID-19 pandemic, such as influenza, varicella, herpes zoster, rubella, and measles [52‐58]. This might have been due to adherence to non-pharmaceutical interventions and lower non-polio enterovirus activity during the COVID-19 pandemic compared to 2014–2019 [59]. Switzerland had an unprecedented complete absence of pediatric enteroviral meningitis in 2020 [60]. In Japan, community-acquired pneumonia [61] and influenza [62] admissions have reduced during the COVID-19 pandemic. COVID-19 preventative actions and better personal hygiene are beneficial for preventing the spread of the disease. However, the prevalence of common diseases may rise as the public gradually complies less with infection control measures in the upcoming season [61]. Consistent with our results, a peak in HFMD infection and public interest reoccurred in November 2021. Continuous monitoring of HFMD is required, and public information-seeking behaviors may be helpful in public health surveillance.

Google search data was applied in our study to explain HFMD cases affected by COVID-19 instead of Baidu search data, which was used for real-time estimation of HFMD cases in China [15] and other categories of data for HFMD prediction or explanation [11‐14]. In contrast to previous studies, we focused on the distinction between the information-seeking behavior of HFMD before and during COVID-19 and attempted to explain the HFMD cases using Google Trends data, which has the highest market share in Japan [17]. Many researchers have shown that Google search data represent public interest in a specific topic. However, Google search data should be used cautiously as a surveillance system, because large events can easily interfere with it. Combining fine-grained data, such as mobility data, could help develop surveillance systems that can effectively exclude biased or irrelevant information to respond rapidly [63].

This study described trends and correlations in HFMD cases with RSV of “HFMD” and identified significant search terms to explain HFMD infections before and during the COVID-19 pandemic. We found that the prevalence of HFMD was abnormal during COVID-19, and the public might have enhanced awareness of HFMD infection affected by the pandemic. It is critical to continuously monitor resurgent common infections, as the public gradually reduces compliance with infection control measures. Public information seeking behavior using Google search data may be useful for public health surveillance.

This study has several limitations. First, our findings are limited to those who used Google to search for health-related information, which may not represent the entire community. The results may be biased toward younger people, who are more digitally connected than older individuals, although the Google search engine market share in Japan is nearly 80% [17]. Second, Google Trends improved the geographical assignment and data collection systems in 2011, 2016, and 2022. Our results in the basic description of HFMD cases and “HFMD” RSV might be affected by them. Third, search data analysis is hypersensitive to large events; therefore, it is complementary instead of replacing traditional research methods. Fourth, the specific HFMD-related terms selected by Twitter may not represent all search terms in public use, especially hiragana, katakana, kanji, and alphabets used in Japan. Fifth, we used search data from 2016 to 2019 to represent the period before the COVID-19 pandemic owing to restrictions of Google Trends, which may not represent the entire period. Finally, during the process of backward elimination for regression model construction, significant terms may be eliminated because they are jointly insignificant. Although we can find potentially significant terms from all eliminated terms, it is not practical to conduct F-tests multiple times because multiple hypothesis testing leads to lower confidence levels. Hence, the current processing results were retained.