ABSTRACT
Suicide is a significant public health concern globally, with its varying rates influenced by numerous factors, including seasonal changes. Online search behaviors, particularly searches related to suicide and mental health, have been proposed as real-time indicators of suicidal ideation in populations. In this study, a cross-sectional time series analysis was conducted, utilizing data on suicide attempts from the Polish Police Headquarters and online search behavior from Google Trends over a decade. Suicide attempt data were analyzed alongside the frequency of Google searches for suicide-related keywords derived from the Polish Corpus of Suicide Notes. A total of 66 keywords were selected for analysis to identify seasonal trends and patterns in search behavior. The study employed linear regression, Seasonal Mann-Kendall tests, and TBATS models to analyze the data. Suicide rates show seasonal patterns, peaking in warmer months. However, keyword searches did not strongly correlate with peak suicide months. This study enhances our understanding of suicide-related search trends and their potential connection to suicide rates. It suggests avenues for more effective prevention efforts and the potential for future algorithms to predict suicide rates and identify at-risk groups.
ABSTRACT
The exponential increase in internet use and the consequent surge in data generation present both opportunities and challenges for public health. Infodemiology, an emerging field at the intersection of information science and public health, seeks to harness the vast amounts of health-related data generated online for public health benefits. This paper provides a comprehensive overview of infodemiology, examining its development, methodologies, and potential to address public health challenges. We discuss the role of infodemiology in identifying and mitigating the spread of misinformation, especially in the context of the COVID-19 pandemic, which underscored the dangers of the "infodemic" - an overabundance of information, both accurate and not, that complicates public health responses. Through both demand and supply-based studies, infodemiology offers unique insights into health trends, misinformation dynamics, and the digital behaviors of health information seekers. Tools such as sentiment analysis are highlighted as essential in navigating the vast digital landscape for real-time health data analysis. Despite the potential of infodemiology, challenges such as data overload or misinformation. The paper concludes by emphasizing the importance of interdisciplinary collaboration, the development of advanced analytical tools, and the need for guidelines to maximize the field's impact on public health policy and practice.
Subject(s)
COVID-19 , Public Health , Humans , COVID-19/epidemiology , SARS-CoV-2 , Pandemics , CommunicationABSTRACT
BACKGROUND: The amount of data available online is constantly increasing, including search behavior and tracking trends in domains such as Google. Analyzing the data helps to predict patient needs and epidemiological events more accurately. Our study aimed to identify dermatology-related terms that occur seasonally and any search anomalies during the SARS-CoV-2 pandemic. METHODS: The data were gathered using Google Trends, with 69 entries between January-2010 and December-2020 analyzed. We conducted the Seasonal Mann-Kendal Test to determine the strength of trends. The month with the highest seasonal component (RSV) and the lowest seasonal component (RSV) was indicated for every keyword. Groups of keywords occurring together regularly at specific periods of the year were shown. RESULTS: We found that some topics were seasonally searched in winter (e.g., herpes, scabies, candida) and others in summer (e.g., erythema, warts, urticaria). CONCLUSIONS: Interestingly, downward trends in searches on sexually transmitted diseases in comparison with increased infection rates reported officially show a strong need for improved sexual education in Poland. There were no significant differences in trends for coronavirus-related cutaneous symptoms during 2020. We have shown that the seasonality of dermatologically related terms searched in Poland via Google did not differ significantly during SARS-CoV-2 pandemic.
