ArticleJMIR public health and surveillance2020
Tracking COVID-19 in Europe: Infodemiology Approach.
Article in JMIR public health and surveillance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.
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Who cites it
68 citing papers in PubMed.
- Nowcasting methods to improve the performance of respiratory sentinel surveillance: lessons from the COVID-19 pandemic.Scientific reports · 2024Article
- Using Natural Language Processing to Explore Social Media Opinions on Food Security: Sentiment Analysis and Topic Modeling Study.Journal of medical Internet research · 2024Article
- Facebook addiction and sleep problems in peruvian university students after the COVID-19 pandemic.Heliyon · 2024Article
- Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- Development of an early alert model for pandemic situations in Germany.Scientific reports · 2023Article
- An overview of SARS-CoV-2 transmission and engineering strategies to mitigate risk.Journal of building engineering · 2023Review
- Analysis of policy responses to COVID-19: a case study in Babol University of Medical Sciences (BUMS), Iran.Cost effectiveness and resource allocation : C/E · 2022Article
- Assessing Associations Between COVID-19 Symptomology and Adverse Outcomes After Piloting Crowdsourced Data Collection: Cross-sectional Survey Study.JMIR formative research · 2022Article
- Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review.International journal of environmental research and public health · 2022Review
- Public Interest and Accessibility of Telehealth in Japan: Retrospective Analysis Using Google Trends and National Surveillance.JMIR formative research · 2022Article
- Interest in dentistry in early months of the COVID-19 global pandemic: A Google Trends approach.Health information and libraries journal · 2022Article
- COVID-19 forecasts using Internet search information in the United States.Scientific reports · 2022Article
- How Italy Tweeted about COVID-19: Detecting Reactions to the Pandemic from Social Media.International journal of environmental research and public health · 2022Article
- Assessing the Capability of Government Information Intervention and Socioeconomic Factors of Information Sharing during the COVID-19 Pandemic: A Cross-Country Study Using Big Data Analytics.Behavioral sciences (Basel, Switzerland) · 2022Article
- Recording and evaluating affect and coping during COVID-19 in healthcare workers and outcomes (REACCH-Out): mental health implications for our junior doctor cohort.BMJ open quality · 2022Article
- Effect of COVID-19 quarantine on cognitive, functional and neuropsychiatric symptoms in patients with mild cognitive impairment and dementia.Aging clinical and experimental research · 2022Article
- Early warning of COVID-19 hotspots using human mobility and web search query data.Computers, environment and urban systems · 2022Article
- Tracking the COVID-19 outbreak in India through Twitter: Opportunities for social media based global pandemic surveillance.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2022Article
- Modeling approaches for early warning and monitoring of pandemic situations as well as decision support.Frontiers in public health · 2022Review
- The impact the COVID-19 pandemic on urology literature: a bibliometric analysis.Central European journal of urology · 2022Review
8 more citing papers are in PubMed but not listed here.
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1 author.
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Abstract
backgroundInfodemiology (ie, information epidemiology) uses web-based data to inform public health and policy. Infodemiology metrics have been widely and successfully used to assess and forecast epidemics and outbreaks.
objectiveIn light of the recent coronavirus disease (COVID-19) pandemic that started in Wuhan, China in 2019, online search traffic data from Google are used to track the spread of the new coronavirus disease in Europe.
methodsTime series from Google Trends from January to March 2020 on the Topic (Virus) of "Coronavirus" were retrieved and correlated with official data on COVID-19 cases and deaths worldwide and in the European countries that have been affected the most: Italy (at national and regional level), Spain, France, Germany, and the United Kingdom.
resultsStatistically significant correlations are observed between online interest and COVID-19 cases and deaths. Furthermore, a critical point, after which the Pearson correlation coefficient starts declining (even if it is still statistically significant) was identified, indicating that this method is most efficient in regions or countries that have not yet peaked in COVID-19 cases.
conclusionsIn the past, infodemiology metrics in general and data from Google Trends in particular have been shown to be useful in tracking and forecasting outbreaks, epidemics, and pandemics as, for example, in the cases of the Middle East respiratory syndrome, Ebola, measles, and Zika. With the COVID-19 pandemic still in the beginning stages, it is essential to explore and combine new methods of disease surveillance to assist with the preparedness of health care systems at the regional level.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.