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Tudor C, Sova RA. Mining Google Trends data for nowcasting and forecasting colorectal cancer (CRC) prevalence. PeerJ Comput Sci 2023; 9:e1518. [PMID: 37869464 PMCID: PMC10588692 DOI: 10.7717/peerj-cs.1518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 07/14/2023] [Indexed: 10/24/2023]
Abstract
Background Colorectal cancer (CRC) is the third most prevalent and second most lethal form of cancer in the world. Consequently, CRC cancer prevalence projections are essential for assessing the future burden of the disease, planning resource allocation, and developing service delivery strategies, as well as for grasping the shifting environment of cancer risk factors. However, unlike cancer incidence and mortality rates, national and international agencies do not routinely issue projections for cancer prevalence. Moreover, the limited or even nonexistent cancer statistics for large portions of the world, along with the high heterogeneity among world nations, further complicate the task of producing timely and accurate CRC prevalence projections. In this situation, population interest, as shown by Internet searches, can be very important for improving cancer statistics and, in the long run, for helping cancer research. Methods This study aims to model, nowcast and forecast the CRC prevalence at the global level using a three-step framework that incorporates three well-established univariate statistical and machine-learning models. First, data mining is performed to evaluate the relevancy of Google Trends (GT) data as a surrogate for the number of CRC survivors. The results demonstrate that population web-search interest in the term "colonoscopy" is the most reliable indicator to nowcast CRC disease prevalence. Then, various statistical and machine-learning models, including ARIMA, ETS, and FNNAR, are trained and tested using relevant GT time series. Finally, the updated monthly query series spanning 2004-2022 and the best forecasting model in terms of out-of-sample forecasting ability (i.e., the neural network autoregression) are utilized to generate point forecasts up to 2025. Results Results show that the number of people with colorectal cancer will continue to rise over the next 24 months. This in turn emphasizes the urgency for public policies aimed at reducing the population's exposure to the principal modifiable risk factors, such as lifestyle and nutrition. In addition, given the major drop in population interest in CRC during the first wave of the COVID-19 pandemic, the findings suggest that public health authorities should implement measures to increase cancer screening rates during pandemics. This in turn would deliver positive externalities, including the mitigation of the global burden and the enhancement of the quality of official statistics.
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Affiliation(s)
- Cristiana Tudor
- Bucharest University of Economic Studies, Bucharest, Romania
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2
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Maaß CH. Shedding light on dark figures: Steps towards a methodology for estimating actual numbers of COVID-19 infections in Germany based on Google Trends. PLoS One 2022; 17:e0276485. [PMID: 36288363 PMCID: PMC9605024 DOI: 10.1371/journal.pone.0276485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 10/02/2022] [Indexed: 11/07/2022] Open
Abstract
In order to shed light on unmeasurable real-world phenomena, we investigate exemplarily the actual number of COVID-19 infections in Germany based on big data. The true occurrence of infections is not visible, since not every infected person is tested. This paper demonstrates that coronavirus-related search queries issued on Google can depict true infection levels appropriately. We find significant correlation between search volume and national as well as federal COVID-19 cases as reported by RKI. Additionally, we discover indications that the queries are indeed causal for infection levels. Finally, this approach can replicate varying dark figures throughout different periods of the pandemic and enables early insights into the true spread of future virus outbreaks. This is of high relevance for society in order to assess and understand the current situation during virus outbreaks and for decision-makers to take adequate and justifiable health measures.
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Affiliation(s)
- Christina H. Maaß
- Department of Economics, University of Hamburg, Hamburg, Germany
- * E-mail:
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3
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Gupta R, Mohanty V, Balappanavar AY, Chahar P, Rijhwani K, Bhatia S. Infodemiology for oral health and disease: A scoping review. Health Info Libr J 2022; 39:207-224. [PMID: 36046959 DOI: 10.1111/hir.12453] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 06/30/2022] [Accepted: 07/05/2022] [Indexed: 01/28/2023]
Abstract
INTRODUCTION Increasing affordability, accessibility and penetration of internet services worldwide, have substantially changed the ways of gathering health-related information. This has led to the origin of concept infodemiology that allows the information to be collected and analysed in near real time. Globally, oral diseases affect nearly 3.5 billion people; thus, volume and profile of oral health searches would help in understanding specific community dental needs and formulation of pertinent oral health strategies. AIM To review the published literature on infodemiological aspects of oral health and disease. METHODOLOGY This scoping review was conducted in accordance with PRISMA-ScR guidelines. Electronic search engines (Google Scholar) and databases (PubMed, Web of science, Scopus) were searched from 2002 onwards. RESULTS Thirty-eight articles were included in this review. The infodemiological studies for oral health and disease were mainly used in two domains. Out of 38 articles, 24 accessed the quality of available online information and 15 studied online oral health-related information seeking behaviour. CONCLUSION The most commonly searched oral diseases were toothache, oral cancer, dental caries, periodontal disease, oral maxillofacial surgical procedures and paediatric oral diseases. Most of the studies belonged to developed countries and Google was the most researched search engine.
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Affiliation(s)
- Radhika Gupta
- Department of Public Health Dentistry, Maulana Azad Institute of Dental Sciences, New Delhi, India
| | - Vikrant Mohanty
- Department of Public Health Dentistry, Maulana Azad Institute of Dental Sciences, New Delhi, India
| | - Aswini Y Balappanavar
- Department of Public Health Dentistry, Maulana Azad Institute of Dental Sciences, New Delhi, India
| | - Puneet Chahar
- Department of Public Health Dentistry, Maulana Azad Institute of Dental Sciences, New Delhi, India
| | - Kavita Rijhwani
- Department of Public Health Dentistry, Maulana Azad Institute of Dental Sciences, New Delhi, India
| | - Sonal Bhatia
- Department of Public Health Dentistry, Maulana Azad Institute of Dental Sciences, New Delhi, India
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4
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Garett R, Young SD. The role of social media in monitoring COVID-19 vaccine uptake. J Eval Clin Pract 2022; 28:650-652. [PMID: 35856457 PMCID: PMC9310197 DOI: 10.1111/jep.13656] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 12/17/2021] [Accepted: 12/21/2021] [Indexed: 12/22/2022]
Affiliation(s)
| | - Sean D Young
- Department of Emergency Medicine, University of California, Irvine, California, USA.,Department of Informatics, Institute for Prediction Technology, University of California, Irvine, California, USA
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5
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Deiner MS, Kaur G, McLeod SD, Schallhorn JM, Chodosh J, Hwang DH, Lietman TM, Porco TC. A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study. J Med Internet Res 2022; 24:e27310. [PMID: 35537041 PMCID: PMC9297131 DOI: 10.2196/27310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 08/18/2021] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
Background Studies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as web-based search data to learn more about such patterns could improve the understanding of patients’ eye-related conditions and well-being, better inform timing of clinical and remote eye care, and improve precision when targeting web-based public health campaigns toward underserved populations. Objective To investigate our hypothesis that the public is likely to consistently search about different ophthalmologic conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to ophthalmologic conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other. Methods We designed a study to analyze and compare hourly search data for eye-related and control search terms, using time series regression models with trend and periodicity terms to remove outliers and then estimate diurnal effects. We planned a Google Trends setting, extracting data from 10 US states for the entire year of 2018. The exposure was internet search, and the participants were populations who searched through Google’s search engine using our chosen study terms. Our main outcome measures included cyclical hourly and day-of-week web-based search patterns. For statistical analyses, we considered P<.001 to be statistically significant. Results Distinct diurnal (P<.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented those reported from prior clinical studies. Of the eye-related terms, “pink eye” showed the largest diurnal amplitude-to-mean ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. By contrast, “dry eyes” had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening-to-morning period and peaking in early morning. Conclusions The frequency of web-based searches for various eye conditions can show cyclic patterns according to time of the day or week. Further studies to understand the reasons for these variations may help supplement the current clinical understanding of ophthalmologic symptom presentation and improve the timeliness of patient messaging and care interventions.
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Affiliation(s)
- Michael S Deiner
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, United States.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, United States
| | - Gurbani Kaur
- Department of Ophthalmology, University of California San Francisco, San Francisco, CA, United States.,School of Medicine, University of California San Francisco, San Francisco, CA, United States
| | - Stephen D McLeod
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, United States.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, United States
| | - Julie M Schallhorn
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, United States.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, United States
| | - James Chodosh
- Department of Ophthalmology, Harvard Medical School, Boston, MA, United States.,Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, United States
| | - Daniel H Hwang
- Stanford University, San Mateo, CA, United States.,The Nueva School, San Mateo, CA, United States
| | - Thomas M Lietman
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, United States.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, United States.,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, United States.,Global Health Sciences, University of California San Francisco, San Francisco, CA, United States
| | - Travis C Porco
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, United States.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, United States.,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, United States.,Global Health Sciences, University of California San Francisco, San Francisco, CA, United States
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Gillis T, Garrison S. Confounding Effect of Undergraduate Semester-Driven "Academic" Internet Searches on the Ability to Detect True Disease Seasonality in Google Trends Data: Fourier Filter Method Development and Demonstration. JMIR INFODEMIOLOGY 2022; 2:e34464. [PMID: 37113451 PMCID: PMC9987186 DOI: 10.2196/34464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 06/09/2022] [Accepted: 06/24/2022] [Indexed: 04/29/2023]
Abstract
Background Internet search volume for medical information, as tracked by Google Trends, has been used to demonstrate unexpected seasonality in the symptom burden of a variety of medical conditions. However, when more technical medical language is used (eg, diagnoses), we believe that this technique is confounded by the cyclic, school year-driven internet search patterns of health care students. Objective This study aimed to (1) demonstrate that artificial "academic cycling" of Google Trends' search volume is present in many health care terms, (2) demonstrate how signal processing techniques can be used to filter academic cycling out of Google Trends data, and (3) apply this filtering technique to some clinically relevant examples. Methods We obtained the Google Trends search volume data for a variety of academic terms demonstrating strong academic cycling and used a Fourier analysis technique to (1) identify the frequency domain fingerprint of this modulating pattern in one particularly strong example, and (2) filter that pattern out of the original data. After this illustrative example, we then applied the same filtering technique to internet searches for information on 3 medical conditions believed to have true seasonal modulation (myocardial infarction, hypertension, and depression), and all bacterial genus terms within a common medical microbiology textbook. Results Academic cycling explains much of the seasonal variation in internet search volume for many technically oriented search terms, including the bacterial genus term ["Staphylococcus"], for which academic cycling explained 73.8% of the variability in search volume (using the squared Spearman rank correlation coefficient, P<.001). Of the 56 bacterial genus terms examined, 6 displayed sufficiently strong seasonality to warrant further examination post filtering. This included (1) ["Aeromonas" + "Plesiomonas"] (nosocomial infections that were searched for more frequently during the summer), (2) ["Ehrlichia"] (a tick-borne pathogen that was searched for more frequently during late spring), (3) ["Moraxella"] and ["Haemophilus"] (respiratory infections that were searched for more frequently during late winter), (4) ["Legionella"] (searched for more frequently during midsummer), and (5) ["Vibrio"] (which spiked for 2 months during midsummer). The terms ["myocardial infarction"] and ["hypertension"] lacked any obvious seasonal cycling after filtering, whereas ["depression"] maintained an annual cycling pattern. Conclusions Although it is reasonable to search for seasonal modulation of medical conditions using Google Trends' internet search volume and lay-appropriate search terms, the variation in more technical search terms may be driven by health care students whose search frequency varies with the academic school year. When this is the case, using Fourier analysis to filter out academic cycling is a potential means to establish whether additional seasonality is present.
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Affiliation(s)
- Timber Gillis
- Department of Family Medicine University of Alberta Edmonton, AB Canada
| | - Scott Garrison
- Department of Family Medicine University of Alberta Edmonton, AB Canada
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7
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Infodemiological study on the impact of the COVID-19 pandemic on increased headache incidences at the world level. Sci Rep 2022; 12:10253. [PMID: 35715461 PMCID: PMC9205282 DOI: 10.1038/s41598-022-13663-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 05/17/2022] [Indexed: 12/21/2022] Open
Abstract
The analysis of the public interest as reflected by Internet queries has become a highly valuable tool in many fields. The Google Trends platform, providing timely and informative data, has become increasingly popular in health and medical studies. This study explores whether Internet search frequencies for the keyword “headache” have been increasing after the COVID-19 pandemic outbreak, which could signal an increased incidence of the health problem. Weekly search volume data for 5 years spanning February 2017 to February 2022 were sourced from Google Trends. Six statistical and machine-learning methods were implemented on training and testing sets via pre-set automated forecasting algorithms. Holt-Winters has been identified as overperforming in predicting web query trends through several accuracy measures and the DM test for forecasting superiority and has been employed for producing the baseline level in the estimation of excess query level over the first pandemic wave. Findings indicate that the COVID-19 pandemic resulted in an increased global incidence of headache (as proxied by related web queries) in the first 6 months after its outbreak, with an excess occurrence of 4.53% globally. However, the study also concludes that the increasing trend in headache incidence at the world level would have continued in the absence of the pandemic, but it has been accelerated by the pandemic event. Results further show mixed correlations at the country-level between COVID-19 infection rates and population web-search behavior, suggesting that the increased headache incidence is caused by pandemic-related factors (i.e. increased stress and mental health problems), rather than a direct effect of coronavirus infections. Other noteworthy findings entail that in the Philippines, the term "headache" was the most frequently searched term in the period spanning February 2020 to February 2022, indicating that headache occurrences are a significant aspect that defines population health at the country level. High relative interest is also detected in Kenya and South Africa after the pandemic outbreak. Additionally, research findings indicate that the relative interest has decreased in some countries (i.e. US, Canada, and Australia), whereas it has increased in others (i.e. India and Pakistan) after the pandemic outbreak. We conclude that observing Internet search habits can provide timely information for policymakers on collective health trends, as opposed to ex-post statistics, and can furthermore yield valuable information for the pain management drug market key players about aggregate consumer behavior.
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Ethical Issues in AI-Enabled Disease Surveillance: Perspectives from Global Health. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12083890] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Infectious diseases, as COVID-19 is proving, pose a global health threat in an interconnected world. In the last 20 years, resistant infectious diseases such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), H1N1 influenza (swine flu), Ebola virus, Zika virus, and now COVID-19 have been impacting global health defences, and aggressively flourishing with the rise of global travel, urbanization, climate change, and ecological degradation. In parallel, this extraordinary episode in global human health highlights the potential for artificial intelligence (AI)-enabled disease surveillance to collect and analyse vast amounts of unstructured and real-time data to inform epidemiological and public health emergency responses. The uses of AI in these dynamic environments are increasingly complex, challenging the potential for human autonomous decisions. In this context, our study of qualitative perspectives will consider a responsible AI framework to explore its potential application to disease surveillance in a global health context. Thus far, there is a gap in the literature in considering these multiple and interconnected levels of disease surveillance and emergency health management through the lens of a responsible AI framework.
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Shakeri Hossein Abad Z, Butler GP, Thompson W, Lee J. Crowdsourcing for Machine Learning in Public Health Surveillance: Lessons Learned From Amazon Mechanical Turk. J Med Internet Res 2022; 24:e28749. [PMID: 35040794 PMCID: PMC8808350 DOI: 10.2196/28749] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 07/05/2021] [Accepted: 11/15/2021] [Indexed: 12/30/2022] Open
Abstract
Background Crowdsourcing services, such as Amazon Mechanical Turk (AMT), allow researchers to use the collective intelligence of a wide range of web users for labor-intensive tasks. As the manual verification of the quality of the collected results is difficult because of the large volume of data and the quick turnaround time of the process, many questions remain to be explored regarding the reliability of these resources for developing digital public health systems. Objective This study aims to explore and evaluate the application of crowdsourcing, generally, and AMT, specifically, for developing digital public health surveillance systems. Methods We collected 296,166 crowd-generated labels for 98,722 tweets, labeled by 610 AMT workers, to develop machine learning (ML) models for detecting behaviors related to physical activity, sedentary behavior, and sleep quality among Twitter users. To infer the ground truth labels and explore the quality of these labels, we studied 4 statistical consensus methods that are agnostic of task features and only focus on worker labeling behavior. Moreover, to model the meta-information associated with each labeling task and leverage the potential of context-sensitive data in the truth inference process, we developed 7 ML models, including traditional classifiers (offline and active), a deep learning–based classification model, and a hybrid convolutional neural network model. Results Although most crowdsourcing-based studies in public health have often equated majority vote with quality, the results of our study using a truth set of 9000 manually labeled tweets showed that consensus-based inference models mask underlying uncertainty in data and overlook the importance of task meta-information. Our evaluations across 3 physical activity, sedentary behavior, and sleep quality data sets showed that truth inference is a context-sensitive process, and none of the methods studied in this paper were consistently superior to others in predicting the truth label. We also found that the performance of the ML models trained on crowd-labeled data was sensitive to the quality of these labels, and poor-quality labels led to incorrect assessment of these models. Finally, we have provided a set of practical recommendations to improve the quality and reliability of crowdsourced data. Conclusions Our findings indicate the importance of the quality of crowd-generated labels in developing ML models designed for decision-making purposes, such as public health surveillance decisions. A combination of inference models outlined and analyzed in this study could be used to quantitatively measure and improve the quality of crowd-generated labels for training ML models.
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Affiliation(s)
- Zahra Shakeri Hossein Abad
- Department of Biomedical Informatics, Harvard Medical School, Harvard University, Boston, MA, United States.,Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Gregory P Butler
- Centre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, ON, Canada
| | - Wendy Thompson
- Centre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, ON, Canada
| | - Joon Lee
- Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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10
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Trevino J, Malik S, Schmidt M. Integrating Google Trends Search Engine Query Data Into Adult Emergency Department Volume Forecasting: Infodemiology Study. JMIR INFODEMIOLOGY 2022; 2:e32386. [PMID: 37113800 PMCID: PMC10014085 DOI: 10.2196/32386] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/05/2021] [Accepted: 12/07/2021] [Indexed: 04/29/2023]
Abstract
Background The search for health information from web-based resources raises opportunities to inform the service operations of health care systems. Google Trends search query data have been used to study public health topics, such as seasonal influenza, suicide, and prescription drug abuse; however, there is a paucity of literature using Google Trends data to improve emergency department patient-volume forecasting. Objective We assessed the ability of Google Trends search query data to improve the performance of adult emergency department daily volume prediction models. Methods Google Trends search query data related to chief complaints and health care facilities were collected from Chicago, Illinois (July 2015 to June 2017). We calculated correlations between Google Trends search query data and emergency department daily patient volumes from a tertiary care adult hospital in Chicago. A baseline multiple linear regression model of emergency department daily volume with traditional predictors was augmented with Google Trends search query data; model performance was measured using mean absolute error and mean absolute percentage error. Results There were substantial correlations between emergency department daily volume and Google Trends "hospital" (r=0.54), combined terms (r=0.50), and "Northwestern Memorial Hospital" (r=0.34) search query data. The final Google Trends data-augmented model included the predictors Combined 3-day moving average and Hospital 3-day moving average and performed better (mean absolute percentage error 6.42%) than the final baseline model (mean absolute percentage error 6.67%)-an improvement of 3.1%. Conclusions The incorporation of Google Trends search query data into an adult tertiary care hospital emergency department daily volume prediction model modestly improved model performance. Further development of advanced models with comprehensive search query terms and complementary data sources may improve prediction performance and could be an avenue for further research.
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Affiliation(s)
- Jesus Trevino
- Department of Emergency Medicine The George Washington University School of Medicine & Health Sciences Washington, DC United States
| | - Sanjeev Malik
- Department of Emergency Medicine Northwestern University Feinberg School of Medicine Chicago, IL United States
| | - Michael Schmidt
- Department of Emergency Medicine Northwestern University Feinberg School of Medicine Chicago, IL United States
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Deiner MS, Seitzman GD, Kaur G, McLeod SD, Chodosh J, Lietman TM, Porco TC. Sustained Reductions in Online Search Interest for Communicable Eye and Other Conditions During the COVID-19 Pandemic: Infodemiology Study. JMIR INFODEMIOLOGY 2022; 2:e31732. [PMID: 35320981 PMCID: PMC8931841 DOI: 10.2196/31732] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 01/26/2022] [Accepted: 02/16/2022] [Indexed: 12/20/2022]
Abstract
Background In a prior study at the start of the pandemic, we reported reduced numbers of Google searches for the term “conjunctivitis” in the United States in March and April 2020 compared with prior years. As one explanation, we conjectured that reduced information-seeking may have resulted from social distancing reducing contagious conjunctivitis cases. Here, after 1 year of continued implementation of social distancing, we asked if there have been persistent reductions in searches for “conjunctivitis,” and similarly for other communicable disease terms, compared to control terms. Objective The aim of this study was to determine if reduction in searches in the United States for terms related to conjunctivitis and other common communicable diseases occurred in the spring-winter season of the COVID-19 pandemic, and to compare this outcome to searches for terms representing noncommunicable conditions, COVID-19, and to seasonality. Methods Weekly relative search frequency volume data from Google Trends for 68 search terms in English for the United States were obtained for the weeks of March 2011 through February 2021. Terms were classified a priori as 16 terms related to COVID-19, 29 terms representing communicable conditions, and 23 terms representing control noncommunicable conditions. To reduce bias, all analyses were performed while masked to term names, classifications, and locations. To test for the significance of changes during the pandemic, we detrended and compared postpandemic values to those expected based on prepandemic trends, per season, computing one- and two-sided P values. We then compared these P values between term groups using Wilcoxon rank-sum and Fisher exact tests to assess if non-COVID-19 terms representing communicable diseases were more likely to show significant reductions in searches in 2020-2021 than terms not representing such diseases. We also assessed any relationship between a term’s seasonality and a reduced search trend for the term in 2020-2021 seasons. P values were subjected to false discovery rate correction prior to reporting. Data were then unmasked. Results Terms representing conjunctivitis and other communicable conditions showed a sustained reduced search trend in the first 4 seasons of the 2020-2021 COVID-19 pandemic compared to prior years. In comparison, the search for noncommunicable condition terms was significantly less reduced (Wilcoxon and Fisher exact tests, P<.001; summer, autumn, winter). A significant correlation was also found between reduced search for a term in 2020-2021 and seasonality of that term (Theil-Sen, P<.001; summer, autumn, winter). Searches for COVID-19–related conditions were significantly elevated compared to those in prior years, and searches for influenza-related terms were significantly lower than those for prior years in winter 2020-2021 (P<.001). Conclusions We demonstrate the low-cost and unbiased use of online search data to study how a wide range of conditions may be affected by large-scale interventions or events such as social distancing during the COVID-19 pandemic. Our findings support emerging clinical evidence implicating social distancing and the COVID-19 pandemic in the reduction of communicable disease and on ocular conditions.
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Affiliation(s)
- Michael S Deiner
- Francis I Proctor Foundation University of California San Francisco San Francisco, CA United States.,Department of Ophthalmology University of California San Francisco San Francisco, CA United States
| | - Gerami D Seitzman
- Francis I Proctor Foundation University of California San Francisco San Francisco, CA United States.,Department of Ophthalmology University of California San Francisco San Francisco, CA United States
| | - Gurbani Kaur
- School of Medicine University of California San Francisco San Francisco, CA United States
| | - Stephen D McLeod
- Francis I Proctor Foundation University of California San Francisco San Francisco, CA United States.,Department of Ophthalmology University of California San Francisco San Francisco, CA United States
| | - James Chodosh
- Department of Ophthalmology Massachusetts Eye and Ear Harvard Medical School Boston, MA United States
| | - Thomas M Lietman
- Francis I Proctor Foundation University of California San Francisco San Francisco, CA United States.,Department of Ophthalmology University of California San Francisco San Francisco, CA United States.,Department of Epidemiology and Biostatistics Global Health Sciences University of California San Francisco San Francisco, CA United States
| | - Travis C Porco
- Francis I Proctor Foundation University of California San Francisco San Francisco, CA United States.,Department of Ophthalmology University of California San Francisco San Francisco, CA United States.,Department of Epidemiology and Biostatistics Global Health Sciences University of California San Francisco San Francisco, CA United States
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12
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Garett R, Young SD. Digital Public Health Surveillance Tools for Alcohol Use and HIV Risk Behaviors. AIDS Behav 2021; 25:333-338. [PMID: 33730254 PMCID: PMC7966886 DOI: 10.1007/s10461-021-03221-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/08/2021] [Indexed: 11/25/2022]
Abstract
There is a need for real-time and predictive data on alcohol use both broadly and specific to HIV. However, substance use and HIV data often suffer from lag times in reporting as they are typically measured from surveys, clinical case visits and other methods requiring extensive time for collection and analysis. Social big data might help to address this problem and be used to provide near real-time assessments of people's alcohol use and/or alcohol. This manuscript describes three types of social data sources (i.e., social media data, internet search data, and wearable device data) that might be used in surveillance of alcohol and HIV, and then discusses the implications and potential of implementing them as additional tools for public health surveillance.
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Affiliation(s)
- Renee Garett
- ElevateU, LLC; and Department of Informatics, University of California, Irvine, CA, USA
| | - Sean D Young
- Department of Emergency Medicine, University of California, Irvine, Irvine, CA, USA.
- University of California Institute for Prediction Technology, Department of Informatics, University of California, Irvine, Bren Hall, Irvine, CA, 6091, USA.
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13
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Chartier KG, Guidry JPD, Lee CA, Buckley TD. At home and online during the early months of the COVID-19 pandemic and the relationship to alcohol consumption in a national sample of U.S. adults. PLoS One 2021; 16:e0259947. [PMID: 34784402 PMCID: PMC8594812 DOI: 10.1371/journal.pone.0259947] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 10/29/2021] [Indexed: 01/12/2023] Open
Abstract
Introduction The current study aimed to understand the links between social media use and alcohol consumption during the early months of the COVID-19 pandemic. Method Data were from the national Understanding American Study, a probability-based Internet panel weighted to represent the U.S. population. Subjects (N = 5874; 51% female) were adults, 18 years and older, who completed a March survey (wave 1) and a follow-up survey one month later (wave 3). Analyses assessed the relationships of social media use at wave 1 with wave 3 alcohol use frequency, accounting for wave 1 alcohol use frequency and the sociodemographic characteristics of the sample. Two alcohol use change variables were also assessed as outcomes–increased and decreased alcohol use between waves. We considered the effect of work status changes (working/studying from home and job loss) as potential moderators. Results Twitter and Instagram users and users of multiple social media platforms, but not Facebook users, drank more frequently at wave 3. The results were similar when assessing relationships between social media use and increased alcohol use between waves. For Instagram users, more frequent alcohol use at wave 3 was at least partially attributed to drinking frequency at wave 1. Additionally, working/studying from home at wave 3 and employment (rather than job loss) were associated with greater consumption. The interaction effect between Twitter use and working/studying from home was statistically significant in association with alcohol use frequency at wave 3, as was the interaction effect between using multiple platforms and working/studying from home in association with decreased alcohol use between waves. Discussion Exposure to content about COVID-19 and increased alcohol consumption during the pandemic may have contributed to more frequent alcohol use for some social media users. The study of public health messaging via social media to change alcohol use behaviors during traumatic events is warranted.
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Affiliation(s)
- Karen G Chartier
- School of Social Work and Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Jeanine P D Guidry
- Robertson School of Media and Culture, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Catherine A Lee
- Schar School of Policy and Government, George Mason University, Fairfax, Virginia, United States of America
| | - Thomas D Buckley
- School of Social Work, Virginia Commonwealth University, Richmond, Virginia, United States of America
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14
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Kostkova P, Saigí-Rubió F, Eguia H, Borbolla D, Verschuuren M, Hamilton C, Azzopardi-Muscat N, Novillo-Ortiz D. Data and Digital Solutions to Support Surveillance Strategies in the Context of the COVID-19 Pandemic. Front Digit Health 2021; 3:707902. [PMID: 34713179 PMCID: PMC8522016 DOI: 10.3389/fdgth.2021.707902] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 06/30/2021] [Indexed: 12/23/2022] Open
Abstract
Background: In order to prevent spread and improve control of infectious diseases, public health experts need to closely monitor human and animal populations. Infectious disease surveillance is an established, routine data collection process essential for early warning, rapid response, and disease control. The quantity of data potentially useful for early warning and surveillance has increased exponentially due to social media and other big data streams. Digital epidemiology is a novel discipline that includes harvesting, analysing, and interpreting data that were not initially collected for healthcare needs to enhance traditional surveillance. During the current COVID-19 pandemic, the importance of digital epidemiology complementing traditional public health approaches has been highlighted. Objective: The aim of this paper is to provide a comprehensive overview for the application of data and digital solutions to support surveillance strategies and draw implications for surveillance in the context of the COVID-19 pandemic and beyond. Methods: A search was conducted in PubMed databases. Articles published between January 2005 and May 2020 on the use of digital solutions to support surveillance strategies in pandemic settings and health emergencies were evaluated. Results: In this paper, we provide a comprehensive overview of digital epidemiology, available data sources, and components of 21st-century digital surveillance, early warning and response, outbreak management and control, and digital interventions. Conclusions: Our main purpose was to highlight the plausible use of new surveillance strategies, with implications for the COVID-19 pandemic strategies and then to identify opportunities and challenges for the successful development and implementation of digital solutions during non-emergency times of routine surveillance, with readiness for early-warning and response for future pandemics. The enhancement of traditional surveillance systems with novel digital surveillance methods opens a direction for the most effective framework for preparedness and response to future pandemics.
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Affiliation(s)
- Patty Kostkova
- UCL Centre for Digital Public Health in Emergencies (dPHE), Institute for Risk and Disaster Reduction, University College London, London, United Kingdom
| | - Francesc Saigí-Rubió
- Faculty of Health Sciences, Universitat Oberta de Catalunya, Barcelona, Spain.,Interdisciplinary Research Group on ICTs, Barcelona, Spain
| | - Hans Eguia
- Faculty of Health Sciences, Universitat Oberta de Catalunya, Barcelona, Spain.,SEMERGEN New Technologies Working Group, Madrid, Spain
| | - Damian Borbolla
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States
| | - Marieke Verschuuren
- Division of Country Health Policies and Systems, Regional Office for Europe, World Health Organization, Copenhagen, Denmark
| | - Clayton Hamilton
- Division of Country Health Policies and Systems, Regional Office for Europe, World Health Organization, Copenhagen, Denmark
| | - Natasha Azzopardi-Muscat
- Division of Country Health Policies and Systems, Regional Office for Europe, World Health Organization, Copenhagen, Denmark
| | - David Novillo-Ortiz
- Division of Country Health Policies and Systems, Regional Office for Europe, World Health Organization, Copenhagen, Denmark
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15
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Mukka M, Pesälä S, Hammer C, Mustonen P, Jormanainen V, Pelttari H, Kaila M, Helve O. Analyzing citizens' and healthcare professionals' searches for smell/taste disorders and coronavirus in Finland during the COVID-19 pandemic: Infodemiological approach using database logs. JMIR Public Health Surveill 2021; 7:e31961. [PMID: 34727525 PMCID: PMC8653973 DOI: 10.2196/31961] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 10/12/2021] [Accepted: 10/28/2021] [Indexed: 11/25/2022] Open
Abstract
Background The COVID-19 pandemic has prevailed over a year, and log and register data on coronavirus have been utilized to establish models for detecting the pandemic. However, many sources contain unreliable health information on COVID-19 and its symptoms, and platforms cannot characterize the users performing searches. Prior studies have assessed symptom searches from general search engines (Google/Google Trends). Little is known about how modeling log data on smell/taste disorders and coronavirus from the dedicated internet databases used by citizens and health care professionals (HCPs) could enhance disease surveillance. Our material and method provide a novel approach to analyze web-based information seeking to detect infectious disease outbreaks. Objective The aim of this study was (1) to assess whether citizens’ and professionals’ searches for smell/taste disorders and coronavirus relate to epidemiological data on COVID-19 cases, and (2) to test our negative binomial regression modeling (ie, whether the inclusion of the case count could improve the model). Methods We collected weekly log data on searches related to COVID-19 (smell/taste disorders, coronavirus) between December 30, 2019, and November 30, 2020 (49 weeks). Two major medical internet databases in Finland were used: Health Library (HL), a free portal aimed at citizens, and Physician’s Database (PD), a database widely used among HCPs. Log data from databases were combined with register data on the numbers of COVID-19 cases reported in the Finnish National Infectious Diseases Register. We used negative binomial regression modeling to assess whether the case numbers could explain some of the dynamics of searches when plotting database logs. Results We found that coronavirus searches drastically increased in HL (0 to 744,113) and PD (4 to 5375) prior to the first wave of COVID-19 cases between December 2019 and March 2020. Searches for smell disorders in HL doubled from the end of December 2019 to the end of March 2020 (2148 to 4195), and searches for taste disorders in HL increased from mid-May to the end of November (0 to 1980). Case numbers were significantly associated with smell disorders (P<.001) and taste disorders (P<.001) in HL, and with coronavirus searches (P<.001) in PD. We could not identify any other associations between case numbers and searches in either database. Conclusions Novel infodemiological approaches could be used in analyzing database logs. Modeling log data from web-based sources was seen to improve the model only occasionally. However, search behaviors among citizens and professionals could be used as a supplementary source of information for infectious disease surveillance. Further research is needed to apply statistical models to log data of the dedicated medical databases.
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Affiliation(s)
- Milla Mukka
- University of Helsinki, Tukholmankatu 8B, Helsinki, FI
| | - Samuli Pesälä
- University of Helsinki, Tukholmankatu 8B, Helsinki, FI.,Epidemiological Operations Unit, Helsinki, FI
| | - Charlotte Hammer
- European Programme for Intervention Epidemiology training, Solna, SE.,Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, FI
| | | | - Vesa Jormanainen
- University of Helsinki, Tukholmankatu 8B, Helsinki, FI.,Finnish Institute for Health and Welfare, Helsinki, FI
| | | | - Minna Kaila
- Clinicum, University of Helsinki, Helsinki, FI
| | - Otto Helve
- Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, FI.,Children's Hospital, Pediatric Research Center, University of Helsinki & Helsinki University Hospital, Helsinki, FI
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16
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Yuan K, Huang G, Wang L, Wang T, Liu W, Jiang H, Yang AC. Predicting Norovirus in the United States Using Google Trends: Infodemiology Study. J Med Internet Res 2021; 23:e24554. [PMID: 34586079 PMCID: PMC8515228 DOI: 10.2196/24554] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 02/26/2021] [Accepted: 07/05/2021] [Indexed: 12/23/2022] Open
Abstract
Background Norovirus is a contagious disease. The transmission of norovirus spreads quickly and easily in various ways. Because effective methods to prevent or treat norovirus have not been discovered, it is important to rapidly recognize and report norovirus outbreaks in the early phase. Internet search has been a useful method for people to access information immediately. With the precise record of internet search trends, internet search has been a useful tool to manifest infectious disease outbreaks. Objective In this study, we tried to discover the correlation between internet search terms and norovirus infection. Methods The internet search trend data of norovirus were obtained from Google Trends. We used cross-correlation analysis to discover the temporal correlation between norovirus and other terms. We also used multiple linear regression with the stepwise method to recognize the most important predictors of internet search trends and norovirus. In addition, we evaluated the temporal correlation between actual norovirus cases and internet search terms in New York, California, and the United States as a whole. Results Some Google search terms such as gastroenteritis, watery diarrhea, and stomach bug coincided with norovirus Google Trends. Some Google search terms such as contagious, travel, and party presented earlier than norovirus Google Trends. Some Google search terms such as dehydration, bar, and coronavirus presented several months later than norovirus Google Trends. We found that fever, gastroenteritis, poison, cruise, wedding, and watery diarrhea were important factors correlated with norovirus Google Trends. In actual norovirus cases from New York, California, and the United States as a whole, some Google search terms presented with, earlier, or later than actual norovirus cases. Conclusions Our study provides novel strategy-based internet search evidence regarding the epidemiology of norovirus.
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Affiliation(s)
- Kai Yuan
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Guangrui Huang
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Lepeng Wang
- School of Humanities, Beijing University of Chinese Medicine, Beijing, China
| | - Ting Wang
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Wenbin Liu
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Haixu Jiang
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Albert C Yang
- Digital Medicine Center, National Yang Ming Chiao Tung University, Taiwan, Republic of China.,Department of Medical Research, Taipei Veterans General Hospital, Taiwan, Republic of China.,Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, United States
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17
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Gabarron E, Rivera-Romero O, Miron-Shatz T, Grainger R, Denecke K. Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review. Yearb Med Inform 2021; 30:200-209. [PMID: 33882600 PMCID: PMC8432992 DOI: 10.1055/s-0041-1726486] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVES Using participatory health informatics (PHI) to detect disease outbreaks or learn about pandemics has gained interest in recent years. However, the role of PHI in understanding and managing pandemics, citizens' role in this context, and which methods are relevant for collecting and processing data are still unclear, as is which types of data are relevant. This paper aims to clarify these issues and explore the role of PHI in managing and detecting pandemics. METHODS Through a literature review we identified studies that explore the role of PHI in detecting and managing pandemics. Studies from five databases were screened: PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature), IEEE Xplore, ACM (Association for Computing Machinery) Digital Library, and Cochrane Library. Data from studies fulfilling the eligibility criteria were extracted and synthesized narratively. RESULTS Out of 417 citations retrieved, 53 studies were included in this review. Most research focused on influenza-like illnesses or COVID-19 with at least three papers on other epidemics (Ebola, Zika or measles). The geographic scope ranged from global to concentrating on specific countries. Multiple processing and analysis methods were reported, although often missing relevant information. The majority of outcomes are reported for two application areas: crisis communication and detection of disease outbreaks. CONCLUSIONS For most diseases, the small number of studies prevented reaching firm conclusions about the utility of PHI in detecting and monitoring these disease outbreaks. For others, e.g., COVID-19, social media and online search patterns corresponded to disease patterns, and detected disease outbreak earlier than conventional public health methods, thereby suggesting that PHI can contribute to disease and pandemic monitoring.
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Affiliation(s)
- Elia Gabarron
- Norwegian Centre for E-health Research, University Hospital of North Norway, Troms⊘, Norway
| | | | - Talya Miron-Shatz
- Faculty of Business Administration, Ono Academic College, Israel
- Winton Centre for Risk and Evidence Communication, Cambridge University, England
| | - Rebecca Grainger
- Department of Medicine, University of Otago, Wellington, New Zealand
| | - Kerstin Denecke
- Institute for Medical Informatics, Bern University of Applied Sciences, Bern, Switzerland
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18
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Gao Z, Fujita S, Shimizu N, Liew K, Murayama T, Yada S, Wakamiya S, Aramaki E. Measuring Public Concern About COVID-19 in Japanese Internet Users Through Search Queries: Infodemiological Study. JMIR Public Health Surveill 2021; 7:e29865. [PMID: 34174781 PMCID: PMC8294121 DOI: 10.2196/29865] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 06/01/2021] [Accepted: 06/13/2021] [Indexed: 01/19/2023] Open
Abstract
Background COVID-19 has disrupted lives and livelihoods and caused widespread panic worldwide. Emerging reports suggest that people living in rural areas in some countries are more susceptible to COVID-19. However, there is a lack of quantitative evidence that can shed light on whether residents of rural areas are more concerned about COVID-19 than residents of urban areas. Objective This infodemiology study investigated attitudes toward COVID-19 in different Japanese prefectures by aggregating and analyzing Yahoo! JAPAN search queries. Methods We measured COVID-19 concerns in each Japanese prefecture by aggregating search counts of COVID-19–related queries of Yahoo! JAPAN users and data related to COVID-19 cases. We then defined two indices—the localized concern index (LCI) and localized concern index by patient percentage (LCIPP)—to quantitatively represent the degree of concern. To investigate the impact of emergency declarations on people's concerns, we divided our study period into three phases according to the timing of the state of emergency in Japan: before, during, and after. In addition, we evaluated the relationship between the LCI and LCIPP in different prefectures by correlating them with prefecture-level indicators of urbanization. Results Our results demonstrated that the concerns about COVID-19 in the prefectures changed in accordance with the declaration of the state of emergency. The correlation analyses also indicated that the differentiated types of public concern measured by the LCI and LCIPP reflect the prefectures’ level of urbanization to a certain extent (ie, the LCI appears to be more suitable for quantifying COVID-19 concern in urban areas, while the LCIPP seems to be more appropriate for rural areas). Conclusions We quantitatively defined Japanese Yahoo users’ concerns about COVID-19 by using the search counts of COVID-19–related search queries. Our results also showed that the LCI and LCIPP have external validity.
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Affiliation(s)
- Zhiwei Gao
- Social Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
| | | | | | - Kongmeng Liew
- Social Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
| | - Taichi Murayama
- Social Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
| | - Shuntaro Yada
- Social Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
| | - Shoko Wakamiya
- Social Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
| | - Eiji Aramaki
- Social Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
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19
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Williams CYK, Ferreira AF. Impact of political partisanship on public interest in infection prevention measures in the United States: An infodemiological study. Prev Med Rep 2021; 23:101493. [PMID: 34367886 PMCID: PMC8326196 DOI: 10.1016/j.pmedr.2021.101493] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 06/19/2021] [Accepted: 07/10/2021] [Indexed: 11/25/2022] Open
Abstract
There has been conflicting public messaging from government and state officials about recommended health behaviours during the COVID-19 pandemic. We examined whether differences in political affiliation influences the public's interest in infection prevention measures in the United States. State-specific data on public search interest in four key infection prevention measures (Quarantine, Social distancing, Hand washing and Masks) were obtained from Google Trends for the period 1 January 2020 to 12 December 2020. Political affiliation was ascertained based on the 2020 U.S. Presidential election results and 2017 Cook Partisan Voting Index. Spearman's rank, partial correlation, and multiple regression analyses were conducted to compare political partisanship with public interest in infection prevention measures and overall case rate per 100 000 population. Statistical analysis was performed in R version 4.0.3. The COVID-19 pandemic has led to significantly increased public interest in infection prevention measures. The greater the support for the Democratic Party, the greater the search interest in all four measures analysed. Political partisanship was most highly correlated with searches relating to Quarantine (ρ = 0.79, p < 0.001), followed by Social distancing (ρ = 0.71, p < 0.001), Hand washing (ρ = 0.69, p < 0.001), and Masks (ρ = 0.66, p < 0.001). These findings were robust to using two different partisanship measures, controlling for state-level demographic variables, different pandemic onset dates, and using exact rather than Topic search methods. This partisan divide among the American people has important health implications that must be better addressed. We call for clear, bipartisan support of simple public health advice to combat the continued SARS-CoV-2 spread across the USA.
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Affiliation(s)
- Christopher Y K Williams
- University of Cambridge, School of Clinical Medicine, Addenbrooke's Hospital, Hills Rd, Cambridge CB2 0SP, United Kingdom
| | - Alice F Ferreira
- University of Cambridge, School of Clinical Medicine, Addenbrooke's Hospital, Hills Rd, Cambridge CB2 0SP, United Kingdom
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20
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Wang P, Xu Q, Cao RR, Deng FY, Lei SF. Global Public Interests and Dynamic Trends in Osteoporosis From 2004 to 2019: Infodemiology Study. J Med Internet Res 2021; 23:e25422. [PMID: 36260400 PMCID: PMC8406103 DOI: 10.2196/25422] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 12/22/2020] [Accepted: 04/27/2021] [Indexed: 12/26/2022] Open
Abstract
Background With the prolonging of human life expectancy and subsequent population aging, osteoporosis (OP) has become an important public health issue. Objective This study aimed to understand the global public search interests and dynamic trends in “osteoporosis” using the data derived from Google Trends. Methods An online search was performed using the term “osteoporosis” in Google Trends from January 1, 2004, to December 31, 2019, under the category “Health.” Cosinor analysis was used to test the seasonality of relative search volume (RSV) for “osteoporosis.” An analysis was conducted to investigate the public search topic rising in RSV for “osteoporosis.” Results There was a descending trend of global RSV for “osteoporosis” from January 2004 to December 2014, and a slowly increasing trend from January 2015 to December 2019. Cosinor analysis showed significant seasonal variations in global RSV for “osteoporosis” (P=.01), with a peak in March and a trough in September. In addition, similar decreasing trends of RSV for “osteoporosis” were found in Australia, New Zealand, Ireland, and Canada from January 2004 to December 2019. Cosinor test revealed significant seasonal variations in RSV for “osteoporosis” in Australia, New Zealand, Canada, Ireland, UK, and USA (all P<.001). Furthermore, public search rising topics related to “osteoporosis” included denosumab, fracture risk assessment tool, bone density, osteopenia, osteoarthritis, and risk factor. Conclusions Our study provided evidence about the public search interest and dynamic trends in OP using web-based data, which would be helpful for public health and policy making.
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Affiliation(s)
- Peng Wang
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University Medical College, Soochow University, Suzhou, China
| | - Qing Xu
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University Medical College, Soochow University, Suzhou, China
| | - Rong-Rong Cao
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University Medical College, Soochow University, Suzhou, China
| | - Fei-Yan Deng
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University Medical College, Soochow University, Suzhou, China
| | - Shu-Feng Lei
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University Medical College, Soochow University, Suzhou, China
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21
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Li J, Sia CL, Chen Z, Huang W. Enhancing Influenza Epidemics Forecasting Accuracy in China with Both Official and Unofficial Online News Articles, 2019-2020. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18126591. [PMID: 34207479 PMCID: PMC8296334 DOI: 10.3390/ijerph18126591] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 06/05/2021] [Accepted: 06/15/2021] [Indexed: 11/16/2022]
Abstract
Real-time online data sources have contributed to timely and accurate forecasting of influenza activities while also suffered from instability and linguistic noise. Few previous studies have focused on unofficial online news articles, which are abundant in their numbers, rich in information, and relatively low in noise. This study examined whether monitoring both official and unofficial online news articles can improve influenza activity forecasting accuracy during influenza outbreaks. Data were retrieved from a Chinese commercial online platform and the website of the Chinese National Influenza Center. We modeled weekly fractions of influenza-related online news articles and compared them against weekly influenza-like illness (ILI) rates using autoregression analyses. We retrieved 153,958,695 and 149,822,871 online news articles focusing on the south and north of mainland China separately from 6 October 2019 to 17 May 2020. Our model based on online news articles could significantly improve the forecasting accuracy, compared to other influenza surveillance models based on historical ILI rates (p = 0.002 in the south; p = 0.000 in the north) or adding microblog data as an exogenous input (p = 0.029 in the south; p = 0.000 in the north). Our finding also showed that influenza forecasting based on online news articles could be 1-2 weeks ahead of official ILI surveillance reports. The results revealed that monitoring online news articles could supplement traditional influenza surveillance systems, improve resource allocation, and offer models for surveillance of other emerging diseases.
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Affiliation(s)
- Jingwei Li
- School of Management, Xi’an Jiaotong University, Xi’an 710049, China;
- Department of Information Systems, City University of Hong Kong, Hong Kong 999077, China;
| | - Choon-Ling Sia
- Department of Information Systems, City University of Hong Kong, Hong Kong 999077, China;
| | - Zhuo Chen
- College of Public Health, University of Georgia, Athens, GA 30602, USA;
- School of Economics, University of Nottingham Ningbo China, Ningbo 315000, China
| | - Wei Huang
- College of Business, Southern University of Science and Technology, Shenzhen 518000, China
- Correspondence:
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22
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Naik H, Johnson MDD, Johnson MR. Internet Interest in Colon Cancer Following the Death of Chadwick Boseman: Infoveillance Study. J Med Internet Res 2021; 23:e27052. [PMID: 34128824 PMCID: PMC8277405 DOI: 10.2196/27052] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 05/13/2021] [Accepted: 05/24/2021] [Indexed: 12/26/2022] Open
Abstract
Background Compared with White Americans, Black Americans have higher colon cancer mortality rates but lower up-to-date screening rates. Chadwick Boseman was a prominent Black American actor who died of colon cancer on August 28, 2020. As announcements of celebrity diagnoses often result in increased awareness, Boseman’s death may have resulted in greater interest in colon cancer on the internet, particularly among Black Americans. Objective This study aims to quantify the impact of Chadwick Boseman’s death on web-based search interest in colon cancer and determine whether there was an increase in interest in regions of the United States with a greater proportion of Black Americans. Methods We conducted an infoveillance study using Google Trends (GT) and Wikipedia pageview analysis. Using an autoregressive integrated moving average algorithm, we forecasted the weekly relative search volume (RSV) for GT search topics and terms related to colon cancer that would have been expected had his death not occurred and compared it with observed RSV data. This analysis was also conducted for the number of page views on the Wikipedia page for colorectal cancer. We then delineated GT RSV data for the term colon cancer for states and metropolitan areas in the United States and determined how the RSV values for these regions correlated with the percentage of Black Americans in that region. Differences in these correlations before and after Boseman’s death were compared to determine whether there was a shift in the racial demographics of the individuals conducting the searches. Results The observed RSVs for the topics colorectal cancer and colon cancer screening increased by 598% and 707%, respectively, and were on average 121% (95% CI 72%-193%) and 256% (95% CI 35%-814%) greater than expected during the first 3 months following Boseman’s death. Daily Wikipedia page view volume during the 2 months following Boseman’s death was on average 1979% (95% CI 1375%-2894%) greater than expected, and it was estimated that this represented 547,354 (95% CI 497,708-585,167) excess Wikipedia page views. Before Boseman’s death, there were negative correlations between the percentage of Black Americans living in a state or metropolitan area and the RSV for colon cancer in that area (r=−0.18 and r=−0.05, respectively). However, in the 2 weeks following his death, there were positive correlations between the RSV for colon cancer and the percentage of Black Americans per state and per metropolitan area (r=0.73 and r=0.33, respectively). These changes persisted for 4 months and were all statistically significant (P<.001). Conclusions There was a significant increase in web-based activity related to colon cancer following Chadwick Boseman’s death, particularly in areas with a higher proportion of Black Americans. This reflects a heightened public awareness that can be leveraged to further educate the public.
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Affiliation(s)
- Hiten Naik
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
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23
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Liu W, Wei Z, Cheng X, Pang R, Zhang H, Li G. Public Interest in Cosmetic Surgical and Minimally Invasive Plastic Procedures During the COVID-19 Pandemic: Infodemiology Study of Twitter Data. J Med Internet Res 2021; 23:e23970. [PMID: 33608248 PMCID: PMC7968479 DOI: 10.2196/23970] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 01/28/2021] [Accepted: 02/18/2021] [Indexed: 12/21/2022] Open
Abstract
Background The unprecedented COVID-19 pandemic has brought drastic changes to the field of plastic surgery. It is critical for stakeholders in this field to identify the changes in public interest in plastic procedures to be adequately prepared to meet the challenges of the pandemic. Objective The aim of this study is to examine tweets related to the public interest in plastic procedures during the COVID-19 pandemic and to help stakeholders in the field of plastic surgery adjust their practices and sustain their operations during the current difficult situation of the pandemic. Methods Using a web crawler, 73,963 publicly accessible tweets about the most common cosmetic surgical and minimally invasive plastic procedures were collected. The tweets were grouped into three phases, and the tweeting frequencies and Google Trends indices were examined. Tweeting frequency, sentiment, and word frequency analyses were performed with Python modules. Results Tweeting frequency increased by 24.0% in phase 2 and decreased by 9.1% in phase 3. Tweets about breast augmentation, liposuction, and abdominoplasty (“tummy tuck”) procedures consecutively increased over the three phases of the pandemic. Interest in Botox and chemical peel procedures revived first when the lockdown was lifted. The COVID-19 pandemic was associated with a negative impact on public sentiment about plastic procedures. The word frequency pattern significantly changed after phase 1 and then remained relatively stable. Conclusions According to Twitter data, the public maintained their interest in plastic procedures during the COVID-19 pandemic. Stakeholders should consider refocusing on breast augmentation, liposuction, and abdominoplasty procedures during the current phase of the pandemic. In the case of a second wave of COVID-19, stakeholders should prepare for a temporary surge of Botox and chemical peel procedures.
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Affiliation(s)
- Wenhui Liu
- Plastic and Reconstructive Surgery, First Affiliated Hospital, Zhengzhou University, Zhengzhou, China
| | - Zhiru Wei
- Plastic and Reconstructive Surgery, First Affiliated Hospital, Zhengzhou University, Zhengzhou, China
| | - Xu Cheng
- Plastic and Reconstructive Surgery, First Affiliated Hospital, Zhengzhou University, Zhengzhou, China
| | - Ran Pang
- Plastic and Reconstructive Surgery, First Affiliated Hospital, Zhengzhou University, Zhengzhou, China
| | - Han Zhang
- Plastic and Reconstructive Surgery, First Affiliated Hospital, Zhengzhou University, Zhengzhou, China
| | - Guangshuai Li
- Plastic and Reconstructive Surgery, First Affiliated Hospital, Zhengzhou University, Zhengzhou, China
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Shakeri Hossein Abad Z, Kline A, Sultana M, Noaeen M, Nurmambetova E, Lucini F, Al-Jefri M, Lee J. Digital public health surveillance: a systematic scoping review. NPJ Digit Med 2021; 4:41. [PMID: 33658681 PMCID: PMC7930261 DOI: 10.1038/s41746-021-00407-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 01/21/2021] [Indexed: 02/06/2023] Open
Abstract
The ubiquitous and openly accessible information produced by the public on the Internet has sparked an increasing interest in developing digital public health surveillance (DPHS) systems. We conducted a systematic scoping review in accordance with the PRISMA extension for scoping reviews to consolidate and characterize the existing research on DPHS and identify areas for further research. We used Natural Language Processing and content analysis to define the search strings and searched Global Health, Web of Science, PubMed, and Google Scholar from 2005 to January 2020 for peer-reviewed articles on DPHS, with extensive hand searching. Seven hundred fifty-five articles were included in this review. The studies were from 54 countries and utilized 26 digital platforms to study 208 sub-categories of 49 categories associated with 16 public health surveillance (PHS) themes. Most studies were conducted by researchers from the United States (56%, 426) and dominated by communicable diseases-related topics (25%, 187), followed by behavioural risk factors (17%, 131). While this review discusses the potentials of using Internet-based data as an affordable and instantaneous resource for DPHS, it highlights the paucity of longitudinal studies and the methodological and inherent practical limitations underpinning the successful implementation of a DPHS system. Little work studied Internet users' demographics when developing DPHS systems, and 39% (291) of studies did not stratify their results by geographic region. A clear methodology by which the results of DPHS can be linked to public health action has yet to be established, as only six (0.8%) studies deployed their system into a PHS context.
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Affiliation(s)
- Zahra Shakeri Hossein Abad
- Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
| | - Adrienne Kline
- Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Madeena Sultana
- Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Mohammad Noaeen
- Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Elvira Nurmambetova
- Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Filipe Lucini
- Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, AB, Canada
| | - Majed Al-Jefri
- Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Joon Lee
- Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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Huynh Dagher S, Lamé G, Hubiche T, Ezzedine K, Duong TA. The Influence of Media Coverage and Governmental Policies on Google Queries Related to COVID-19 Cutaneous Symptoms: Infodemiology Study. JMIR Public Health Surveill 2021; 7:e25651. [PMID: 33513563 PMCID: PMC7909455 DOI: 10.2196/25651] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 12/15/2020] [Accepted: 01/22/2021] [Indexed: 12/29/2022] Open
Abstract
Background During COVID-19, studies have reported the appearance of internet searches for disease symptoms before their validation by the World Health Organization. This suggested that monitoring of these searches with tools including Google Trends may help monitor the pandemic itself. In Europe and North America, dermatologists reported an unexpected outbreak of cutaneous acral lesions (eg, chilblain-like lesions) in April 2020. However, external factors such as public communications may also hinder the use of Google Trends as an infodemiology tool. Objective The study aimed to assess the impact of media announcements and lockdown enforcement on internet searches related to cutaneous acral lesions during the COVID-19 outbreak in 2020. Methods Two searches on Google Trends, including daily relative search volumes for (1) “toe” or “chilblains” and (2) “coronavirus,” were performed from January 1 to May 16, 2020, with the United States, the United Kingdom, France, Italy, Spain, and Germany as the countries of choice. The ratio of interest over time in “chilblains” and “coronavirus” was plotted. To assess the impact of lockdown enforcement and media coverage on these internet searches, we performed an interrupted time-series analysis for each country. Results The ratio of interest over time in “chilblains” to “coronavirus” showed a constant upward trend. In France, Italy, and the United Kingdom, lockdown enforcement was associated with a significant slope change for “chilblain” searches with a variation coefficient of 1.06 (SE 0.42) (P=0.01), 1.04 (SE 0.28) (P<.01), and 1.21 (SE 0.44) (P=0.01), respectively. After media announcements, these ratios significantly increased in France, Spain, Italy, and the United States with variation coefficients of 18.95 (SE 5.77) (P=.001), 31.31 (SE 6.31) (P<.001), 14.57 (SE 6.33) (P=.02), and 11.24 (SE 4.93) (P=.02), respectively, followed by a significant downward trend in France (–1.82 [SE 0.45]), Spain (–1.10 [SE 0.38]), and Italy (–0.93 [SE 0.33]) (P<.001, P=0.004, and P<.001, respectively). The adjusted R2 values were 0.311, 0.351, 0.325, and 0.305 for France, Spain, Italy, and the United States, respectively, suggesting an average correlation between time and the search volume; however, this correlation was weak for Germany and the United Kingdom. Conclusions To date, the association between chilblain-like lesions and COVID-19 remains controversial; however, our results indicate that Google queries of “chilblain” were highly influenced by media coverage and government policies, indicating that caution should be exercised when using Google Trends as a monitoring tool for emerging diseases.
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Affiliation(s)
- Solene Huynh Dagher
- Assistance Publique des Hôpitaux de Paris (AP-HP), Département de dermatologie, Hôpital Henri Mondor, Créteil, France
| | - Guillaume Lamé
- Laboratoire Génie Industriel, CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Thomas Hubiche
- Département de dermatologie, Centre hospitalier universitaire de Nice, Nice, France
| | - Khaled Ezzedine
- Assistance Publique des Hôpitaux de Paris (AP-HP), Département de dermatologie, Hôpital Henri Mondor, Créteil, France.,EA 7379, EpidermE, Université Paris-Est Créteil, Créteil, France
| | - Tu Anh Duong
- Assistance Publique des Hôpitaux de Paris (AP-HP), Département de dermatologie, Hôpital Henri Mondor, Créteil, France.,Chaire Avenir Santé numérique, Équipe 8 IMRB U955, INSERM, Université Paris-Est Créteil, Créteil, France
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26
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Use of "Social Media"-an Option for Spreading Awareness in Infection Prevention. CURRENT TREATMENT OPTIONS IN INFECTIOUS DISEASES 2021; 13:14-31. [PMID: 33519303 PMCID: PMC7826144 DOI: 10.1007/s40506-020-00244-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/26/2020] [Indexed: 11/24/2022]
Abstract
Purpose of review There is a need for enhanced adoption of infection prevention and control (IPC) practices in both healthcare settings and the entire community, more so during pandemics. The exponential increase in the use of social media (SM) has made it a powerful tool for creating awareness, education, training and community engagement on IPC. Here, we review how social media can be used effectively to implement strategies to combat public health issues especially vis-à-vis infection prevention and control. Recent findings According to the World Health Organization, 10% of patients get an infection whilst receiving care in healthcare institutions. Effective infection prevention and control measures can reduce healthcare-associated infections by at least 30%. Education and awareness play a vital role in implementation of infection prevention and control (IPC) strategies. Various studies show how social media has been used successfully in education and training activities, for awareness campaigns, community engagement, risk communications during outbreaks, disease surveillance and pharmacovigilance. Summary Infection prevention and control (IPC) is the need of the hour to mitigate transmission of disease in healthcare settings as well as in the community. SM is the fastest and most efficient way of communicating with the general population as well as health professionals. SM can help people take the right decisions and enable change in their behaviour patterns to introduce infection control practices.
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Sajjadi NB, Feldman K, Shepard S, Reddy AK, Torgerson T, Hartwell M, Vassar M. Public Interest and Behavior Change in the United States Regarding Colorectal Cancer Following the Death of Chadwick Boseman: Infodemiology Investigation of Internet Search Trends Nationally and in At-Risk Areas. JMIR INFODEMIOLOGY 2021; 1:e29387. [PMID: 37114199 PMCID: PMC10014084 DOI: 10.2196/29387] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/29/2021] [Accepted: 08/09/2021] [Indexed: 04/29/2023]
Abstract
Background Colorectal cancer (CRC) has the third highest cancer mortality rate in the United States. Enhanced screening has reduced mortality rates; however, certain populations remain at high risk, notably African Americans. Raising awareness among at-risk populations may lead to improved CRC outcomes. The influence of celebrity death and illness is an important driver of public awareness. As such, the death of actor Chadwick Boseman from CRC may have influenced CRC awareness. Objective We sought to assess the influence of Chadwick Boseman's death on public interest in CRC in the United States, evidenced by internet searches, website traffic, and donations to prominent cancer organizations. Methods We used an auto-regressive integrated moving average model to forecast Google searching trends for the topic "Colorectal cancer" in the United States. We performed bivariate and multivariable regressions on state-wise CRC incidence rate and percent Black population. We obtained data from the American Cancer Society (ACS) and the Colon Cancer Foundation (CCF) for information regarding changes in website traffic and donations. Results The expected national relative search volume (RSV) for colorectal cancer was 2.71 (95% CI 1.76-3.66), reflecting a 3590% (95% CI 2632%-5582%) increase compared to the expected values. With multivariable regression, the statewise RSV increased for each percent Black population by 1.09 (SE 0.18, P<.001), with 42% of the variance explained (P<.001). The American Cancer Society reported a 58,000% increase in CRC-related website traffic the weekend following Chadwick Boseman's death compared to the weekend before. The Colon Cancer Foundation reported a 331% increase in donations and a 144% increase in revenue in the month following Boseman's death compared to the month prior. Conclusions Our results suggest that Chadwick Boseman's death was associated with substantial increases in awareness of CRC. Increased awareness of CRC may support earlier detection and better prognoses.
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Affiliation(s)
- Nicholas B Sajjadi
- Office of Medical Student Research College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
| | - Kaylea Feldman
- Office of Medical Student Research College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
| | - Samuel Shepard
- Office of Medical Student Research College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
| | - Arjun K Reddy
- Office of Medical Student Research College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
| | - Trevor Torgerson
- Office of Medical Student Research College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
| | - Micah Hartwell
- Office of Medical Student Research College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
- Department of Psychiatry and Behavioral Sciences College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
| | - Matt Vassar
- Office of Medical Student Research College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
- Department of Psychiatry and Behavioral Sciences College of Osteopathic Medicine Oklahoma State University Center for Health Sciences Tulsa, OK United States
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COVID-19 predictability in the United States using Google Trends time series. Sci Rep 2020; 10:20693. [PMID: 33244028 PMCID: PMC7692493 DOI: 10.1038/s41598-020-77275-9] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 11/06/2020] [Indexed: 02/06/2023] Open
Abstract
During the unprecedented situation that all countries around the globe are facing due to the Coronavirus disease 2019 (COVID-19) pandemic, which has also had severe socioeconomic consequences, it is imperative to explore novel approaches to monitoring and forecasting regional outbreaks as they happen or even before they do so. To that end, in this paper, the role of Google query data in the predictability of COVID-19 in the United States at both national and state level is presented. As a preliminary investigation, Pearson and Kendall rank correlations are examined to explore the relationship between Google Trends data and COVID-19 data on cases and deaths. Next, a COVID-19 predictability analysis is performed, with the employed model being a quantile regression that is bias corrected via bootstrap simulation, i.e., a robust regression analysis that is the appropriate statistical approach to taking against the presence of outliers in the sample while also mitigating small sample estimation bias. The results indicate that there are statistically significant correlations between Google Trends and COVID-19 data, while the estimated models exhibit strong COVID-19 predictability. In line with previous work that has suggested that online real-time data are valuable in the monitoring and forecasting of epidemics and outbreaks, it is evident that such infodemiology approaches can assist public health policy makers in addressing the most crucial issues: flattening the curve, allocating health resources, and increasing the effectiveness and preparedness of their respective health care systems.
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29
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Mavragani A, Gkillas K. COVID-19 predictability in the United States using Google Trends time series. Sci Rep 2020. [PMID: 33244028 DOI: 10.1038/s41598‐020‐77275‐9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
During the unprecedented situation that all countries around the globe are facing due to the Coronavirus disease 2019 (COVID-19) pandemic, which has also had severe socioeconomic consequences, it is imperative to explore novel approaches to monitoring and forecasting regional outbreaks as they happen or even before they do so. To that end, in this paper, the role of Google query data in the predictability of COVID-19 in the United States at both national and state level is presented. As a preliminary investigation, Pearson and Kendall rank correlations are examined to explore the relationship between Google Trends data and COVID-19 data on cases and deaths. Next, a COVID-19 predictability analysis is performed, with the employed model being a quantile regression that is bias corrected via bootstrap simulation, i.e., a robust regression analysis that is the appropriate statistical approach to taking against the presence of outliers in the sample while also mitigating small sample estimation bias. The results indicate that there are statistically significant correlations between Google Trends and COVID-19 data, while the estimated models exhibit strong COVID-19 predictability. In line with previous work that has suggested that online real-time data are valuable in the monitoring and forecasting of epidemics and outbreaks, it is evident that such infodemiology approaches can assist public health policy makers in addressing the most crucial issues: flattening the curve, allocating health resources, and increasing the effectiveness and preparedness of their respective health care systems.
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Affiliation(s)
- Amaryllis Mavragani
- Department of Computing Science and Mathematics, Faculty of Natural Sciences, University of Stirling, Stirling, FK9 4LA, Scotland, UK.
| | - Konstantinos Gkillas
- Department of Management Science and Technology, University of Patras, Patras, Greece
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30
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van Heerden A, Young S. Use of social media big data as a novel HIV surveillance tool in South Africa. PLoS One 2020; 15:e0239304. [PMID: 33006979 PMCID: PMC7531824 DOI: 10.1371/journal.pone.0239304] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 09/03/2020] [Indexed: 01/06/2023] Open
Abstract
Sub-Saharan Africa has been heavily impacted by the HIV/AIDS epidemic. Social data (e.g., social media, internet search, wearable device, etc) show great promise assisting in public health and HIV surveillance. However, research on this topic has primarily focused in higher resource settings, such as the United States. It is especially important to study the prevalence and potential use of these data sources and tools in low- and middle-income countries (LMIC), such as Sub-Saharan Africa, which have been heavily impacted by the HIV epidemic, to determine the feasibility of using these technologies as surveillance and intervention tools. Accordingly, we 1) described the prevalence and characteristics of various social technologies within South Africa, 2) using Twitter, Instagram, and YouTube as a case study, analyzed the prevalence and patterns of social media use related to HIV risk in South Africa, and 3) mapped and statistically tested differences in HIV-related social media posts within regions of South Africa. Geocoded data were collected over a three-week period in 2018 (654,373 tweets, 90,410 Instagram posts and 14,133 YouTube videos with 1,121 comments). Of all tweets, 4,524 (0.7%) were found to related to HIV and AIDS. The percentage was similar for Instagram 95 (0.7%) but significantly lower for YouTube 18 (0.1%). We found regional differences in prevalence and use of social media related to HIV. We discuss the implication of data from these technologies in surveillance and interventions within South Africa and other LMICs.
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Affiliation(s)
- Alastair van Heerden
- Human and Social Development, Human Sciences Research Council, Pietermaritzburg, KwaZulu Natal, South Africa
- Developmental Pathways for Health Research Unit, University of the Witwatersrand, Johannesburg, Gauteng, South Africa
| | - Sean Young
- Department of Informatics, University of California Institute for Prediction Technology (UCIPT), University of California Irvine, Irvine, CA, United States of America
- Department of Emergency Medicine, University of California, Irvine, CA, United States of America
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Sousa-Pinto B, Anto A, Czarlewski W, Anto JM, Fonseca JA, Bousquet J. Assessment of the Impact of Media Coverage on COVID-19-Related Google Trends Data: Infodemiology Study. J Med Internet Res 2020; 22:e19611. [PMID: 32530816 PMCID: PMC7423386 DOI: 10.2196/19611] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 05/29/2020] [Accepted: 06/11/2020] [Indexed: 12/22/2022] Open
Abstract
Background The influence of media coverage on web-based searches may hinder the role of Google Trends (GT) in monitoring coronavirus disease (COVID-19). Objective The aim of this study was to assess whether COVID-19–related GT data, particularly those related to ageusia and anosmia, were primarily related to media coverage or to epidemic trends. Methods We retrieved GT query data for searches on coronavirus, cough, anosmia, and ageusia and plotted them over a period of 5 years. In addition, we analyzed the trends of those queries for 17 countries throughout the year 2020 with a particular focus on the rises and peaks of the searches. For anosmia and ageusia, we assessed whether the respective GT data correlated with COVID-19 cases and deaths both throughout 2020 and specifically before March 16, 2020 (ie, the date when the media started reporting that these symptoms can be associated with COVID-19). Results Over the last five years, peaks for coronavirus searches in GT were only observed during the winter of 2020. Rises and peaks in coronavirus searches appeared at similar times in the 17 different assessed countries irrespective of their epidemic situations. In 15 of these countries, rises in anosmia and ageusia searches occurred in the same week or 1 week after they were identified in the media as symptoms of COVID-19. When data prior to March 16, 2020 were analyzed, anosmia and ageusia GT data were found to have variable correlations with COVID-19 cases and deaths in the different countries. Conclusions Our results indicate that COVID-19–related GT data are more closely related to media coverage than to epidemic trends.
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Affiliation(s)
- Bernardo Sousa-Pinto
- Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal.,Center for Health Technology and Services Research, University of Porto, Porto, Portugal
| | | | - Wienia Czarlewski
- MASK-air, Montpellier, France.,Medical Consulting Czarlewski, Levallois, France
| | - Josep M Anto
- Centre for Research in Environmental Epidemiology, Barcelona Institute for Global Health, Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,CIBER Epidemiología y Salud Pública, Barcelona, Spain
| | - João Almeida Fonseca
- Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal.,Center for Health Technology and Services Research, University of Porto, Porto, Portugal
| | - Jean Bousquet
- Charité, Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Comprehensive Allergy Center, Department of Dermatology and Allergy, Berlin Institute of Health, Berlin, Germany.,MACVIA-France, Montpellier, France
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Sofiev M, Palamarchuk Y, Bédard A, Basagana X, Anto JM, Kouznetsov R, Urzua RD, Bergmann KC, Fonseca JA, De Vries G, Van Erd M, Annesi-Maesano I, Laune D, Pépin JL, Jullian-Desayes I, Zeng S, Czarlewski W, Bousquet J. A demonstration project of Global Alliance against Chronic Respiratory Diseases: Prediction of interactions between air pollution and allergen exposure-the Mobile Airways Sentinel NetworK-Impact of air POLLution on Asthma and Rhinitis approach. Chin Med J (Engl) 2020; 133:1561-1567. [PMID: 32649522 PMCID: PMC7386352 DOI: 10.1097/cm9.0000000000000916] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Indexed: 02/07/2023] Open
Abstract
This review analyzes the state and recent progress in the field of information support for pollen allergy sufferers. For decades, information available for the patients and allergologists consisted of pollen counts, which are vital but insufficient. New technology paves the way to substantial increase in amount and diversity of the data. This paper reviews old and newly suggested methods to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept, which combines the pollen and pollution information and transforms it into a qualitative risk index. This new index is available in an app (Mobile Airways Sentinel NetworK-air) that was developed in the frame of the European Union grant Impact of Air POLLution on sleep, Asthma and Rhinitis (a project of European Institute of Innovation and Technology-Health). On-going transformation of the pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and predictions. The new information-technology and artificial-intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.
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Affiliation(s)
- Mikhail Sofiev
- Finnish Meteorological Institute (FMI), Helsinki 00560, Finland
| | | | - Annabelle Bédard
- Barcelona Institute for Global Health, Centre for Research in Environmental Epidemiology (CREAL), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBER) Epidemiología y Salud Pública (CIBERESP), Barcelona 08003, Spain
- Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
| | - Xavier Basagana
- Barcelona Institute for Global Health, Centre for Research in Environmental Epidemiology (CREAL), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBER) Epidemiología y Salud Pública (CIBERESP), Barcelona 08003, Spain
- Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
- Institut Hospital del Mar d’Investigacions Mediques (IMIM), Barcelona 08003, Spain
| | - Josep M. Anto
- Barcelona Institute for Global Health, Centre for Research in Environmental Epidemiology (CREAL), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBER) Epidemiología y Salud Pública (CIBERESP), Barcelona 08003, Spain
- Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
- Institut Hospital del Mar d’Investigacions Mediques (IMIM), Barcelona 08003, Spain
| | | | | | - Karl Christian Bergmann
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Uniersität zu Berlin and Berlin Institute of Health, Comprehensive Allergy-Centre, Department of Dermatology and Allergy, Berlin 10117, Germany
| | - Joao A. Fonseca
- Center for Health Technology and Services Research (CINTESIS), Center for Research in Health Technology and Information Systems, Faculdade de Medicina da Universidade do Porto; and Medida, Lda Porto s/n 4200-450, Portugal
| | | | | | - Isabella Annesi-Maesano
- Epidemiology of Allergic and Respiratory Diseases Department, Institute Pierre Louis of Epidemiology and Public Health, INSERM and Sorbonne Université, Medical School Saint Antoine, Paris 75571, France
| | | | - Jean Louis Pépin
- Université Grenoble Alpes, Laboratoire HP2, Grenoble, INSERM, U1042 and CHU de Grenoble, Grenoble 38000, France
| | - Ingrid Jullian-Desayes
- Université Grenoble Alpes, Laboratoire HP2, Grenoble, INSERM, U1042 and CHU de Grenoble, Grenoble 38000, France
| | | | | | - Jean Bousquet
- University Hospital Montpellier, Montpellier 34000, France
- Contre les Maladies Chroniques pour un Vieillissement Actif en Languedoc Roussillon-France, Montpellier, France
- Charité, Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Comprehensive Allergy Center, Department of Dermatology and Allergy, Berlin 10117, Germany
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Paguio JA, Yao JS, Dee EC. Silver lining of COVID-19: Heightened global interest in pneumococcal and influenza vaccines, an infodemiology study. Vaccine 2020; 38:5430-5435. [PMID: 32620371 PMCID: PMC7315971 DOI: 10.1016/j.vaccine.2020.06.069] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 06/20/2020] [Accepted: 06/22/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Health-seeking behaviors change during pandemics and may increase with regard to illnesses with symptoms similar to the pandemic. The global reaction to COVID-19 may drive interest in vaccines for other diseases. OBJECTIVES Our study investigated the correlation between global online interest in COVID-19 and interest in CDC-recommended routine vaccines. DESIGN, SETTINGS, MEASUREMENTS This infodemiology study used Google Trends data to quantify worldwide interest in COVID-19 and CDC-recommended vaccines using the unit search volume index (SVI), which estimates volume of online search activity relative to highest volume of searches within a specified period. SVIs from December 30, 2019 to March 30, 2020 were collected for "coronavirus (Virus)" and compared with SVIs of search terms related to CDC-recommended adult vaccines. To account for seasonal variation, we compared SVIs from December 30, 2019 to March 30, 2020 with SVIs from the same months in 2015 to 2019. We performed country-level analyses in ten COVID-19 hotspots and ten countries with low disease burden. RESULTS There were significant positive correlations between SVIs for "coronavirus (Virus)" and search terms for pneumococcal (R = 0.89, p < 0.0001) and influenza vaccines (R = 0.93, p < 0.0001) in 2020, which were greater than SVIs for the same terms in 2015-2019 (p = 0.005, p < 0.0001, respectively). Eight in ten COVID-19 hotspots demonstrated significant positive correlations between SVIs for coronavirus and search terms for pneumococcal and influenza vaccines. LIMITATIONS SVIs estimate relative changes in online interest and do not represent the interest of people with no Internet access. CONCLUSION A peak in worldwide interest in pneumococcal and influenza vaccines coincided with the COVID-19 pandemic in February and March 2020. Trends are likely not seasonal in origin and may be driven by COVID-19 hotspots. Global events may change public perception about the importance of vaccines. Our findings may herald higher demand for pneumonia and influenza vaccines in the upcoming season.
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Affiliation(s)
| | - Jasper Seth Yao
- University of the Philippines College of Medicine, Philippines
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Nazir M, Hussain I, Tian J, Akram S, Mangenda Tshiaba S, Mushtaq S, Shad MA. A Multidimensional Model of Public Health Approaches Against COVID-19. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E3780. [PMID: 32466581 PMCID: PMC7312600 DOI: 10.3390/ijerph17113780] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 05/16/2020] [Accepted: 05/22/2020] [Indexed: 11/21/2022]
Abstract
COVID-19 is appearing as one of the most fetal disease of the world's history and has caused a global health emergency. Therefore, this study was designed with the aim to address the issue of public response against COVID-19. The literature lacks studies on social aspects of COVID-19. Therefore, the current study is an attempt to investigate its social aspects and suggest a theoretical structural equation model to examine the associations between social media exposure, awareness, and information exchange and preventive behavior and to determine the indirect as well as direct impact of social media exposure on preventive behavior from the viewpoints of awareness and information exchange. The current empirical investigation was held in Pakistan, and the collected survey data from 500 respondents through social media tools were utilized to examine the associations between studied variables as stated in the anticipated study model. The findings of the study indicate that social media exposure has no significant and direct effect on preventive behavior. Social media exposure influences preventive behavior indirectly through awareness and information exchange. In addition, awareness and information exchange have significant and direct effects on preventive behavior. Findings are valuable for health administrators, governments, policymakers, and social scientists, specifically for individuals whose situations are like those in Pakistan. This research validates how social media exposure indirectly effects preventive behavior concerning COVID-19 and explains the paths of effect through awareness or information exchange. To the best of our knowledge, there is no work at present that covers this gap, for this reason the authors propose a new model. The conceptual model offers valuable information for policymakers and practitioners to enhance preventive behavior through the adoption of appropriate awareness strategies and information exchange and social media strategies.
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Affiliation(s)
- Mehrab Nazir
- School of Economics and Management, Jiangsu University of Science & Technology, Zhenjiang 212003, China; (M.N.); (S.M.T.)
| | - Iftikhar Hussain
- Dean, Faculty of Computing & Engineering, University of Kotli Azad Jammu & Kashmir, Kotli 11100, Pakistan
| | - Jian Tian
- School of Economics and Management, Jiangsu University of Science & Technology, Zhenjiang 212003, China; (M.N.); (S.M.T.)
| | - Sabahat Akram
- Department of Econmomics, University of Kotli Azad Jammu & Kashmir, Kotli 11100, Pakistan;
| | - Sidney Mangenda Tshiaba
- School of Economics and Management, Jiangsu University of Science & Technology, Zhenjiang 212003, China; (M.N.); (S.M.T.)
| | - Shahrukh Mushtaq
- Department of Business Administration, University of Kotli Azad Jammu & Kashmir, Kotli 11100, Pakistan;
| | - Muhammad Afzal Shad
- Department of Commerce, University of Kotli Azad Jammu & Kashmir, Kotli 11100, Pakistan;
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Higgins TS, Wu AW, Sharma D, Illing EA, Rubel K, Ting JY. Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study. JMIR Public Health Surveill 2020; 6:e19702. [PMID: 32401211 PMCID: PMC7244220 DOI: 10.2196/19702] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 05/12/2020] [Accepted: 05/13/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The coronavirus disease (COVID-19) is the latest pandemic of the digital age. With the internet harvesting large amounts of data from the general population in real time, public databases such as Google Trends (GT) and the Baidu Index (BI) can be an expedient tool to assist public health efforts. OBJECTIVE The aim of this study is to apply digital epidemiology to the current COVID-19 pandemic to determine the utility of providing adjunctive epidemiologic information on outbreaks of this disease and evaluate this methodology in the case of future pandemics. METHODS An epidemiologic time series analysis of online search trends relating to the COVID-19 pandemic was performed from January 9, 2020, to April 6, 2020. BI was used to obtain online search data for China, while GT was used for worldwide data, the countries of Italy and Spain, and the US states of New York and Washington. These data were compared to real-world confirmed cases and deaths of COVID-19. Chronologic patterns were assessed in relation to disease patterns, significant events, and media reports. RESULTS Worldwide search terms for shortness of breath, anosmia, dysgeusia and ageusia, headache, chest pain, and sneezing had strong correlations (r>0.60, P<.001) to both new daily confirmed cases and deaths from COVID-19. GT COVID-19 (search term) and GT coronavirus (virus) searches predated real-world confirmed cases by 12 days (r=0.85, SD 0.10 and r=0.76, SD 0.09, respectively, P<.001). Searches for symptoms of diarrhea, fever, shortness of breath, cough, nasal obstruction, and rhinorrhea all had a negative lag greater than 1 week compared to new daily cases, while searches for anosmia and dysgeusia peaked worldwide and in China with positive lags of 5 days and 6 weeks, respectively, corresponding with widespread media coverage of these symptoms in COVID-19. CONCLUSIONS This study demonstrates the utility of digital epidemiology in providing helpful surveillance data of disease outbreaks like COVID-19. Although certain online search trends for this disease were influenced by media coverage, many search terms reflected clinical manifestations of the disease and showed strong correlations with real-world cases and deaths.
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Affiliation(s)
- Thomas S Higgins
- Department of Otolaryngology-Head and Neck Surgery and Communicative Disorders, University of Louisville, Louisville, KY, United States.,Rhinology, Sinus & Skull Base, Kentuckiana Ear Nose Throat, Louisville, KY, United States
| | - Arthur W Wu
- Department of Otolaryngology-Head and Neck Surgery, Cedars Sinai Medical Center, Los Angeles, CA, United States
| | - Dhruv Sharma
- Department of Otolaryngology-Head and Neck Surgery, Indiana University, Indianapolis, IN, United States
| | - Elisa A Illing
- Department of Otolaryngology-Head and Neck Surgery, Indiana University, Indianapolis, IN, United States
| | - Kolin Rubel
- Department of Otolaryngology-Head and Neck Surgery, Indiana University, Indianapolis, IN, United States
| | - Jonathan Y Ting
- Department of Otolaryngology-Head and Neck Surgery, Indiana University, Indianapolis, IN, United States
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- Snot Force, KY, United States
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Moore JH, Barnett I, Boland MR, Chen Y, Demiris G, Gonzalez-Hernandez G, Herman DS, Himes BE, Hubbard RA, Kim D, Morris JS, Mowery DL, Ritchie MD, Shen L, Urbanowicz R, Holmes JH. Ideas for how informaticians can get involved with COVID-19 research. BioData Min 2020; 13:3. [PMID: 32419848 PMCID: PMC7216865 DOI: 10.1186/s13040-020-00213-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on population health and wellbeing. Biomedical informatics is central to COVID-19 research efforts and for the delivery of healthcare for COVID-19 patients. Critical to this effort is the participation of informaticians who typically work on other basic science or clinical problems. The goal of this editorial is to highlight some examples of COVID-19 research areas that could benefit from informatics expertise. Each research idea summarizes the COVID-19 application area, followed by an informatics methodology, approach, or technology that could make a contribution. It is our hope that this piece will motivate and make it easy for some informaticians to adopt COVID-19 research projects.
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Affiliation(s)
- Jason H. Moore
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Ian Barnett
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Mary Regina Boland
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Yong Chen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - George Demiris
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Graciela Gonzalez-Hernandez
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Daniel S. Herman
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Blanca E. Himes
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Rebecca A. Hubbard
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Dokyoon Kim
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Jeffrey S. Morris
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Danielle L. Mowery
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Marylyn D. Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - Ryan Urbanowicz
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
| | - John H. Holmes
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
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Mavragani A. Infodemiology and Infoveillance: Scoping Review. J Med Internet Res 2020; 22:e16206. [PMID: 32310818 PMCID: PMC7189791 DOI: 10.2196/16206] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 02/05/2020] [Accepted: 02/08/2020] [Indexed: 12/12/2022] Open
Abstract
Background Web-based sources are increasingly employed in the analysis, detection, and forecasting of diseases and epidemics, and in predicting human behavior toward several health topics. This use of the internet has come to be known as infodemiology, a concept introduced by Gunther Eysenbach. Infodemiology and infoveillance studies use web-based data and have become an integral part of health informatics research over the past decade. Objective The aim of this paper is to provide a scoping review of the state-of-the-art in infodemiology along with the background and history of the concept, to identify sources and health categories and topics, to elaborate on the validity of the employed methods, and to discuss the gaps identified in current research. Methods The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed to extract the publications that fall under the umbrella of infodemiology and infoveillance from the JMIR, PubMed, and Scopus databases. A total of 338 documents were extracted for assessment. Results Of the 338 studies, the vast majority (n=282, 83.4%) were published with JMIR Publications. The Journal of Medical Internet Research features almost half of the publications (n=168, 49.7%), and JMIR Public Health and Surveillance has more than one-fifth of the examined studies (n=74, 21.9%). The interest in the subject has been increasing every year, with 2018 featuring more than one-fourth of the total publications (n=89, 26.3%), and the publications in 2017 and 2018 combined accounted for more than half (n=171, 50.6%) of the total number of publications in the last decade. The most popular source was Twitter with 45.0% (n=152), followed by Google with 24.6% (n=83), websites and platforms with 13.9% (n=47), blogs and forums with 10.1% (n=34), Facebook with 8.9% (n=30), and other search engines with 5.6% (n=19). As for the subjects examined, conditions and diseases with 17.2% (n=58) and epidemics and outbreaks with 15.7% (n=53) were the most popular categories identified in this review, followed by health care (n=39, 11.5%), drugs (n=40, 10.4%), and smoking and alcohol (n=29, 8.6%). Conclusions The field of infodemiology is becoming increasingly popular, employing innovative methods and approaches for health assessment. The use of web-based sources, which provide us with information that would not be accessible otherwise and tackles the issues arising from the time-consuming traditional methods, shows that infodemiology plays an important role in health informatics research.
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Affiliation(s)
- Amaryllis Mavragani
- Department of Computing Science and Mathematics, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom
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Barros JM, Duggan J, Rebholz-Schuhmann D. The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review. J Med Internet Res 2020; 22:e13680. [PMID: 32167477 PMCID: PMC7101503 DOI: 10.2196/13680] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 09/18/2019] [Accepted: 11/26/2019] [Indexed: 12/30/2022] Open
Abstract
Background Public health surveillance is based on the continuous and systematic collection, analysis, and interpretation of data. This informs the development of early warning systems to monitor epidemics and documents the impact of intervention measures. The introduction of digital data sources, and specifically sources available on the internet, has impacted the field of public health surveillance. New opportunities enabled by the underlying availability and scale of internet-based sources (IBSs) have paved the way for novel approaches for disease surveillance, exploration of health communities, and the study of epidemic dynamics. This field and approach is also known as infodemiology or infoveillance. Objective This review aimed to assess research findings regarding the application of IBSs for public health surveillance (infodemiology or infoveillance). To achieve this, we have presented a comprehensive systematic literature review with a focus on these sources and their limitations, the diseases targeted, and commonly applied methods. Methods A systematic literature review was conducted targeting publications between 2012 and 2018 that leveraged IBSs for public health surveillance, outbreak forecasting, disease characterization, diagnosis prediction, content analysis, and health-topic identification. The search results were filtered according to previously defined inclusion and exclusion criteria. Results Spanning a total of 162 publications, we determined infectious diseases to be the preferred case study (108/162, 66.7%). Of the eight categories of IBSs (search queries, social media, news, discussion forums, websites, web encyclopedia, and online obituaries), search queries and social media were applied in 95.1% (154/162) of the reviewed publications. We also identified limitations in representativeness and biased user age groups, as well as high susceptibility to media events by search queries, social media, and web encyclopedias. Conclusions IBSs are a valuable proxy to study illnesses affecting the general population; however, it is important to characterize which diseases are best suited for the available sources; the literature shows that the level of engagement among online platforms can be a potential indicator. There is a necessity to understand the population’s online behavior; in addition, the exploration of health information dissemination and its content is significantly unexplored. With this information, we can understand how the population communicates about illnesses online and, in the process, benefit public health.
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Affiliation(s)
- Joana M Barros
- Insight Centre for Data Analytics, National University of Ireland Galway, Galway, Ireland.,School of Computer Science, National University of Ireland Galway, Galway, Ireland
| | - Jim Duggan
- School of Computer Science, National University of Ireland Galway, Galway, Ireland
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Kamiński M, Łoniewski I, Marlicz W. "Dr. Google, I am in Pain"-Global Internet Searches Associated with Pain: A Retrospective Analysis of Google Trends Data. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17030954. [PMID: 32033087 PMCID: PMC7037174 DOI: 10.3390/ijerph17030954] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 01/26/2020] [Accepted: 01/31/2020] [Indexed: 12/12/2022]
Abstract
We aimed to rank the most common locations of pain among Google users globally and locally and analyze secular and seasonal trends in pain-related searches in the years 2004–2019. We used data generated by Google Trends (GT) to identify and analyze global interest in topics (n = 24) related to locations of pain and how these progressed over time. We analyzed secular trends and time series decomposition to identify seasonal variations. We also calculated the interest in all topics with reference to the relative search volume (RSV) of “Abdominal pain”. Google users were most commonly interested in “Headache” (1.30 [times more frequently than “Abdominal pain”]), “Abdominal pain” (1.00), and “Back pain” (0.84). “Headache” was the most frequent search term in n = 41 countries, while “Abdominal pain” was the most frequent term in n = 27 countries. The interest in all pain-related topics except “Dyspareunia” increased over time. The sharpest increase was observed for “Abdominal pain” (5.67 RSV/year), and “Toothache” (5.52 RSV/year). Most of the topics revealed seasonal variations. Among pain-related topics, “Headache,” “Abdominal pain,” and “Back pain” interested most Google users. GT is a novel tool that allows retrospective investigation of complaints among Internet users.
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Affiliation(s)
- Mikołaj Kamiński
- Sanprobi Sp.z.o.o. Sp.K., 70-535 Szczecin, Poland
- Faculty of Medicine I, Poznan University of Medical Sciences, 60-780 Poznan, Poland
- Correspondence: ; Tel.: +48-516268563
| | - Igor Łoniewski
- Department of Biochemistry and Human Nutrition, Pomeranian Medical University, 70-204 Szczecin, Poland;
| | - Wojciech Marlicz
- Department of Gastroenterology, Pomeranian Medical University, 70-204 Szczecin, Poland;
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Heartburn-Related Internet Searches and Trends of Interest across Six Western Countries: A Four-Year Retrospective Analysis Using Google Ads Keyword Planner. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16234591. [PMID: 31756947 PMCID: PMC6926592 DOI: 10.3390/ijerph16234591] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Revised: 11/16/2019] [Accepted: 11/18/2019] [Indexed: 12/12/2022]
Abstract
The internet is becoming the main source of health-related information. We aimed to investigate data regarding heartburn-related searches made by Google users from Australia, Canada, Germany, Poland, the United Kingdom, and the United States. We retrospectively analyzed data from Google Ads Keywords Planner. We extracted search volumes of keywords associated with “heartburn” for June 2015 to May 2019. The data were generated in the respective primary language. The number of searches per 1000 Google-user years was as follows: 177.4 (Australia), 178.1 (Canada), 123.8 (Germany), 199.7 (Poland), 152.5 (United Kingdom), and 194.5 (United States). The users were particularly interested in treatment (19.0 to 41.3%), diet (4.8 to 10.7%), symptoms (2.6 to 13.1%), and causes (3.7 to 10.0%). In all countries except Germany, the number of heartburn-related queries significantly increased over the analyzed period. For Canada, Germany, Poland, and the United Kingdom, query numbers were significantly lowest in summer; there was no significant seasonal trend for Australia and the United States. The number of heartburn-related queries has increased over the past four years, and a seasonal pattern may exist in certain regions. The trends in heartburn-related searches may reflect the scale of the complaint, and should be verified through future epidemiological studies.
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Cesare N, Nguyen QC, Grant C, Nsoesie EO. Social media captures demographic and regional physical activity. BMJ Open Sport Exerc Med 2019; 5:e000567. [PMID: 31423323 PMCID: PMC6678033 DOI: 10.1136/bmjsem-2019-000567] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/02/2019] [Indexed: 12/04/2022] Open
Abstract
Objectives We examined the use of data from social media for surveillance of physical activity prevalence in the USA. Methods We obtained data from the social media site Twitter from April 2015 to March 2016. The data consisted of 1 382 284 geotagged physical activity tweets from 481 146 users (55.7% men and 44.3% women) in more than 2900 counties. We applied machine learning and statistical modelling to demonstrate sex and regional variations in preferred exercises, and assessed the association between reports of physical activity on Twitter and population-level inactivity prevalence from the US Centers for Disease Control and Prevention. Results The association between physical inactivity tweet patterns and physical activity prevalence varied by sex and region. Walking was the most popular physical activity for both men and women across all regions (15.94% (95% CI 15.85% to 16.02%) and 18.74% (95% CI 18.64% to 18.88%) of tweets, respectively). Men and women mentioned performing gym-based activities at approximately the same rates (4.68% (95% CI 4.63% to 4.72%) and 4.13% (95% CI 4.08% to 4.18%) of tweets, respectively). CrossFit was most popular among men (14.91% (95% CI 14.52% to 15.31%)) among gym-based tweets, whereas yoga was most popular among women (26.66% (95% CI 26.03% to 27.19%)). Men mentioned engaging in higher intensity activities than women. Overall, counties with higher physical activity tweets also had lower leisure-time physical inactivity prevalence for both sexes. Conclusions The regional-specific and sex-specific activity patterns captured on Twitter may allow public health officials to identify changes in health behaviours at small geographical scales and to design interventions best suited for specific populations.
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Affiliation(s)
- Nina Cesare
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA.,Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
| | - Quynh C Nguyen
- Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, Maryland, USA
| | - Christan Grant
- School of Computer Science, University of Oklahoma, Norman, Oklahoma, USA
| | - Elaine O Nsoesie
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA.,Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
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Nikfarjam A, Ransohoff JD, Callahan A, Jones E, Loew B, Kwong BY, Sarin KY, Shah NH. Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection. JMIR Public Health Surveill 2019; 5:e11264. [PMID: 31162134 PMCID: PMC6684218 DOI: 10.2196/11264] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 02/27/2019] [Accepted: 04/04/2019] [Indexed: 12/31/2022] Open
Abstract
Background Adverse drug reactions (ADRs) occur in nearly all patients on chemotherapy, causing morbidity and therapy disruptions. Detection of such ADRs is limited in clinical trials, which are underpowered to detect rare events. Early recognition of ADRs in the postmarketing phase could substantially reduce morbidity and decrease societal costs. Internet community health forums provide a mechanism for individuals to discuss real-time health concerns and can enable computational detection of ADRs. Objective The goal of this study is to identify cutaneous ADR signals in social health networks and compare the frequency and timing of these ADRs to clinical reports in the literature. Methods We present a natural language processing-based, ADR signal-generation pipeline based on patient posts on Internet social health networks. We identified user posts from the Inspire health forums related to two chemotherapy classes: erlotinib, an epidermal growth factor receptor inhibitor, and nivolumab and pembrolizumab, immune checkpoint inhibitors. We extracted mentions of ADRs from unstructured content of patient posts. We then performed population-level association analyses and time-to-detection analyses. Results Our system detected cutaneous ADRs from patient reports with high precision (0.90) and at frequencies comparable to those documented in the literature but an average of 7 months ahead of their literature reporting. Known ADRs were associated with higher proportional reporting ratios compared to negative controls, demonstrating the robustness of our analyses. Our named entity recognition system achieved a 0.738 microaveraged F-measure in detecting ADR entities, not limited to cutaneous ADRs, in health forum posts. Additionally, we discovered the novel ADR of hypohidrosis reported by 23 patients in erlotinib-related posts; this ADR was absent from 15 years of literature on this medication and we recently reported the finding in a clinical oncology journal. Conclusions Several hundred million patients report health concerns in social health networks, yet this information is markedly underutilized for pharmacosurveillance. We demonstrated the ability of a natural language processing-based signal-generation pipeline to accurately detect patient reports of ADRs months in advance of literature reporting and the robustness of statistical analyses to validate system detections. Our findings suggest the important contributions that social health network data can play in contributing to more comprehensive and timely pharmacovigilance.
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Affiliation(s)
- Azadeh Nikfarjam
- Stanford Center for Biomedical Informatics Research, Stanford Department of Medicine, Stanford, CA, United States
| | - Julia D Ransohoff
- Stanford Center for Biomedical Informatics Research, Stanford Department of Medicine, Stanford, CA, United States
| | - Alison Callahan
- Stanford Center for Biomedical Informatics Research, Stanford Department of Medicine, Stanford, CA, United States
| | | | | | - Bernice Y Kwong
- Department of Dermatology, Stanford University School of Medicine, Stanford, CA, United States
| | - Kavita Y Sarin
- Department of Dermatology, Stanford University School of Medicine, Stanford, CA, United States
| | - Nigam H Shah
- Stanford Center for Biomedical Informatics Research, Stanford Department of Medicine, Stanford, CA, United States
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Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health Surveill 2019; 5:e13439. [PMID: 31144671 PMCID: PMC6660120 DOI: 10.2196/13439] [Citation(s) in RCA: 220] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 02/17/2019] [Accepted: 03/23/2019] [Indexed: 02/06/2023] Open
Abstract
Internet data are being increasingly integrated into health informatics research and are becoming a useful tool for exploring human behavior. The most popular tool for examining online behavior is Google Trends, an open tool that provides information on trends and the variations of online interest in selected keywords and topics over time. Online search traffic data from Google have been shown to be useful in analyzing human behavior toward health topics and in predicting disease occurrence and outbreaks. Despite the large number of Google Trends studies during the last decade, the literature on the subject lacks a specific methodology framework. This article aims at providing an overview of the tool and data and at presenting the first methodology framework in using Google Trends in infodemiology and infoveillance, including the main factors that need to be taken into account for a strong methodology base. We provide a step-by-step guide for the methodology that needs to be followed when using Google Trends and the essential aspects required for valid results in this line of research. At first, an overview of the tool and the data are presented, followed by an analysis of the key methodological points for ensuring the validity of the results, which include selecting the appropriate keyword(s), region(s), period, and category. Overall, this article presents and analyzes the key points that need to be considered to achieve a strong methodological basis for using Google Trends data, which is crucial for ensuring the value and validity of the results, as the analysis of online queries is extensively integrated in health research in the big data era.
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Affiliation(s)
- Amaryllis Mavragani
- Department of Computing Science and Mathematics, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom
| | - Gabriela Ochoa
- Department of Computing Science and Mathematics, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom
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Kogan NE, Bolon I, Ray N, Alcoba G, Fernandez-Marquez JL, Müller MM, Mohanty SP, Ruiz de Castañeda R. Wet Markets and Food Safety: TripAdvisor for Improved Global Digital Surveillance. JMIR Public Health Surveill 2019; 5:e11477. [PMID: 30932867 PMCID: PMC6462893 DOI: 10.2196/11477] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 01/18/2019] [Accepted: 01/18/2019] [Indexed: 11/21/2022] Open
Abstract
Background Wet markets are markets selling fresh meat and produce. Wet markets are critical for food security and sustainable development in their respective regions. Due to their cultural significance, they attract numerous visitors and consequently generate tourist-geared information on the Web (ie, on social networks such as TripAdvisor). These data can be used to create a novel, international wet market inventory to support epidemiological surveillance and control in such settings, which are often associated with negative health outcomes. Objective Using social network data, we aimed to assess the level of wet markets’ touristic importance on the Web, produce the first distribution map of wet markets of touristic interest, and identify common diseases facing visitors in these settings. Methods A Google search was performed on 31 food market–related keywords, with the first 150 results for each keyword evaluated based on their relevance to tourism. Of all these queries, wet market had the highest number of tourism-related Google Search results; among these, TripAdvisor was the most frequently-occurring travel information aggregator, prompting its selection as the data source for this study. A Web scraping tool (ParseHub) was used to extract wet market names, locations, and reviews from TripAdvisor. The latter were searched for disease-related content, which enabled assignment of GeoSentinel diagnosis codes to each. This syndromic categorization was overlaid onto a mapping of wet market locations. Regional prevalence of the most commonly occurring symptom group - food poisoning - was then determined (ie, by dividing the number of wet markets per continent with more than or equal to 1 review containing this syndrome by the total number of wet markets on that continent with syndromic information). Results Of the 1090 hits on TripAdvisor for wet market, 36.06% (393/1090) conformed to the query’s definition; wet markets were heterogeneously distributed: Asia concentrated 62.6% (246/393) of them, Europe 19.3% (76/393), North America 7.9% (31/393), Oceania 5.1% (20/393), Africa 3.1% (12/393), and South America 2.0% (8/393). Syndromic information was available for 14.5% (57/393) of wet markets. The most frequently occurring syndrome among visitors to these wet markets was food poisoning, accounting for 54% (51/95) of diagnoses. Cases of this syndrome were identified in 56% (22/39) of wet markets with syndromic information in Asia, 71% (5/7) in Europe, and 71% (5/7) in North America. All wet markets in South America and Oceania reported food poisoning cases, but the number of reviews with syndromic information was very limited in these regions (n=2). Conclusions The map produced illustrates the potential role of touristically relevant social network data to support global epidemiological surveillance. This includes the possibility to approximate the global distribution of wet markets and to identify diseases (ie, food poisoning) that are most prevalent in such settings.
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Affiliation(s)
- Nicole E Kogan
- Massachusetts Institute of Technology, Cambridge, MA, United States.,Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Isabelle Bolon
- Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicolas Ray
- Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland
| | - Gabriel Alcoba
- Division of Tropical and Humanitarian Medicine, University Hospitals of Geneva, Geneva, Switzerland
| | - Jose L Fernandez-Marquez
- Citizen Cyberlab, Centre Universitaire d'Informatique, University of Geneva, Carouge, Switzerland
| | - Martin M Müller
- Digital Epidemiology Lab, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Sharada P Mohanty
- Digital Epidemiology Lab, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Abstract
INTRODUCTION The rising popularity of social media, since their inception around 20 years ago, has been echoed in the growth of health-related research using data derived from them. This has created a demand for literature reviews to synthesise this emerging evidence base and inform future activities. Existing reviews tend to be narrow in scope, with limited consideration of the different types of data, analytical methods and ethical issues involved. There has also been a tendency for research to be siloed within different academic communities (eg, computer science, public health), hindering knowledge translation. To address these limitations, we will undertake a comprehensive scoping review, to systematically capture the broad corpus of published, health-related research based on social media data. Here, we present the review protocol and the pilot analyses used to inform it. METHODS A version of Arksey and O'Malley's five-stage scoping review framework will be followed: (1) identifying the research question; (2) identifying the relevant literature; (3) selecting the studies; (4) charting the data and (5) collating, summarising and reporting the results. To inform the search strategy, we developed an inclusive list of keyword combinations related to social media, health and relevant methodologies. The frequency and variability of terms were charted over time and cross referenced with significant events, such as the advent of Twitter. Five leading health, informatics, business and cross-disciplinary databases will be searched: PubMed, Scopus, Association of Computer Machinery, Institute of Electrical and Electronics Engineers and Applied Social Sciences Index and Abstracts, alongside the Google search engine. There will be no restriction by date. ETHICS AND DISSEMINATION The review focuses on published research in the public domain therefore no ethics approval is required. The completed review will be submitted for publication to a peer-reviewed, interdisciplinary open access journal, and conferences on public health and digital research.
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Affiliation(s)
- Joanna Taylor
- Usher Institute for Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK
| | - Claudia Pagliari
- Usher Institute for Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK
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Schwab-Reese LM, Hovdestad W, Tonmyr L, Fluke J. The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations. CHILD ABUSE & NEGLECT 2018; 85:187-201. [PMID: 29366596 PMCID: PMC7112406 DOI: 10.1016/j.chiabu.2018.01.014] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 12/06/2017] [Accepted: 01/12/2018] [Indexed: 05/12/2023]
Abstract
Collecting child maltreatment data is a complicated undertaking for many reasons. As a result, there is an interest by child maltreatment researchers to develop methodologies that allow for the triangulation of data sources. To better understand how social media and internet-based technologies could contribute to these approaches, we conducted a scoping review to provide an overview of social media and internet-based methodologies for health research, to report results of evaluation and validation research on these methods, and to highlight studies with potential relevance to child maltreatment research and surveillance. Many approaches were identified in the broad health literature; however, there has been limited application of these approaches to child maltreatment. The most common use was recruiting participants or engaging existing participants using online methods. From the broad health literature, social media and internet-based approaches to surveillance and epidemiologic research appear promising. Many of the approaches are relatively low cost and easy to implement without extensive infrastructure, but there are also a range of limitations for each method. Several methods have a mixed record of validation and sources of error in estimation are not yet understood or predictable. In addition to the problems relevant to other health outcomes, child maltreatment researchers face additional challenges, including the complex ethical issues associated with both internet-based and child maltreatment research. If these issues are adequately addressed, social media and internet-based technologies may be a promising approach to reducing some of the limitations in existing child maltreatment data.
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Affiliation(s)
- Laura M Schwab-Reese
- The Kempe Center for The Prevention and Treatment of Child Abuse and Neglect, University of Colorado, Anschutz Medical Campus, 13123 E 16th Ave., Aurora, CO 80045, USA.
| | - Wendy Hovdestad
- Public Health Agency of Canada, 785 Carling Ave., Ottawa, ON, K1A 0K9, Canada
| | - Lil Tonmyr
- Public Health Agency of Canada, 785 Carling Ave., Ottawa, ON, K1A 0K9, Canada
| | - John Fluke
- The Kempe Center for The Prevention and Treatment of Child Abuse and Neglect, University of Colorado, Anschutz Medical Campus, 13123 E 16th Ave., Aurora, CO 80045, USA
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Reuter K, Angyan P, Le N, MacLennan A, Cole S, Bluthenthal RN, Lane CJ, El-Khoueiry AB, Buchanan TA. Monitoring Twitter Conversations for Targeted Recruitment in Cancer Trials in Los Angeles County: Protocol for a Mixed-Methods Pilot Study. JMIR Res Protoc 2018; 7:e177. [PMID: 30274964 PMCID: PMC6231794 DOI: 10.2196/resprot.9762] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 07/22/2018] [Accepted: 07/23/2018] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Insufficient recruitment of participants remains a critical roadblock to successful clinical research, particularly clinical trials. Social media provide new ways for connecting potential participants with research opportunities. Researchers suggest that the social network Twitter may serve as a rich avenue for exploring how patients communicate about their health issues and increasing enrollment in cancer clinical trials. However, there is a lack of evidence that Twitter offers practical utility and impact. OBJECTIVE This pilot study aimed to examine the feasibility and impact of using Twitter monitoring data (ie, user activity and their conversations about cancer-related conditions and concerns expressed by Twitter users in Los Angeles County) as a tool for enhancing clinical trial recruitment at a comprehensive cancer center. METHODS We will conduct a mixed-methods interrupted time series study design with a before-and-after social media recruitment intervention. On the basis of a preliminary analysis of eligible trials, we plan to onboard at least 84 clinical trials across 6 disease categories: breast cancer, colon cancer, kidney cancer, lymphoma, non-small cell lung cancer, and prostate cancer that are open to accrual at the University of Southern California (USC) Norris Comprehensive Cancer Center. We will monitor messages about these 6 cancer conditions posted by Twitter users in Los Angeles County. Recruitment for the trials will occur through the Twitter account (@USCTrials). Primary study outcomes-feasibility and acceptance of the social media intervention among targeted Twitter users and the study teams of the onboarded trials-will be assessed using qualitative interviews and the 4-point Likert scale and by calculating the proportion of targeted Twitter users who engaged with outreach messages. Second, impact of the social media intervention will be measured by calculating the proportion of enrollees in trials. The enrollment rate will be compared between the active intervention period and the prior 10 months as historical control for each disease trial group. This study has been funded by the National Center for Advancing Translational Science through a Clinical and Translational Science Award. Study approval was obtained from the clinical investigations committee at USC Norris and the institutional review board at USC. RESULTS Recruitment on Twitter started in February 2018. Data collection will be completed in November 2018. CONCLUSIONS This pilot project will provide preliminary data and practical insight into the application of publicly available Twitter data to identify and recruit clinical trial participants across 6 cancer disease types. We will shed light on the acceptance of the social media intervention among Twitter users and study team members of the onboarded trials. If successful, the findings will inform a multisite randomized controlled trial to determine the efficacy of the social media intervention across different locations and populations. TRIAL REGISTRATION ClinicalTrials.gov NCT03408561; https://clinicaltrials.gov/ct2/show/NCT03408561 (Archived by WebCite at http://www.webcitation.org/72LihauzW). REGISTERED REPORT IDENTIFIER RR1-10.2196/9762.
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Affiliation(s)
- Katja Reuter
- Institute for Health Promotion & Disease Prevention Research, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.,Southern California Clinical and Translational Science Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Praveen Angyan
- Southern California Clinical and Translational Science Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - NamQuyen Le
- Southern California Clinical and Translational Science Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Alicia MacLennan
- Southern California Clinical and Translational Science Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Sarah Cole
- USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Ricky N Bluthenthal
- Institute for Health Promotion & Disease Prevention Research, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Christianne J Lane
- Southern California Clinical and Translational Science Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.,Division of Biostatistics, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Anthony B El-Khoueiry
- USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Thomas A Buchanan
- Southern California Clinical and Translational Science Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.,Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
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Oldroyd RA, Morris MA, Birkin M. Identifying Methods for Monitoring Foodborne Illness: Review of Existing Public Health Surveillance Techniques. JMIR Public Health Surveill 2018; 4:e57. [PMID: 29875090 PMCID: PMC6010836 DOI: 10.2196/publichealth.8218] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 01/16/2018] [Accepted: 01/31/2018] [Indexed: 11/13/2022] Open
Abstract
Background Traditional methods of monitoring foodborne illness are associated with problems of untimeliness and underreporting. In recent years, alternative data sources such as social media data have been used to monitor the incidence of disease in the population (infodemiology and infoveillance). These data sources prove timelier than traditional general practitioner data, they can help to fill the gaps in the reporting process, and they often include additional metadata that is useful for supplementary research. Objective The aim of the study was to identify and formally analyze research papers using consumer-generated data, such as social media data or restaurant reviews, to quantify a disease or public health ailment. Studies of this nature are scarce within the food safety domain, therefore identification and understanding of transferrable methods in other health-related fields are of particular interest. Methods Structured scoping methods were used to identify and analyze primary research papers using consumer-generated data for disease or public health surveillance. The title, abstract, and keyword fields of 5 databases were searched using predetermined search terms. A total of 5239 papers matched the search criteria, of which 145 were taken to full-text review—62 papers were deemed relevant and were subjected to data characterization and thematic analysis. Results The majority of studies (40/62, 65%) focused on the surveillance of influenza-like illness. Only 10 studies (16%) used consumer-generated data to monitor outbreaks of foodborne illness. Twitter data (58/62, 94%) and Yelp reviews (3/62, 5%) were the most commonly used data sources. Studies reporting high correlations against baseline statistics used advanced statistical and computational approaches to calculate the incidence of disease. These include classification and regression approaches, clustering approaches, and lexicon-based approaches. Although they are computationally intensive due to the requirement of training data, studies using classification approaches reported the best performance. Conclusions By analyzing studies in digital epidemiology, computer science, and public health, this paper has identified and analyzed methods of disease monitoring that can be transferred to foodborne disease surveillance. These methods fall into 4 main categories: basic approach, classification and regression, clustering approaches, and lexicon-based approaches. Although studies using a basic approach to calculate disease incidence generally report good performance against baseline measures, they are sensitive to chatter generated by media reports. More computationally advanced approaches are required to filter spurious messages and protect predictive systems against false alarms. Research using consumer-generated data for monitoring influenza-like illness is expansive; however, research regarding the use of restaurant reviews and social media data in the context of food safety is limited. Considering the advantages reported in this review, methods using consumer-generated data for foodborne disease surveillance warrant further investment.
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Affiliation(s)
- Rachel A Oldroyd
- Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.,School of Geography, University of Leeds, Leeds, United Kingdom
| | - Michelle A Morris
- Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.,School of Medicine, University of Leeds, Leeds, United Kingdom
| | - Mark Birkin
- Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.,School of Geography, University of Leeds, Leeds, United Kingdom
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Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Info Libr J 2018; 35:91-120. [PMID: 29729073 DOI: 10.1111/hir.12216] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Accepted: 03/17/2018] [Indexed: 12/15/2022]
Abstract
INTRODUCTION The health care industry is rich in data and information. Web technologies, such as search engines and social media, have provided an opportunity for the management of user generated data in real time in the form of infodemiology studies. The aim of this study was to investigate infodemiology studies conducted during 2002-2016, and compare them based on developed, developing and in transition countries. METHODS This scoping review was conducted in 2017 with the help of the PRISMA guidelines. PubMed, Scopus, Science Direct, Web of Knowledge, Google Scholar, Wiley and Springer databases were searched between the years 2002 and 2016. Finally, 56 articles were included in the review and analysed. RESULTS The initial infodemiology studies pertain to the quality assessment of the hospital's websites. Most of the studies were on developed countries, based on flu, and published in the Journal of Medical Internet Research. CONCLUSION The infodemiology approach provides unmatched opportunities for the management of health data and information generated by the users. Using this potential will provide unique opportunities for the health information need assessment in real time by health librarians and thereby provide evidence based health information to the people.
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Affiliation(s)
- Kimia Zeraatkar
- Department of Health Information Technology, Iran University of Medical Sciences, Tehran, Iran
| | - Maryam Ahmadi
- Department of Health Information Technology, Iran University of Medical Sciences, Tehran, Iran
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