Digital disease detection - harnessing the Web for public health surveillance

Detecting influenza epidemics using search engine query data

Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2009) · Nature · doi:10.1038/nature07634 · Cited by 4,295

Using Internet Searches for Influenza Surveillance

Polgreen, P. M., Chen, Y., Pennock, D. M., & Nelson, F. D. (2008) · Clinical Infectious Diseases · doi:10.1086/593098 · Cited by 567

Infodemiology: tracking flu-related searches on the web for syndromic surveillance.

Eysenbach, G. (2006) · PubMed · Cited by 414

Surveillance Sans Frontières: Internet-Based Emerging Infectious Disease Intelligence and the HealthMap Project

Brownstein, J. S., Freifeld, C. C., Reis, B. Y., & Mandl, K. D. (2008) · PLoS Medicine · doi:10.1371/journal.pmed.0050151 · Cited by 413

ProMED-mail: An Early Warning System for Emerging Diseases

Yu, V. L., & Madoff, L. C. (2004) · Clinical Infectious Diseases · doi:10.1086/422003 · Cited by 269

Patterns of Routes of Administration and Drug Tampering for Nonmedical Opioid Consumption: Data Mining and Content Analysis of Reddit Discussions

Balsamo, D., Bajardi, P., Salomone, A., & Schifanella, R. (2021) · Journal of Medical Internet Research · doi:10.2196/21212 · Cited by 42

Prediction and analysis of Coronavirus Disease 2019Preprint

Jia, L., Li, K., Jiang, Y., Guo, X. Q., & Zhao, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.05447 · Cited by 43

Monitoring Online Discussions About Suicide Among Twitter Users With Schizophrenia: Exploratory Study

Hswen, Y., Naslund, J. A., Brownstein, J. S., & Hawkins, J. B. (2018) · JMIR Mental Health · doi:10.2196/11483 · Cited by 43

Changes to public health surveillance methods due to the COVID-19 pandemic: scoping review

Clark, E. C., Neumann, S., Hopkins, S., Kostopoulos, A., Hagerman, L., & Dobbins, M. (2024) · JMIR Public Health and Surveillance · doi:10.2196/49185 · Cited by 42

The Potential Capability of Social Media as a Component of Food Safety and Food Terrorism Surveillance Systems

Newkirk, R. W., Bender, J. B., & Hedberg, C. W. (2012) · Foodborne Pathogens and Disease · doi:10.1089/fpd.2011.0990 · Cited by 42

Emerging Challenges and Opportunities in Infectious Disease Epidemiology

Lewnard, J. A., & Reingold, A. L. (2018) · American Journal of Epidemiology · doi:10.1093/aje/kwy264 · Cited by 42

Real-Time Digital Surveillance of Vaping-Induced Pulmonary Disease

Hswen, Y., & Brownstein, J. S. (2019) · New England Journal of Medicine · doi:10.1056/nejmc1912818 · Cited by 41

Data journalism and the COVID-19 pandemic: opportunities and challenges

Desai, A. N., Nouvellet, P., Bhatia, S., Cori, A., & Lassmann, B. (2021) · The Lancet Digital Health · doi:10.1016/s2589-7500(21)00178-3 · Cited by 41

Eight Years of the Great Influenza Survey to Monitor Influenza-Like Illness in Flanders

Vandendijck, Y., Faes, C., & Hens, N. (2013) · PLoS ONE · doi:10.1371/journal.pone.0064156 · Cited by 41

Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study

Bragazzi, N. L., Dini, G., Toletone, A., Brigo, F., & Durando, P. (2016) · PLoS ONE · doi:10.1371/journal.pone.0166051 · Cited by 41

An ensemble forecast model of dengue in Guangzhou, China using climate and social media surveillance data

Guo, P., Zhang, Q., Chen, Y., Xiao, J., He, J., Zhang, Y., Wang, L., Liu, T., & Ma, W. (2018) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2018.08.044 · Cited by 41

Recent Advances in Computational Epidemiology

MARATHE, M. V., & Ramakrishnan, N. (2013) · IEEE Intelligent Systems · doi:10.1109/mis.2013.114 · Cited by 40

Supplementing Public Health Inspection via Social Media

Schomberg, J., Haimson, O. L., Hayes, G. R., & Anton‐Culver, H. (2016) · PLoS ONE · doi:10.1371/journal.pone.0152117 · Cited by 40

Use of syndromic surveillance data to monitor poisonings and drug overdoses in state and local public health agencies

Ising, A., Proescholdbell, S., Harmon, K., Sachdeva, N., Marshall, S. W., & Waller, A. E. (2016) · Injury Prevention · doi:10.1136/injuryprev-2015-041821 · Cited by 40

Saúde na Copa: The World’s First Application of Participatory Surveillance for a Mass Gathering at FIFA World Cup 2014, Brazil

Leal-Neto, O. B., Dimech, G. S., Libel, M., de Souza, W. V., Cesse, E. Â. P., Smolinski, M. S., de Oliveira, W. K., & Albuquerque, J. D. O. (2017) · JMIR Public Health and Surveillance · doi:10.2196/publichealth.7313 · Cited by 40

The future of pharmaceutical manufacturing in the context of the scientific, social, technological and economic evolution

Stegemann, S. (2015) · European Journal of Pharmaceutical Sciences · doi:10.1016/j.ejps.2015.11.003 · Cited by 39

Characterizing Awareness of Schizophrenia Among Facebook Users by Leveraging Facebook Advertisement Estimates

Saha, K., Weber, I. G., Birnbaum, M. L., & Choudhury, M. D. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6815 · Cited by 39

Reconstruction and prediction of viral disease epidemics

Kraemer, M. U. G., Cummings, D. A. T., Funk, S., Reiner, R. C., Faria, N. R., Pybus, O. G., & Cauchemez, S. (2018) · Epidemiology and Infection · doi:10.1017/s0950268818002881 · Cited by 36

A Multidimensional Model of Public Health Approaches Against COVID-19

Nazir, M., Hussain, I., Tian, J., Akram, S., Tshiaba, S. M., Mushtaq, S., & Shad, M. A. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17113780 · Cited by 39

Prioritising Infectious Disease Mapping

Pigott, D. M., Howes, R. E., Wiebe, A., Battle, K. E., Golding, N., Gething, P. W., Dowell, S. F., Farag, T. H., Garcia, A. J., Kimball, A. M., et al. (2015) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0003756 · Cited by 39

Artificial Intelligence in Infectious Disease Clinical Practice: An Overview of Gaps, Opportunities, and Limitations

Sarantopoulos, A., Mastori Kourmpani, C., Yokarasa, A. L., Makamanzi, C., Antoniou, P., Spernovasilis, N., & Tsioutis, C. (2024) · Tropical Medicine and Infectious Disease · doi:10.3390/tropicalmed9100228 · Cited by 40

Participatory Disease Surveillance Systems: Ethical Framework

Geneviève, L. D., Martani, A., Wangmo, T., Paolotti, D., Koppeschaar, C. E., Kjelsø, C., Guerrisi, C., Hirsch, M., Woolley-Meza, O., Lukowicz, P., et al. (2019) · Journal of Medical Internet Research · doi:10.2196/12273 · Cited by 41

Dynamic Public Health Surveillance to Track and Mitigate the US COVID-19 Epidemic: Longitudinal Trend Analysis Study

Post, L. A., Issa, T. Z., Boctor, M. J., Moss, C. B., Murphy, R. L., Ison, M. G., Achenbach, C. J., Resnick, D., Singh, L. N., White, J. I., et al. (2020) · Journal of Medical Internet Research · doi:10.2196/24286 · Cited by 38

Using Twitter to recruit participants for health research: An example from a caregiving study

Wasilewski, M. B., Stinson, J., Webster, F., & Cameron, J. I. (2018) · Health Informatics Journal · doi:10.1177/1460458218775158 · Cited by 37

Firsthand Opiates Abuse on Social Media: Monitoring Geospatial Patterns of Interest Through a Digital Cohort

Balsamo, D., Bajardi, P., & Panisson, A. (2019) · International World Wide Web Conference (WWW) · doi:10.1145/3308558.3313634 · Cited by 37

Cancer Cluster Investigations: Review of the Past and Proposals for the Future

Goodman, M. G., LaKind, J. S., Fagliano, J. A., Lash, T. L., Wiemels, J. L., Winn, D. M., Patel, C. J., Eenwyk, J. V., Kohler, B., Schisterman, E. F., et al. (2014) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph110201479 · Cited by 39

Public health intelligence and the detection of potential pandemics

French, M. A., & Mykhalovskiy, E. (2012) · Sociology of Health & Illness · doi:10.1111/j.1467-9566.2012.01536.x · Cited by 35

Participatory Surveillance of Hypoglycemia and Harms in an Online Social Network

Weitzman, E. R., Kelemen, S., Quinn, M., Eggleston, E., & Mandl, K. D. (2013) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2013.2512 · Cited by 35

Deploying nEmesis: Preventing Foodborne Illness by Data Mining Social Media

Sadilek, A., Kautz, H., DiPrete, L., Labus, B., Portman, E., Teitel, J., & Silenzio, V. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i2.19072 · Cited by 35

A Participatory System for Preventing Pandemics of Animal Origins: Pilot Study of the Participatory One Health Disease Detection (PODD) System

Yano, T., Phornwisetsirikun, S., Susumpow, P., Visrutaratna, S., Chanachai, K., Phetra, P., Chaisowwong, W., Trakarnsirinont, P., Hemwan, P., Kaewpinta, B., et al. (2018) · JMIR Public Health and Surveillance · doi:10.2196/publichealth.7375 · Cited by 35

Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing

O’Sullivan, S., Ali, Z., Jiang, X., Abdolvand, R., Ünlü, M. S., Silva, H., Baca, J. T., Kim, B. N., Scott, S. M., Sajid, M. I., et al. (2019) · Sensors · doi:10.3390/s19081917 · Cited by 36

Google Trends Data and COVID‐19 in Europe: Correlations and model enhancement are European wide

Sulyok, M., Ferenci, T., & Walker, M. D. (2020) · Transboundary and Emerging Diseases · doi:10.1111/tbed.13887 · Cited by 34

A New Approach to Monitoring Dengue Activity

Madoff, L. C., Fisman, D. N., & Kass‐Hout, T. (2011) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0001215 · Cited by 35

Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance

Nsoesie, E. O., Buckeridge, D. L., & Brownstein, J. S. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.2998 · Cited by 34

Social media analytics and research test-bed (SMART dashboard)

Tsou, M., Jung, C., Allen, C. B., Yang, J., Gawron, J.-M., Spitzberg, B. H., & Han, S. Y. (2015) · doi:10.1145/2789187.2789196 · Cited by 34

A population health perspective on artificial intelligence

Lavigne, M., Mussa, F., Creatore, M. I., Hoffman, S. J., & Buckeridge, D. L. (2019) · Healthcare Management Forum · doi:10.1177/0840470419848428 · Cited by 37

Using Google Trends Data to Study Public Interest in Breast Cancer Screening in Malaysia

Mohamad, M., & Kok, H. S. (2019) · Asian Pacific Journal of Cancer Prevention · doi:10.31557/apjcp.2019.20.5.1427 · Cited by 34

Epidemic tracking and forecasting: Lessons learned from a tumultuous year

Rosenfeld, R., & Tibshirani, R. J. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2111456118 · Cited by 33

GET WELL: an automated surveillance system for gaining new epidemiological knowledge

Hulth, A., & Rydevik, G. (2011) · BMC Public Health · doi:10.1186/1471-2458-11-252 · Cited by 34

Timeliness of Nongovernmental versus Governmental Global Outbreak Communications

Mondor, L., Brownstein, J. S., Chan, E. H., Madoff, L. C., Pollack, M. P., Buckeridge, D. L., & Brewer, T. F. (2012) · Emerging infectious diseases · doi:10.3201/eid1807.120249 · Cited by 34

Surveillance of Acute Respiratory Infections Using Community-Submitted Symptoms and Specimens for Molecular Diagnostic Testing

Goff, J., Rowe, A. A., Brownstein, J. S., & Chunara, R. (2015) · PLoS Currents · doi:10.1371/currents.outbreaks.0371243baa7f3810ba1279e30b96d3b6 · Cited by 34

Seasonality of bruxism: evidence from Google Trends

Kardeş, S., & Kardeş, E. (2019) · Sleep And Breathing · doi:10.1007/s11325-019-01787-6 · Cited by 34

Ensuring Safe Foods and Medical Products Through Stronger Regulatory Systems Abroad

Board on Global Health, & Board on Health Sciences Policy (2012) · National Academies Press eBooks · doi:10.17226/13296 · Cited by 33

Communicating Biosecurity

Briggs, C. L. (2011) · Medical Anthropology · doi:10.1080/01459740.2010.531066 · Cited by 33

Google Insights and U.S. Senate Elections: Does Search Traffic Provide a Valid Measure of Public Attention to Political Candidates?

Swearingen, C., & RIPBERGER, J. T. (2014) · Social Science Quarterly · doi:10.1111/ssqu.12075 · Cited by 33

The Public Sphere in Emerging Infectious Disease Communication: Recipient or Active and Vocal Partner?

Gesser‐Edelsburg, A., Shir-Raz, Y., Walter, N., Mordini, E., Dimitriou, D., James, J. J., & Green, M. S. (2015) · Disaster Medicine and Public Health Preparedness · doi:10.1017/dmp.2015.31 · Cited by 32

Using Google Trends to Predict COVID-19 Vaccinations and Monitor Search Behaviours about Vaccines: A Retrospective Analysis of Italian Data

Maugeri, A., Barchitta, M., & Agodi, A. (2022) · Vaccines · doi:10.3390/vaccines10010119 · Cited by 30

Using Internet Search Data to Produce State-level Measures: The Case of Tea Party Mobilization

DiGrazia, J. (2015) · Sociological Methods & Research · doi:10.1177/0049124115610348 · Cited by 33

Creating corroborated crisis reports from social media data through formal concept analysis

Andrews, S., Gibson, H. A., Domdouzis, K., & Akhgar, B. (2016) · Journal of Intelligent Information Systems · doi:10.1007/s10844-016-0404-9 · Cited by 31

In the Digital Era, Is Community Outrage a Feasible Proxy Indicator of Emotional Epidemiology? The Case of Meningococcal Disease in Sardinia, Italy

Dettori, M., Arru, B., Azara, A., Piana, A. F., Mariotti, G., Camerada, M. V., Stefanelli, P., Rezza, G., & Castiglia, P. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15071512 · Cited by 31

Using Search Queries to Understand Health Information Needs in Africa

Abebe, R., Hill, S., Vaughan, J. W., Small, P. M., & Schwartz, H. A. (2019) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v13i01.3360 · Cited by 37

The Wisdom of Crowds: Methods of Human Judgement Aggregation

Lyon, A., & Pacuit, E. (2013) · Springer eBooks · doi:10.1007/978-1-4614-8806-4_47 · Cited by 30

Internet Search Patterns of Human Immunodeficiency Virus and the Digital Divide in the Russian Federation: Infoveillance Study

Zheluk, A., Quinn, C., Hercz, D., & Gillespie, J. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2936 · Cited by 30

A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections

Mejia, J., Mankad, S., & Gopal, A. (2019) · Information Systems Research · doi:10.1287/isre.2019.0866 · Cited by 33

Dynamic Panel Surveillance of COVID-19 Transmission in the United States to Inform Health Policy: Observational Statistical Study

Oehmke, J. F., Moss, C. B., Singh, L. N., Oehmke, T. B., & Post, L. A. (2020) · Journal of Medical Internet Research · doi:10.2196/21955 · Cited by 30

SARS-CoV-2 Wave Two Surveillance in East Asia and the Pacific: Longitudinal Trend Analysis

Post, L. A., Lin, J. S., Moss, C. B., Murphy, R. L., Ison, M. G., Achenbach, C. J., Resnick, D., Singh, L. N., White, J. I., Boctor, M. J., et al. (2021) · Journal of Medical Internet Research · doi:10.2196/25454 · Cited by 30

Assessing the Impact of the National Smoking Ban in Indoor Public Places in China: Evidence from Quit Smoking Related Online Searches

Huang, J., Zheng, R., & Emery, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065577 · Cited by 30

Detecting internet search activity for mouth cancer in Ireland

Murray, G., O’Rourke, C., Hogan, J., & Fenton, J. E. (2016) · British Journal of Oral and Maxillofacial Surgery · doi:10.1016/j.bjoms.2015.12.005 · Cited by 29

News trends and web search query of HIV/AIDS in Hong Kong

Chiu, A. P. Y., Lin, Q., & He, D. (2017) · PLoS ONE · doi:10.1371/journal.pone.0185004 · Cited by 29

Digital Pandemic Response Systems: A Strategic Management Framework Against Covid-19

Wirtz, B. W., Müller, W. M., & Weyerer, J. C. (2020) · International Journal of Public Administration · doi:10.1080/01900692.2020.1858316 · Cited by 30

Workplace violence during the COVID-19 pandemic: March–October, 2020, United States

Tiesman, H. M., Marsh, S. M., Konda, S., Tomasi, S. E., Wiegand, D. M., Hales, T., & Webb, S. (2022) · Journal of Safety Research · doi:10.1016/j.jsr.2022.07.004 · Cited by 29

Socioeconomic bias in influenza surveillance

Scarpino, S. V., Scott, J. G., Eggo, R. M., Clements, B., Dimitrov, N. B., & Ancel, L. W. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007941 · Cited by 28

The new informatics of pandemic response: humanitarian technology, efficiency, and the subtle retreat of national agency

Wilson, C., & Jumbert, M. G. (2018) · Journal of International Humanitarian Action · doi:10.1186/s41018-018-0036-5 · Cited by 28

Towards a People’s Social Epidemiology: Envisioning a More Inclusive and Equitable Future for Social Epi Research and Practice in the 21st Century

Petteway, R. J., Mujahid, M. S., Allen, A. M., & Morello-Frosch, R. A. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16203983 · Cited by 30

Survey of Text-based Epidemic Intelligence

Joshi, A., Karimi, S., Sparks, R. S., Paris, C. L., & MacIntyre, C. R. (2019) · ACM Computing Surveys · doi:10.1145/3361141 · Cited by 28

Communicating in a public health crisis

Wang, H., Cleary, P. D., Little, J., & Auffray, C. (2020) · The Lancet Digital Health · doi:10.1016/s2589-7500(20)30197-7 · Cited by 28

Location-Based Mobile Gaming and Local Depression Trends: A Study of Pokémon Go

Cheng, Z., Greenwood, B. N., & Pavlou, P. A. (2022) · Journal of Management Information Systems · doi:10.1080/07421222.2021.2023407 · Cited by 27

Use of a Digital Health Application for Influenza Surveillance in China

Hswen, Y., Brownstein, J. S., Liu, J. Z., & Hawkins, J. B. (2017) · American Journal of Public Health · doi:10.2105/ajph.2017.303767 · Cited by 28

Hand, foot and mouth disease in China: evaluating an automated system for the detection of outbreaks

Li, Z., Lai, S., Zhang, H., Wang, L., Zhou, D., Liu, J., Lan, Y., Ma, J., Yu, H., Buckeridge, D. L., et al. (2014) · Bulletin of the World Health Organization · doi:10.2471/blt.13.130666 · Cited by 27

Lessons Learned About Public Health from Online Crowd Surveillance

Hill, S., Merchant, R. M., & Ungar, L. (2013) · Big Data · doi:10.1089/big.2013.0020 · Cited by 26

Public reaction to Chikungunya outbreaks in Italy—Insights from an extensive novel data streams-based structural equation modeling analysis

Mahroum, N., Adawi, M., Sharif, Κ., Waknin, R., Mahagna, H., Bisharat, B., Mahamid, M., Abu‐Much, A., Amital, H., Bragazzi, N. L., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0197337 · Cited by 29

The Surveillance of Chikungunya Virus in a Temperate Climate: Challenges and Possible Solutions from the Experience of Lazio Region, Italy

Vairo, F., Pietrantonj, C. D., Pasqualini, C., Mammone, A., Lanini, S., Nicastri, E., Castilletti, C., Ferraro, F., Bari, V. D., Puro, V., et al. (2018) · Viruses · doi:10.3390/v10090501 · Cited by 27

Ten years’ work on the World Organisation for Animal Health (OIE) Worldwide Animal Disease Notification System

Jebara, K. B., Cáceres, P., Berlingieri, F., & Weber-Vintzel, L. (2012) · Preventive Veterinary Medicine · doi:10.1016/j.prevetmed.2012.08.008 · Cited by 27

Correlation between reported human infection with avian influenza A H7N9 virus and cyber user awareness: what can we learn from digital epidemiology?

Xie, T., Yang, Z., Yang, S., Wu, N., & Li, L. (2014) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2013.11.013 · Cited by 26

Ciclos de atenção a dietas da moda e tendências de busca na internet pelo Google trends

Passos, J. A., Vasconcellos-Silva, P. R., & Santos, L. A. D. S. (2020) · Ciência & Saúde Coletiva · doi:10.1590/1413-81232020257.23892018 · Cited by 26

Evaluation of Local Media Surveillance for Improved Disease Recognition and Monitoring in Global Hotspot Regions

Schwind, J. S., Wolking, D. J., Brownstein, J. S., Mazet, J. A. K., & Smith, W. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110236 · Cited by 27

Clinical Age-Specific Seasonal Conjunctivitis Patterns and Their Online Detection in Twitter, Blog, Forum, and Comment Social Media Posts

Deiner, M. S., McLeod, S. D., Chodosh, J., Oldenburg, C. E., Fathy, C. A., Lietman, T. M., & Porco, T. C. (2018) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.17-22818 · Cited by 26

Open data mining for Taiwan’s dengue epidemic

Wu, C., Kao, S., Shih, C.-H., & Kan, M.-H. (2018) · Acta Tropica · doi:10.1016/j.actatropica.2018.03.017 · Cited by 26

Google Searches and Suicide Rates in Spain, 2004-2013: Correlation Study

Jiménez, A., Germán, M. Á. S., & Ramos, V. (2019) · JMIR Public Health and Surveillance · doi:10.2196/10919 · Cited by 26

Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems

Stevens, K., & Pfeiffer, D. U. (2015) · Spatial and Spatio-temporal Epidemiology · doi:10.1016/j.sste.2015.04.003 · Cited by 25

Searching Choices: Quantifying Decision‐Making Processes Using Search Engine Data

Moat, H. S., Olivola, C. Y., Chater, N., & Preis, T. (2016) · Topics in Cognitive Science · doi:10.1111/tops.12207 · Cited by 25

Social Media Impact of the Food and Drug Administration's Drug Safety Communication Messaging About Zolpidem: Mixed-Methods Analysis

Sinha, M. S., Freifeld, C. C., Brownstein, J. S., Donneyong, M. M., Rausch, P., Lappin, B. M., Zhou, E. H., Pan, G. J. D., Pawar, A. M., Hwang, T. J., et al. (2018) · JMIR Public Health and Surveillance · doi:10.2196/publichealth.7823 · Cited by 27

Syndromic surveillance using web data: A systematic review

Samaras, L., García‐Barriocanal, E., & Sicilia, M. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-819043-2.00002-2 · Cited by 25

Digital epidemiology, deep phenotyping and the enduring fantasy of pathological omniscience

Engelmann, L. (2022) · Big Data & Society · doi:10.1177/20539517211066451 · Cited by 26

Use of Internet Search Data to Monitor Impact of Rotavirus Vaccination in the United States

Desai, R., Lopman, B. A., Shimshoni, Y., Harris, J. P., Patel, M. M., & Parashar, U. D. (2012) · Clinical Infectious Diseases · doi:10.1093/cid/cis121 · Cited by 25

Exploring Health Topics in Chinese Social Media: An Analysis of Sina Weibo

Wang, S., Paul, M. J., & Dredze, M. H. (2014) · Cited by 24

Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study

Anwar, M. M., Khoury, D. Y., Aldridge, A., Parker, S. J., & Conway, K. P. (2020) · JMIR Public Health and Surveillance · doi:10.2196/17574 · Cited by 24

Artificial Intelligence Approach to Predict the COVID-19 Patient’s Recovery

Salama, A., Darwsih, A., & Hassanien, A. E. (2021) · Studies in systems, decision and control · doi:10.1007/978-3-030-63307-3_8 · Cited by 24

Modeling and Predicting Human Infectious Diseases

Perra, N., & Gonçalves, B. (2015) · Springer eBooks · doi:10.1007/978-3-319-14011-7_4 · Cited by 24

Social Media: A Systematic Review to Understand the Evidence and Application in Infodemiology

Guy, S. D., Ratzki‐Leewing, A. A., Bahati, R. M., & Gwadry-Sridhar, F. H. (2012) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-642-29262-0_1 · Cited by 24

Big Data in Environment and Human Health

Fleming, L. E., Tempini, N., Gordon-Brown, H., Nichols, G. L., Sarran, C. E., Vineis, P., Leonardi, G. S., Golding, B. W., Haines, A., Kessel, A. S., et al. (2016) · Oxford Research Encyclopedia of Environmental Science · doi:10.1093/acrefore/9780199389414.013.541 · Cited by 24

FDA workshop on emerging infectious diseases: evaluating emerging infectious diseases (EIDs) for transfusion safety

Atreya, C. D., Nakhasi, H. L., Mied, P. A., Epstein, J. S., Hughes, J. M., GWINN, M. L., Kleinman, S. H., Dodd, R. Y., Stramer, S. L., WALDERHAUG, M. O., et al. (2011) · Transfusion · doi:10.1111/j.1537-2995.2011.03084.x · Cited by 23

Advancing a Framework to Enable Characterization and Evaluation of Data Streams Useful for Biosurveillance

Margevicius, K. J., Generous, N., Taylor-McCabe, K. J., Brown, M. G., Daniel, W. B., Castro, L. A., Hengartner, A., & Deshpande, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0083730 · Cited by 23

Web-Based Surveillance Systems for Human, Animal, and Plant Diseases

Madoff, L. C., & Li, A. (2014) · Microbiology Spectrum · doi:10.1128/microbiolspec.oh-0015-2012 · Cited by 23

Combining Healthcare-Based and Participatory Approaches to Surveillance: Trends in Diarrheal and Respiratory Conditions Collected by a Mobile Phone System by Community Health Workers in Rural Nepal

Meyers, D. J., Ozonoff, A., Baruwal, A., Pande, S., Harsha, A. P., Sharma, R., Schwarz, D., Schwarz, R. K., Bista, D., Halliday, S., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0152738 · Cited by 23

Updating Public Health Teaching Methods in the Era of Social Media

Kapp, J. M., LeMaster, J. W., Lyon, M., Zhang, B., & Hosokawa, M. C. (2009) · Public Health Reports · doi:10.1177/003335490912400603 · Cited by 23

Inferring Fine-grained Details on User Activities and Home Location from Social Media: Detecting Drinking-While-Tweeting Patterns in CommunitiesPreprint

Hossain, N., Hu, T., Feizi, R., White, A. M., Luo, J., & Kautz, H. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1603.03181 · Cited by 26

A Justifiable Investment in AI for Healthcare: Aligning Ambition with Reality

Karpathakis, K., Morley, J., & Floridi, L. (2024) · Minds and Machines · doi:10.1007/s11023-024-09692-y · Cited by 29

Google as a cancer control tool in Queensland

Huang, X., Baade, P. D., Youlden, D. R., Youl, P., Hu, W., & Kimlin, M. G. (2017) · BMC Cancer · doi:10.1186/s12885-017-3828-x · Cited by 22

Can google trends search inform us about the population response and public health impact of abrupt change in alcohol policy? A case study from India during the covid-19 pandemic

Ghosh, A., e-Roub, F., Krishnan, N. C., Choudhury, S., & Basu, A. (2020) · International Journal of Drug Policy · doi:10.1016/j.drugpo.2020.102984 · Cited by 22

Influenza A (H1N1) Virus, 2009 — Online Monitoring

Brownstein, J. S., Freifeld, C. C., & Madoff, L. C. (2009) · New England Journal of Medicine · doi:10.1056/nejmp0904012 · Cited by 74

Applying informal health reports and search queries for public health monitoring: An evaluation of characteristics, potentials, and requirements of online self-reporting, discussions, and search behaviour

Marques Barros, J. C. (2021) · Arrow@dit (Dublin Institute of Technology) · doi:10.13025/16368

Impact of Online Disease Prediction

Kanekar, M. K., & Sawant, D. M. (2022) · International Journal of Science and Research (IJSR) · doi:10.21275/mr22619225429

Internet crawler uses unconventional information sources to track infectious disease outbreaks

Mayor, S. (2008) · BMJ · doi:10.1136/bmj.a742 · Cited by 4

Innovative disease surveillance

Brownstein, J. S. (2018) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2018.04.3575