1. Eckhoff PA, Tatem AJ. Digital methods in epidemiology can transform disease control. Int Health. 2015; 7(2):77–78.
Article
2. Salathe M. Digital epidemiology: what is it, and where is it going? Life Sci Soc Policy. 2018; 14(1):1.
Article
3. Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L. Detecting influenza epidemics using search engine query data. Nature. 2009; 457(7232):1012–1014.
Article
4. Nuti SV, Wayda B, Ranasinghe I, Wang S, Dreyer RP, Chen SI, et al. The use of google trends in health care research: a systematic review. PLoS One. 2014; 9(10):e109583.
Article
5. Lazer D, Kennedy R, King G, Vespignani A. Big data: the parable of Google Flu: traps in big data analysis. Science. 2014; 343(6176):1203–1205.
Article
6. Signorini A, Segre AM, Polgreen PM. The use of Twitter to track levels of disease activity and public concern in the U.S. during the influenza A H1N1 pandemic. PLoS One. 2011; 6(5):e19467.
Article
7. Salathe M, Khandelwal S. Assessing vaccination sentiments with online social media: implications for infectious disease dynamics and control. PLoS Comput Biol. 2011; 7(10):e1002199.
Article
8. Freifeld CC, Brownstein JS, Menone CM, Bao W, Filice R, Kass-Hout T, et al. Digital drug safety surveillance: monitoring pharmaceutical products in twitter. Drug Saf. 2014; 37(5):343–350.
Article
9. McIver DJ, Brownstein JS. Wikipedia usage estimates prevalence of influenza-like illness in the United States in near real-time. PLoS Comput Biol. 2014; 10(4):e1003581.
Article
10. Wesolowski A, Eagle N, Tatem AJ, Smith DL, Noor AM, Snow RW, et al. Quantifying the impact of human mobility on malaria. Science. 2012; 338(6104):267–270.
Article
11. Bengtsson L, Lu X, Thorson A, Garfield R, von Schreeb J. Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti. PLoS Med. 2011; 8(8):e1001083.
Article
12. Zaccai JH. How to assess epidemiological studies. Postgrad Med J. 2004; 80(941):140–147.
Article
13. Polit DF, Beck CT. Nursing research: generating and assessing evidence for nursing practice. 10th ed. Philadelphia (PA): Lippincott Williams & Wilkins;2017.
14. Sylvestre E, Bouzille G, Breton M, Cuggia M, Campillo-Gimenez B. Retrieving the vital status of patients with cancer using online obituaries. Stud Health Technol Inform. 2018; 247:571–575.
15. Tourassi G, Yoon HJ, Xu S, Han X. The utility of web mining for epidemiological research: studying the association between parity and cancer risk. J Am Med Inform Assoc. 2016; 23(3):588–595.
Article
16. Edoh T. Risk prevention of spreading emerging infectious diseases using a hybridcrowdsensing paradigm, optical sensors, and smartphone. J Med Syst. 2018; 42(5):91.
Article
17. Moon RJ, Curtis EM, Davies JH, Cooper C, Harvey NC. Seasonal variation in Internet searches for vitamin D. Arch Osteoporos. 2017; 12(1):28.
Article
18. Chary M, Genes N, Giraud-Carrier C, Hanson C, Nelson LS, Manini AF. Epidemiology from Tweets: estimating misuse of prescription opioids in the USA from social media. J Med Toxicol. 2017; 13(4):278–286.
Article
19. Towers S, Afzal S, Bernal G, Bliss N, Brown S, Espinoza B, et al. Mass media and the contagion of fear: the case of Ebola in America. PLoS One. 2015; 10(6):e0129179.
Article
20. Ram S, Zhang W, Williams M, Pengetnze Y. Predicting asthma-related emergency department visits using big data. IEEE J Biomed Health Inform. 2015; 19(4):1216–1223.
Article
21. Zhang X, Dang S, Ji F, Shi J, Li Y, Li M, et al. Seasonality of cellulitis: evidence from Google Trends. Infect Drug Resist. 2018; 11:689–693.
Article
22. Miller M, Banerjee T, Muppalla R, Romine W, Sheth A. What are people tweeting about Zika? An exploratory study concerning its symptoms, treatment, transmission, and prevention. JMIR Public Health Surveill. 2017; 3(2):e38.
Article
23. Phillips CA, Barz Leahy A, Li Y, Schapira MM, Bailey LC, Merchant RM. Relationship between state-level Google online search volume and cancer incidence in the United States: retrospective study. J Med Internet Res. 2018; 20(1):e6.
Article
24. McGough SF, Brownstein JS, Hawkins JB, Santillana M. Forecasting Zika incidence in the 2016 Latin America outbreak combining traditional disease surveillance with search, social media, and news report data. PLoS Negl Trop Dis. 2017; 11(1):e0005295.
Article
25. Generous N, Fairchild G, Deshpande A, Del Valle SY, Priedhorsky R. Global disease monitoring and forecasting with Wikipedia. PLoS Comput Biol. 2014; 10(11):e1003892.
Article
26. Adrover C, Bodnar T, Huang Z, Telenti A, Salathe M. Identifying adverse effects of HIV drug treatment and associated sentiments using Twitter. JMIR Public Health Surveill. 2015; 1(2):e7.
Article
27. Nsoesie EO, Buckeridge DL, Brownstein JS. Guess who's not coming to dinner? Evaluating online restaurant reservations for disease surveillance. J Med Internet Res. 2014; 16(1):e22.
Article
28. Valson JS, Soman B. Spatiotemporal clustering of dengue cases in Thiruvananthapuram district, Kerala. Indian J Public Health. 2017; 61(2):74–80.
29. Park SE, Tang L, Bie B, Zhi D. All pins are not created equal communicating skin cancer visually on Pinterest. Transl Behav Med. 2018; 04. 17. [Epub]. DOI:
10.1093/tbm/iby044.
Article
30. Dettori M, Arru B, Azara A, Piana A, Mariotti G, Camerada MV, et al. In the digital era, is community outrage a feasible proxy indicator of emotional epidemiology? The case of meningococcal disease in Sardinia, Italy. Int J Environ Res Public Health. 2018; 15(7):E1512.
Article
31. Roche B, Gaillard B, Leger L, Pelagie-Moutenda R, Sochacki T, Cazelles B, et al. An ecological and digital epidemiology analysis on the role of human behavior on the 2014 Chikungunya outbreak in Martinique. Sci Rep. 2017; 7(1):5967.
Article
32. Pollett S, Boscardin WJ, Azziz-Baumgartner E, Tinoco YO, Soto G, Romero C, et al. Evaluating Google Flu Trends in Latin America: important lessons for the next phase of digital disease detection. Clin Infect Dis. 2017; 64(1):34–41.
Article
33. Hossain N, Househ M. Using HealthMap to analyse Middle East Respiratory Syndrome (MERS) data. Stud Health Technol Inform. 2016; 226:213–216.