Journals / Turkish Journal of Public Health / 2020 / Cilt: 18 Sayı: 2

Digital epidemiology

Dijital epidemiyoloji

Pages
192–203
Publication Date
2020-08-31
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In this way, it has been tried to provide a basis for the opportunities and assumptions and difficulties that this new field provides for health politicians, public health experts and researchers.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Digital epidemiology is an innovative scientific discipline that develops with greater access to scientific knowledge and digital tools.
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Key Findings & Data:The distribution of health related situations in certain societies and the determinants of health are obtained through online platforms and is used to improve health and prevent disease.
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Conclusion & Impact:In this way, it has been tried to provide a basis for the opportunities and assumptions and difficulties that this new field provides for health politicians, public health experts and researchers.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Epidemiyoloji · dijital epidemiyoloji · halk sağlığı

Abstract

Digital epidemiology is an innovative scientific discipline that develops with greater access to scientific knowledge and digital tools. The distribution of health related situations in certain societies and the determinants of health are obtained through online platforms and is used to improve health and prevent disease. This new approach is based on the idea that public health information is produced directly by the public using online services without having to be included in the health care system. Web search records, chat rooms, social networks, blogs and online news media are among these online tools. Some infectious and chronic disease data can be identified through these data sources and can be used for many epidemiological purposes such as assessment of health behaviors and attitudes, early detection of disease outbreaks. Researches has shown increasing parallel evidence that it can be a reliable tool for predicting many diseases and treatments in line with actual disease epidemiology in the world. In this study, it is aimed to present the findings of the researches in this field by addressing the concept of digital epidemiology, its applications, opportunities and difficulties. In this way, it has been tried to provide a basis for the opportunities and assumptions and difficulties that this new field provides for health politicians, public health experts and researchers.

Özet

Dijital epidemiyoloji, bilimsel bilgiye ve dijital araçlara daha fazla erişim ile gelişen yenilikçi bir bilimsel disiplindir. Belirli toplumlardaki sağlıkla ilgili durumların dağılımının ve sağlığın belirleyicilerinin çevrimiçi platformlar aracılığı ile elde edilmesi ve bu bilginin sağlığı geliştirmek ve hastalığı önlemek için kullanılmasıdır. Bu yeni yaklaşım, halk sağlığıyla ilgili bilgilerin, sağlık hizmeti sistemine dahil olmaları gerekmeden, doğrudan halk tarafından çevrimiçi hizmetleri kullanmaları yoluyla üretildiği fikrine dayanmaktadır. Web arama kayıtları, sohbet odaları, sosyal ağlar, bloglar ve çevrimiçi haber medyası; bu çevrimiçi araçlardandır. Bazı bulaşıcı ve kronik hastalık verileri, bu veri kaynakları aracılığıyla tespit edilebilmekte ve sağlık davranış ve tutumlarının değerlendirilmesi, hastalık salgınlarının erken tespiti gibi birçok epidemiyolojik amaç için kullanılabilmektedir. Yapılan araştırmalar, dünyadaki gerçek hastalık epidemiyolojisine paralel olarak birçok hastalığı ve tedaviyi tahmin etmek için güvenilir bir araç olabileceğine dair artan sonuçlar sunmaktadır. Bu çalışma kapsamında dijital epidemiyoloji kavramına, uygulamalarına, fırsat ve zorluklarına değinilerek, bu alanda yapılan araştırmaların bulgularının sunulması amaçlanmıştır. Böylelikle, bu yeni alanın sağlık politikacılarına, halk sağlığı uzmanlarına, araştırmacılara sağladığı fırsatlar ve getirdiği varsayım ve zorluklar hakkında bir temel oluşturulmaya çalışılmıştır.

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Cite This Article

DONAR, G. B. (2020). Digital epidemiology. Turkish Journal of Public Health, Cilt: 18 Sayı: 2, 192–203. https://ajindex.com/articles/944281

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References (15)

  1. Bailey, L. A., Gordis, L., Green, M. (1994). Reference guide on epidemiology. Reference Manual on Scientific Evidence
  2. Eysenbach, G. (2009). Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. Journal of medical Internet research, 11(1), e11
  3. International Telecommunication Union. (2011). Measuring the information society 2011. International Telecommunication Union
  4. Salathé, M., Bengtsson, L., Bodnar, T. J., Brewer, D. D., Brownstein, J. S., Buckee, C.,. & Vespignani, A. (2012). Digital epidemiology. PLoS computational biology, 8(7), e1002616
  5. Brownstein, J. S., Freifeld, C. C., Madoff, L. C. (2009). Digital disease detection—harnessing the Web for public health surveillance. New England Journal of Medicine, 360:21, 2153-2157
  6. Hay, S. I., George, D. B., Moyes, C. L., & Brownstein, J. S. (2013). Big data opportunities for global infectious disease surveillance. PLoS medicine, 10(4), e1001413
  7. Ekman, A., & Litton, J. E. (2007). New times, new needs; e-epidemiology. European journal of epidemiology, 22(5), 285-292
  8. Jessop, L. S. (2015). Use of web-based epidemiology in the investigation of risk factors for common mental disorder (Doctoral dissertation, Cardiff University)
  9. Salathé, M. (2018). Digital epidemiology: what is it, and where is it going?. Life sciences, society and policy, 14(1), 1
  10. Vayena, E. (2015). Ethical Challenges of Big Data in Public HealthEffy Vayena. European Journal of Public Health, 25(suppl_3)
  11. Roth, J. A., Battegay, M., Juchler, F., Vogt, J. E., & Widmer, A. F. (2018). Introduction to machine learning in digital healthcare epidemiology. Infection Control & Hospital Epidemiology, 39(12), 1457-1462
  12. D’Ambrosio, A., Tozzi, A., Gesualdo, F. (2016). Digital epidemiology. Using the internet for population health. How to listen and what can we discoverAngelo D'Ambrosio. European Journal of Public Health, 26:1
  13. Salathé, M., & Khandelwal, S. (2011). Assessing vaccination sentiments with online social media: implications for infectious disease dynamics and control. PLoS computational biology, 7(10), e1002199
  14. Salathé, M., Freifeld, C. C., Mekaru, S. R., Tomasulo, A. F., & Brownstein, J. S. (2013). Influenza A (H7N9) and the importance of digital epidemiology. The New England journal of medicine, 369(5), 401
  15. Höhle, M. (2017). A statistician’s perspective on digital epide