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Digital Epidemiology: Harnessing Big Data for Early Detection and Monitoring of Viral Outbreaks

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Date 2024 Aug 2
PMID 39091623
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Abstract

Digital epidemiology is the process of investigating the dynamics of disease-related patterns, both social and clinical, as well as the causes of these trends in epidemiology. Digital epidemiology, utilising big data from a variety of digital sources, has emerged as a viable method for early detection and monitoring of viral outbreaks. The present review gives an overview of digital epidemiology, emphasising its importance in the timely detection of infectious disease outbreaks. Researchers may discover and track outbreaks in real time using digital data sources such as search engine queries, social media trends, and digital health records. However, data quality, concerns about privacy, and data interoperability must be addressed to maximise the effectiveness of digital epidemiology. As the global landscape of infectious diseases evolves, integrating digital epidemiology becomes critical to improving pandemic preparedness and response efforts. Integrating digital epidemiology into routine monitoring systems has the potential to improve global health outcomes and save lives in the event of viral outbreaks.

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References
1.
Radin J, Wineinger N, Topol E, Steinhubl S . Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study. Lancet Digit Health. 2020; 2(2):e85-e93. PMC: 8048388. DOI: 10.1016/S2589-7500(19)30222-5. View

2.
Taquet M, Geddes J, Husain M, Luciano S, Harrison P . 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records. Lancet Psychiatry. 2021; 8(5):416-427. PMC: 8023694. DOI: 10.1016/S2215-0366(21)00084-5. View

3.
Ndlovu K, Scott R, Mars M . Interoperability opportunities and challenges in linking mhealth applications and eRecord systems: Botswana as an exemplar. BMC Med Inform Decis Mak. 2021; 21(1):246. PMC: 8379582. DOI: 10.1186/s12911-021-01606-7. View

4.
Higgins T, Wu A, Sharma D, Illing E, Rubel K, Ting J . Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study. JMIR Public Health Surveill. 2020; 6(2):e19702. PMC: 7244220. DOI: 10.2196/19702. View

5.
Razzak M, Imran M, Xu G . Big data analytics for preventive medicine. Neural Comput Appl. 2020; 32(9):4417-4451. PMC: 7088441. DOI: 10.1007/s00521-019-04095-y. View