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Digital Epidemiology – the future of health care & privacy concerns

Digital Epidemiology – the future of health care & privacy concerns

UPSC CSE Mains Syllabus: GS-2- Issues relating to development and management of Social Sector/Services relating to Health, Education, Human Resources.

With the outbreak of the novel coronavirus, contact tracing apps have emerged as the best examples of digital epidemiology, a nascent field where digital data is used to understand patterns of disease, and chart out interventions to prevent it.

What has led to the growth of digital epidemiology?

  • Epidemiology, literally the “study of what is upon people”, is concerned with the dynamics of health and disease in human populations.
  • Research in epidemiology aims to identify the distribution, incidence, and etiology of human diseasesto improve the understanding of the causes of diseases and to prevent their spread.
  • Traditionally, epidemiology has been based on data collected by public health agencies through health personnel in hospitals, doctors’ offices, and out in the field.
  • In recent years, however, novel data sources have emerged where data are frequently collected directly from individuals through the digital traces they leave as a consequence of modern communication and an increased use of electronic devices.
  • It involves studying various factors (age, gender, location and other determinants) of the general population to study disease patterns, spread, incidence, and prevalence.
  • Traditional epidemiologists say it is a field founded on the pillars of science and is thus extremely robust.
  • Data is mostly collected by field staffthrough house-to-house surveys and from hospital records.
  • Digital epidemiology, as the term suggests, uses digital data to study the same factors.
  • Digital Epidemiology is a new field that has been growing rapidly in the past few years, fueled by the increasing availability of data and computing power, as well as by breakthroughs in data analytics methods.
  • The goal of epidemiology, is to understand the patterns of disease and health dynamics in populations as well as the causes of these patterns, and to use this understanding to mitigate and prevent disease, and to promote health.
  • Digitaldata sources, when harnessed appropriately, can provide local and timely information about disease and health dynamics in populations around the world.

The rapid, unprecedented increase in the availability of relevant data from various digital sources creates considerable technical and computational challenges.

Good examples of digital epidemiology:

  • An article published in October 2018 in a Korean journal, Healthcare Informatics Research, listed Google Flu Trends as one of the early examples of digital epidemiology.
  • In it researchers from Google and U.S. Centers for Disease Control and Prevention published a method to estimate flu activity by region using search engine queries.
  • The article also cites the use of Twitter to track level of disease activityand concern about the influenza H1N1 pandemic in 2011, and an attempt by the Boston Children’s Hospital to estimate the level of influenza-like illnesses, “in near-real-time, in the U.S. by monitoring the rate of influenza-related Wikipedia article views on a daily basis”.
  • Twitter data mining has been one of the best uses of digital epidemiology in his view. Also, systems like Healthmapare good examples.
  • In 2020, the digital contact tracing appswill certainly become the best examples of digital epidemiology.
  • In other words, Epidemiology that uses data that was generated outside the public health system, i.e. with data that was not generated with the primary purpose of doing epidemiology.

The field of digital epidemiology is new, but has been growing rapidly owing to the increasing amounts of data generated on the internet, especially on social media.


  • Digital epidemiology has an important role to play in preventing disease outbreaks.
  • One of the big advantages of digital speed is it is fastand will be a key contributor in keeping outbreaks under control.

Aarogya Setu:

  • Aarogya Setu, the Indian government’s COVID-19 contract tracing mobile application, is being used by over 13 crore people.
  • The app says “as more and more people use it, its effectiveness will increase”.
  • The app tracks the interaction of its users through Bluetooth and a location-generated social graph.
  • If a user tests positive for COVID-19, other app users who may have been in his/her close proximity, knowingly or unknowingly, are alerted and guided on self-isolation and steps to be taken if they develop symptoms.

Privacy Concerns:

  • Cybersecurity experts and activists have said that Aarogya Setu places data of citizens at the disposition of the government.
  • In response to one such petition, highlighting the violation of the right to privacy, the Centre has told the Karnataka High Court that it is not mandatory for rail and air travellers to download the app.
  • Multiple COVID-19 trackers like Aarogya Setu have been launched across the world.
  • While government employees have been asked to use the app, it was also made mandatory for rail and air travellers.
  • Data privacy is an element of huge concern. COVID-19 trackers like Aarogya Setu, which collect contact network information and location information, can be privacy-intrusive.
  • The privacy mandate under the law (Information Technology Act)as it stands today, is specific to body corporates.

Road ahead:

  • The Puttaswamy judgementmakes it clear that data principles of privacy and consent are equally applicable for the government.
  • It adds that for the use of Aarogya Setu, the government should be transparent about where the data is going, what are they using it for and how one can be assured that it will be deleted when all this is over.
  • The app should be consent-based.

Source:” The Hindu“.


How digital epidemiology is transforming the way epidemic are countered? Critically analyse the benefits and concerns of digital epidemiology.