Loop Holes in Digital Epidemiology — What are the Ethical Concerns?
The emergence and re-emergence of highly contagious diseases like SARS, H1N5, Ebola, and Zika in recent years have contributed to a public perception that infectious diseases and their outbreaks are becoming increasingly more of a threat to public health globally than ever before.
Digital epidemiology in infectious disease is a new discipline in the area of big data, which promises faster detection of disease outbreaks and improved surveillance as well as a reduction in administrative burden, among other things.
Some public health agencies around the world have adopted digital technologies to help them determine who is infected with current pandemic COVID-19, then trace those with who people into treatment or quarantine.
Stanford Health policy’s Michelle Mello and Jason Wang examine the uses of digital technologies to fight COVID-19 around the world and here at home and weigh key ethical and governance considerations.
Mello and Wand believe the issue is not whether to use novel data sources to combat the coronavirus, but how to use them wisely.
Digital epidemiology of the global pandemic has become the new normal in countries whose citizens are used to government surveillance, such as India, Singapore, Taiwan, China, and Israel. And contract tracing has great potential for fighting the coronavirus, as it offers a low-cost, scalable alternative to having public health workers locate contacts of each infected person.
Story of India and the USA — countries with the highest COVID-19 spike
Aarogya Setu, the Indian government’s COVID-19 contract tracing mobile application, is being used by over 13 crores people. On the App’s home page, a quote by PM Narendra Modi appears, where he insists that “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 while government employee has been asked to sue the app, it was also made mandatory for rail and air travelers.
Cybersecurity experts and activists have dubbed the Aarogya Setu government surveillance tool. In response to one such petition, highlighting the violation of the right to privacy, the center has told the Karnataka state high court it is not mandatory for rail and air travelers to download the app. Multiple COVID-19 trackers like Aarogya Setu have been launched across the world.
The United States has the largest number of COVID-19 cases and deaths, far surpassing China, where the coronavirus first took flight.
The companies are working to enable smartphone users to download updates to their operating systems that will make it possible to track the physical proximity between phones.
If a user later tests positive for the coronavirus, they can report it through the app and any users who have been in contact with those patients will receive a notification.
These new public health demands to share personal health data are bumping up against the privacy concerns so entrenched in the democracies.
Digital epidemiology leverages data generated outside the public health system to better understand how the disease is spreading and hot it can be contained these include cell phones geolocation data information from wearable, video surveillance, social media posts, internet searches, and news reports, as well as crowdsourcing apps that collect self-reported symptoms.
What do u understand by digital epidemiology and what led to the growth of it?
The traditional form of epidemiology, considered a basis of public health, consists of 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 field founded on the pillars of science and is thus extremely robust, data is mostly collected by field staff through the house to house drivers and form hospital records. Digital epidemiology, as the term suggests uses digital data to study the same factors.
According to the Swiss epidemiologist Marcel Salathe, director of the Digital Epidemiology Lab in Lausanne defines the field in a more nuanced manner.
Epidemiology 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 growing to the increasing amounts of data generated on the internet, especially in social media.
Example of digital epidemiology
Twitter data mining has been one of the uses of digital epidemiology. Also, systems like health maps are good examples.
In 2020, digital contact tracing apps will certainly become the best examples of digital epidemiology.
In October 2018. There was an article published in Korean journal — listed Google Flu Trends as one the early example of digital epidemiology, wherein 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 the level of disease activity and concern about the influenza H1N1 pandemic in 2011, and an attempt by the Boston Children’s Hospital to estimate the level of influenza-related Wikipedia article views on a daily basis.
Are these technologies raise a number of ethical issues?
For instance, some have voiced concern that trust and participation in such approached may be unevenly distributed across society; others have raised privacy concerns, yet counterbalancing such concerns is the argument that sometimes it is unethical not to use available data; some trade-offs may be not only ethically justifiable, but ethically obligatory.
Collecting personal health data, the app assigns each of them a COVID-19 risk code — red, yellow, or they note one of the most controversial applications of digital epidemiology during the pandemic has been the Chinese government’s requirement that citizens in 200 cities install an Alipay app on their smartphones. After green — that determines how they are permitted to move around their communities.
“The coding algorithm reportedly incorporates information on time spent at risky locations and frequency of contact with other people,” “Public dissatisfaction with the app arose from lack of transparency about the reasons people were classified into particular groups and mismatch with individuals’ own believes about their risk level.”
Yet governments with massive troves of their citizens’ personal data at their disposal have been able to quickly track down those at elevated risk of infection and help them get tested. The authors note that the Taiwanese government, for example, linked immigration and customs data on travelers to National Health Insurance data on hospital and clinic visits to identify individuals whose symptoms could be due to contracting the coronavirus.
New Zealand, Thailand, and Taiwan use cell phone location data to monitor the movement of people subject to quarantine or isolation orders. The authors note China, Poland, and Russia have gone even further, using facial-recognition software to monitor compliance with orders.
Such measures, though intrusive, help reduce the need for labor-intensive, in-person monitoring,” they write. “Location data from cell phones and social media apps can also be used to monitor population-level adherence to social distancing orders.”
Digital contact tracing has garnered the most attention, however. Mello and Wang note that a real-time experiment is underway in Singapore, where the government in March requested that its citizens install a government-developed smartphone app called Trace Together. It uses Bluetooth technology to exchange identifier numbers with the phones of other Trace Together users within 6 feet, sharing data with the government only if the user becomes subject to contact tracing due to a COVID-19 diagnosis. As of late April 2020, the authors note, similar apps have been rolled out in nearly 30 countries.
Israel and South Korea have gone even further than Singapore, using geolocation data without seeking consent and texting people who come into contact with COVID-19 cases that they must immediately quarantine.
What policies should be adopted considering the ethics of digital surveillance during a future pandemic?
The use of digital technology must be judged the least burdensome alternative that would accomplish the public health objective. When digital technologies are used, this principle can also help minimize privacy intrusions by identifying the minimum necessary data elements and duration and scope of use.
The wisdom of adopting a digital surveillance measure should be evaluated by considering what and how they likely would be used instead of the technology, such as shelter-at-home and business closure orders. Though intrusive, technologies offer the prospect of expediting the end of more burdensome public health orders imposed on the entire public and avoiding them in future outbreaks.
Though more effective than relying on police to detect violations, for “the benefits of stringently enforcing mass shelter-at-home orders are not entirely clear, and the potential for strict enforcement — particularly through electronic eyes — to undermine trust in government and stoke resistance is troublesome.”
The researchers endorse the use of electronic monitoring to support individuals subject to isolation, quarantine, and shelter-at-home orders, such as virtual visits from public health workers to check symptoms and ask if people need help fulfilling basic needs like food. But the use of electronic monitoring to enforce these orders is more problematic,
Although about 20% of the U.S. population lacks smartphones, “using the technology can conserve scarce human resources for working with those who don’t.” The researchers endorse an “opt-out” approach, in which smartphone users who object to the technology can choose to uninstall it. And they urge that data about COVID-19 cases and their contacts, including geolocation data, be shared with public health officials.
To ensure that these technologies are deployed responsibly, Mello and Wang argue they must be implemented through transparent processes with public input. An oversight body and carefully crafted data-use agreements would help assure a trustworthy system and lay down new rules-of-the-road for future pandemics.