The coronavirus pandemic has brought disruptive technology solutions to slow the spread of the virus and reduce its impact. Contact tracing using mobile technology is a promising but controversial solution that has been tested in some countries and proposed in the United States.

The Washington Post reports that millions of people around the world are already under some form of surveillance in an effort to track people’s movements and trace the spread.

Notably, at least 27 countries have started using data from cell phones to track the movements of their citizens. While this approach has a great potential for the public good, the implementation and adoption of such technology raises important questions about transparency, AI ethics and data privacy.

Fighting the spread of  with smart technology.
Contact tracing may be one of the most effective ways to prevent an outbreak. However,  is not a specific outbreak. The virus is often transmitted by individuals who exhibit no symptoms of infection and may not even realize that they are carrying the virus.

Standard contact tracing usually involves individuals who are symptomatic and know they are carrying the infection. Because of this, traditional contact tracing methods are challenging and problematic.

Oxford University’s Big Data Institute has proposed a solution for a mobile contact tracing application that is much more agile, traditional and scalable than manual contact tracing methods.

The team has developed a mathematical model that is designed to prevent epidemics when implemented on mobile devices by a large segment of the population.

It is headed to reduce manual contact tracing from 72 hours to four hours. By replacing weeks of manual work doing contact tracing, mobile apps can slow the spread much faster than traditional methods.

For the proposed mobile tracing method to be effective, certain hurdles have to be overcome.

First, the majority of the population – which includes symptomatic and asymptomatic individuals – should voluntarily opt-in and adopt the application. The Oxford research team estimates that around 60% of the population will need to use applications for mobile tracing to reach enough new virus cases to have an impact on the spread of the virus.

Another challenge lies in widespread and accessible testing. For the application to work, the majority of the population will need access to reliable testing to properly and thoroughly survey potential outbreaks.

There is much evidence that the application of mobile technology, as well as the application of rigorous widespread testing, can reduce  infection and mortality rates.

Taiwan was able to better control the outbreak of Why?
A recent Stanford report shows how Taiwan – a country just 130km from the epicenter of the outbreak in China – was able to contain the outbreak without the drastic lockdown measures in place in many advanced economies.

How did Taiwan limit and control the spread of the virus? The report highlights five interconnected factors: pandemic preparedness, national electronic health records databases, widespread testing, big data analysis, and the use of mobile technology to track the movements of individuals who have contracted tested positive for

Within 72 hours of the outbreak, a comprehensive case identification protocol was established based on travel history. High-risk individuals were monitored through their mobile devices.

Health officials were then able to trace the activities of high-risk subjects and reduce the risk of further transmission through targeted isolation measures. Taiwan can serve as a template for mitigating future pandemics.

Balancing the public interest and data privacy rights.
Innovative initiatives are underway by major tech companies, notably Google, Apple and Facebook, to track and analyze how the virus is spreading, and measure the effectiveness of social distancing measures.

Facebook’s Data for Good project is designed to track users’ movements to measure and anticipate potential outbreaks.

In the context of the  outbreak, researchers, non-profits and public agencies can leverage data—that is, anonymized and aggregated—to evaluate and implement strategies to slow the spread. However, such initiatives raise concerns about transparency and data privacy rights.When the processing of PII is necessary for the public interest, it may be done without obtaining the consent of the data subject.

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