Two days ago I was asked if a widespread adoption of personal digital twins would help in controlling the ongoing Covid-19 epidemic. I tried to provide a sensible answer to a science fiction like question… If you read Italian you can find it here.
Let me summarise it. Since the shift from nomadic life to aggregation in clusters/cities humanity has faced epidemics. It is the cluster of people that provides the fertile environment for viruses to jump from one host to the next generating an epidemic. The geographical distance among clusters is a barrier to the spread of the epidemics. This can only happen if someone travels from one cluster to another. In the past, as shown in the graphics, the epidemics spread along the commerce, maritime and land, pathways. Travel was slow and sporadic so an epidemic took years to become a pandemic.
Today we have both bigger clusters (megacities and cities that on average are much bigger than the ones of the past) and much faster and “denser” traffic among clusters. This fuels both epidemics and pandemics.
We also have, luckily, much better tools to fight the effect of viruses (for fighting viruses we need a vaccine, and it takes time to develop one for a virus coming out of the blue, such as the Coronavirus we are facing today that jumped from animals, possibly bats, to humans just few months ago). However, these tools come in limited supply and therefore it is of paramount importance to detect the potential insurgence of epidemics as soon as possible and delay the spreading.
The graphic presented was created based on historical information of actual contagion and it would not have been useful to people at that time. What is needed is the possibility to draw such a graphic in real time and to be able to predict its evolution. Today there are tools based on data harvested from various sources interpreted through epidemic models (taking into account the ways contagion happens and its diffusion speed) that look at the movement of people within a community and across different areas.
Social media are used to capture the manifestation of a virus and the habits of people that can lead to exposure. The current outbreak of coronavirus is been monitored and its growth predicted in various centres like the Network Science Institute at Northeastern University in Boston through big data analytics applied at social networks.
Social networks can indeed be used as a sensor but their sensitivity and in particular their resolution is not optimal. This is where personal digital twins may play a role. A personal digital twin is a representation of various aspects of a person that might include the movement of the person, the interactions that person has in the physical space with others persons and the health status (like presence of fever, coughing…). These data can be accrued by the personal digital twin using a few sensors already available. Position and movement can easily be monitored by extracting data from that person’s smartphone, health status can be monitored through wearable sensors (including a smartwatch: body temperature , heart beats…).
Let’s start by saying that today we do not have personal digital twins. We have a number of companies that are starting to propose the creation of personal digital twins and specifically to use them in the healthcare domain, like General Electric, Siemens, Philips … however we do not have a real adoption of digital twin technology to mirror individual persons.
Let’s suppose that the evolution of personalised healthcare in this decade will result in the adoption of personal digital twins. By the end of this decade one could imagine that every person will be flanked by a digital twin, able to raise a red flag in case of need. This red flag can be customised by the person, or more likely by that person’s physician, to generate an information when a certain situation emerges, or when there is a risk for the emergence of a certain situation.
We can have, as an example, that all personal digital twins can be designed to accept instructions to raise a red flag when a mix of data creates a specific pattern, like temperature at rest rising over 37.5 C and occurrence of rapid breathing, This, as we know, is a sign of a possible Covid-19 infection.
Healthcare institutions at government level can receive these red flags and in turn can analyse a variety of connected data (like the occurrence of these red flags in a specific area, analyse the movement of people in the previous months to correlate this with the emergence of other red flags…). Notice that in this scenario government and healthcare institutions may impose some kind of data analytics and red flag generation on all personal digital twins to harvest data.
This would create an awareness of an incipient epidemics and make accurate forecast of possible contagion based on red flagged people movement. It would provide a most timely and most accurate picture of the situation, worldwide.
All this is great, however it is also raising big issues in terms of privacy and government/institution control. Personal Digital Twins may take the Orwell 1984 vision a step further. For sure it takes all of our society into an uncharted territory.
We are still a few years away from this scenario. However Digital Twins are already considered in the simulation of some epidemics to support the creation of flu vaccines.