The 2019 NYU Abu Dhabi iGEM team aims to create a device to detect bacterial communicable diseases through saliva. The device would be primarily used in country health checkpoints and airports with the aim to prevent the contagion
of diseases across multiple countries. We will use a Cas13a CRISPR complex and RPA to detect the genes of the targeted pathogens :MRSA, TB, Bordetella pertussis.
As air travel becomes more worldwide
accessible, the inherent risks and threats have increased proportionally with it. Air travel is a vector for the transmission of communicable diseases, allowing a local outbreak to spread to possibly anywhere around the world.
Currently there is little reliable infrastructure to process the hundreds of passengers that could arrive to an airport hub on a given day, let alone the millions that pass through every year. A more connected world should
be one where every individual is informed on the risks inherent with their connectedness. Our device and software seeks to shed light on the spreading patterns of travel borne diseases and make that information accessible to
every entity that seeks it.
According to the work of Mangili and Gendreau, there are four ways through which pathogens can spread: contact, airborne, common vehicle, and vector-borne. Modern airports, according
to Magili et al. , support all these channels, however contact through large droplets and airborne mechanism are of higher risk because of the proximity of the high density of highly packed crowds. Large droplets are a form
of contact where droplets of more than 5 microns that are generated as a result of an infected person sneezing or coughing. Airborne transmission happens when an infectious agent is aerosolized in droplet nuclei of less than
5 micron. Figure 1 shows a comprehensive view of how the pathogen charged air is spread.
Source: WHO. Tuberculosis and air travel: guidelines for prevention and control.
Current statistical models that bring together air traffic data and disease outbreak precedents can quantify risk to a certain extent but as can
be seen in the work of Tatem et al. , Wilder-Smith et al. and Mangili, the lack of real-time epidemiological data is a major bottleneck in creating a reliable mathematical model.
The Abu Dhabi and Dubai airports
are the main hubs in the Middle East for air travel. The Dubai airport alone is the world’s busiest airport by international passenger traffic. The worldwide increase in air travel only makes the Abu Dhabi and Dubai airports
greater avenues for the spread of disease. Having a reliable device for communicable disease detection that is efficient enough to be used within a passenger’s average time passing through an airport would be the ultimate way
to keep the risks of contagion in check.
Inspired by the microfluidics principles and the areas of improvement of our team’s past project, Pathogene, we decided to focus on building a device that would be able
to detect pathogens prone to be spread in the airport as shown in our research. We aim on trying new methods of post-amplification signal enhancement through electric fields in order to increase the resolution of the last year’s
NYUD iGEM device. Through the work of Al Shamsi and Hidalgo on strategic diffusion of complex networks and inspired by Tatem et al.’s work on Disease Airline Importation Risk software (Figure 2), we also set out to build an
Application Programming Interface through which institutions and individuals can have access to the data and data structures regarding disease contagion.
Furthermore, we strongly hold the belief that in addition to a working biological protocol and a proof of concept device, making executable files and tools such as the API available, would make logistics easier and coordination with healthcare provider much more efficient, as listed in the “Airport preparedness guidelines for outbreaks of communicable disease” issues by the International Airport Council.
