On June 8, 2021, HORASIS: the Global Visions Community held its annual Global Meeting, co-chaired by Murat Seitnepesov, Chairman of Caspian Week. Because of the COVID-19 pandemic, the event was held as a virtual meeting. One of the most thought-provoking topics was our key session Preparing for a New Pandemic: Global System for Preparedness for Disease X (https://www.youtube.com/watch?v=4otWkAQY6x4).
The main question was whether a global system, built from cutting-edge technologies and the right organisational structure, could identify the next pathogen, currently unknown, before it develops into a possible pandemic.
Murat Seitnepesov (Chairman, Caspian Week, Switzerland) pointed out that today's knowledge about COVID-19 and other potential epidemics or pandemics is very fragmented. The GSPDX project, announced on March 18, 2021, aims to collect and consolidate the world’s fragmented knowledge. It will definitely contribute to the World Health Organization (WHO) initiative to create a Hub for Pandemic and Epidemic Intelligence together with the German government. On 4 June, a patent application for the method was filed with the Swiss and European Patent Offices.
He presented the project in detail, in four stages. The first is to collect data on known pathogens, whether viruses or bacteria. The databases we looked at were very narrow and not enough for a machine learning algorithm to work with, so the second stage needs real data sets from clinics: parameters, symptoms and diagnoses. The algorithm will then learn from those real data sets. The third stage is a pilot project. Subject to agreement with the relevant authorities, the plan is to install sensors and analysers at airports to check passengers’ temperature, and to analyse air and sewage water continuously in airports, including toilets, boarding gates, security gates and entrances and exits. This equipment will be connected to the main database, and the algorithm will already know which parameters and symptoms correspond to each pathogen. At that point the system will be ready to detect known pathogens, like COVID-19. The fourth stage is detecting unknown pathogens. If the algorithm finds an unusual combination of parameters and symptoms, it will flag an unknown pathogen and alert the relevant authorities, who can then analyse it and try to work out what it was.
Manuel Carballo (Executive Director, ICMHD, Switzerland) weighed up the pros and cons of WHO’s involvement. On the plus side, all countries are WHO members, and WHO has the official capacity to issue recommendations and organise international databases. On the downside, WHO can say things that countries are not necessarily expected to follow; official health statistics vary in quantity, quality and accessibility; and the validity of data always reflects how far a country has been able to gather it.
Looking for combinations of symptom data opens up a whole new area of research, which will depend on the capacity of general practice. Mathematical algorithms are highly scientific and more credible today than any other source of information. Whether such pathogens emerge, and whether they become epidemic or pandemic, will depend on a range of social and environmental factors. Environment is a particular concern. Climate change will be a critical factor in where new pathogens come from and how existing ones spread. Urban slums in developing countries provide the most favourable conditions for new pathogens to emerge or spread.
Ernesto Kahan (Scientific Director, Galilea Institute, Israel) looked at the political and philosophical implications of this academic exercise. Serious epidemics and pandemics have a major medical, social and economic impact on all societies. Two clear examples are the Plague in the Middle Ages and the Spanish Flu in the middle of the First World War. Societies need to prepare for new pandemics, because today they are not prepared. A couple of days ago, a new avian flu was discovered in China, and it may be even more aggressive than coronavirus. According to Professor Kahan, the project is not easy to implement. It has to start in small countries.