16.06.2021
Preparing for a New Pandemic: Global System for Preparedness for Disease X
Русский текст – по этой ссылке
On June 8, 2021 HORASIS: the Global Visions Community had its annual Global Meeting, co-chaired by Murat Seitnepesov, Chairman of Caspian Week. Given the COVID-19 pandemic, the event was held as virtual meeting.
One of the most thought-provoking topics of this event 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: Is it possible to create a global system comprised of cutting-edge technologies and the right organizational structure to 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 was very fragmented. A project to accumulate and consolidate all the fragmented knowledge available in the world, the GSPDX, was announced on March 18, 2021. It will definitely contribute to the initiative by the World Health Organization (WHO) to create a Hub for Pandemic and Epidemic Intelligence together with the German government. On 4 June a patent application for the method with the Swiss and European Patent offices was filed.
He presented the project in much detail. There are several stages of that plan. The first stage is to collect data about known existing pathogens, be it viruses or bacteria. We already faced the problem that all databases which we saw were very narrow, and they are not enough for the machine learning algorithm to proceed. At second stage, we will need real data sets from clinics, parameters and symptoms, and what was the diagnosis. Then the machine learning algorithm will deal with real data sets, and learning algorithms will teach themselves. The third stage will be the practical implementation, also called a pilot project. Subject to an agreement with the relevant authorities, we are going to implement sensors and analyzers at the airport, which will analyze temperature of the passengers, and then we are going to constant analysis of the air and sewage water in the airports and the toilets, also in the boarding gates, on the security gates, on the entrance and exit. This equipment will be connected to the main database, and the machine learning algorithm will already know which parameters and symptoms correspond to each pathogen. Here we will be ready to detect already known pathogens, like COVID-19. The fourth stage is how to detect unknown pathogens. If the algorithm finds some unusual combination of parameters and symptoms, it is an unknown pathogen, and this system will alert the relevant authorities. They could do the subsequent analysis and try to understand what the pathogen was.
Manuel Carballo (Executive Director, ICMHD, Switzerland) indicated pros and cons of WHO's involvement in the project. The positive factors are: 1) all countries are WHO members; 2) it has the official capacity to issue recommendations and to organize international databases. The negative aspects are: 1) WHO can say things countries are not necessarily expected to follow, 2) official health statistics are variable in quantity, quality and accessibility, 3) validity of data will always reflect the extent to which a country has been able to gather the data.
The idea to look for a combination of symptomatic data opens up a whole new area of research, which will depend on the capacity of general practice. Mathematical algorithms are highly scientific, and they are more credible today than any other source of information. The fact that pathogens may exist, to what extent will they become epidemic or pandemic, is going to depend on a variety of social and environmental factors. One of the issues of particular concern is environment. Climate change is going to be a critical factor in the issue of the origin of new pathogens, or the spread of existing pathogens. Urban slums in developing countries constitute the most optimal conditions for the emergence of new pathogens or the spread of existing pathogens.
Ernesto Kahan (Scientific Director, Galilea Institute, Israel) presented some aspects related to the political and philosophical implementation of consequences of this academic exercise. The appearance of serious epidemics and pandemics produce a significant medical, social and economic impact in all societies. The two characteristic examples are the Plague in Middle Ages and the Spanish Flu in the middle of the First World War. It is important for the society to be prepared for new pandemics, because today it is not prepared. A couple of days ago the new aviary flu was discovered in China, and it may be even more aggressive than coronavirus. According to Professor Kahan, It is not easy to implement this project. It has to be started in small countries.
On June 8, 2021 HORASIS: the Global Visions Community had its annual Global Meeting, co-chaired by Murat Seitnepesov, Chairman of Caspian Week. Given the COVID-19 pandemic, the event was held as virtual meeting.
One of the most thought-provoking topics of this event 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: Is it possible to create a global system comprised of cutting-edge technologies and the right organizational structure to 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 was very fragmented. A project to accumulate and consolidate all the fragmented knowledge available in the world, the GSPDX, was announced on March 18, 2021. It will definitely contribute to the initiative by the World Health Organization (WHO) to create a Hub for Pandemic and Epidemic Intelligence together with the German government. On 4 June a patent application for the method with the Swiss and European Patent offices was filed.
He presented the project in much detail. There are several stages of that plan. The first stage is to collect data about known existing pathogens, be it viruses or bacteria. We already faced the problem that all databases which we saw were very narrow, and they are not enough for the machine learning algorithm to proceed. At second stage, we will need real data sets from clinics, parameters and symptoms, and what was the diagnosis. Then the machine learning algorithm will deal with real data sets, and learning algorithms will teach themselves. The third stage will be the practical implementation, also called a pilot project. Subject to an agreement with the relevant authorities, we are going to implement sensors and analyzers at the airport, which will analyze temperature of the passengers, and then we are going to constant analysis of the air and sewage water in the airports and the toilets, also in the boarding gates, on the security gates, on the entrance and exit. This equipment will be connected to the main database, and the machine learning algorithm will already know which parameters and symptoms correspond to each pathogen. Here we will be ready to detect already known pathogens, like COVID-19. The fourth stage is how to detect unknown pathogens. If the algorithm finds some unusual combination of parameters and symptoms, it is an unknown pathogen, and this system will alert the relevant authorities. They could do the subsequent analysis and try to understand what the pathogen was.
Manuel Carballo (Executive Director, ICMHD, Switzerland) indicated pros and cons of WHO's involvement in the project. The positive factors are: 1) all countries are WHO members; 2) it has the official capacity to issue recommendations and to organize international databases. The negative aspects are: 1) WHO can say things countries are not necessarily expected to follow, 2) official health statistics are variable in quantity, quality and accessibility, 3) validity of data will always reflect the extent to which a country has been able to gather the data.
The idea to look for a combination of symptomatic data opens up a whole new area of research, which will depend on the capacity of general practice. Mathematical algorithms are highly scientific, and they are more credible today than any other source of information. The fact that pathogens may exist, to what extent will they become epidemic or pandemic, is going to depend on a variety of social and environmental factors. One of the issues of particular concern is environment. Climate change is going to be a critical factor in the issue of the origin of new pathogens, or the spread of existing pathogens. Urban slums in developing countries constitute the most optimal conditions for the emergence of new pathogens or the spread of existing pathogens.
Ernesto Kahan (Scientific Director, Galilea Institute, Israel) presented some aspects related to the political and philosophical implementation of consequences of this academic exercise. The appearance of serious epidemics and pandemics produce a significant medical, social and economic impact in all societies. The two characteristic examples are the Plague in Middle Ages and the Spanish Flu in the middle of the First World War. It is important for the society to be prepared for new pandemics, because today it is not prepared. A couple of days ago the new aviary flu was discovered in China, and it may be even more aggressive than coronavirus. According to Professor Kahan, It is not easy to implement this project. It has to be started in small countries.
Best regards,
Caspian Week Team
Caspian Week Team