Avert successive waves of Covid

Mutation of virus = function (immune system encountered by it).  If we collect data of all Covid infections and filter out human the immune systems that have definitely caused mutations and also the immune systems that have in high probability caused mutations, we have a subset class of immune systems of interest. If we apply the suitable Machine Learning Algorithm to this data, we can predict the next what type of human immune system if the virus encounters, will result in a new mutation that is more transmissible as well as deadly.

Once the immune system that might cause the next dangerous mutation can be predicted, they can be vaccinated in advance and made resistant to the existing strains of the virus. This ensures that further mutations of the virus will adapt to the human system instead of fighting with it, thus bringing an end to the pandemic sooner.

The direction in which a virus mutates depends on the immune system of the person it encounters.

Mutation is a game being played by the virus to adapt itself to the world to thrive and reproduce.

The ultimate aim of the virus is to propagate from one person to another in the shortest time possible. Thus, when the virus encounters an average human immune system, it strives to either adapt to the immune system and become less deadly or be more transmissible in order to jump to the next host in the fastest time possibe.

When the virus encounters special immune systems, i.e immune systems that do not represent the average of the normal population (immunocomromised, with diseases etc.), the virus invading the system thinks that all human immune systems are similar. It tries to adapt to the new immune system. But, the average human immune system is different from what this virus has prepared itself for. As a result, when the virus escapes from this aberrated immune system and infects another normal healthy human, it becomes more transmissible and deadly to the healthy human (as opposed to its original intention).

Mutation of virus = function (immune system encountered by it).  If we collect data of all Covid infections and filter out human the immune systems that have definitely caused mutations and also the immune systems that have in high probability caused mutations, we have a subset class of immune systems of interest. If we apply the suitable Machine Learning Algorithm to this data, we can predict the next what type of human immune system if the virus encounters, will result in a new mutation that is more transmissible as well as deadly.

Once the immune system that might cause the next dangerous mutation can be predicted, they can be vaccinated in advance and made resistant to the existing strains of the virus. This ensures that further mutations of the virus will adapt to the human system instead of fighting with it, thus bringing an end to the pandemic sooner.

Low wage developing and underdeveloped countries with shortage of vaccines.

More and more Covid mutants is a headache for governments, people and the economy. This solution seeks to prevent mutants from arising and thus bring this pandemic to an end. The world can open up again without fear of disease.

I am a one member team. I am a foreign student with other daya to day workloads, so couldn't get beyond conception phase.

Furthermore, if experts give a green light, it makes sense to go for the prototype.

It is an out-of-the-box solution that combines analytics with game theory of viruses.

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