Why is it hard to conduct health optimization?

A. There are too many life factors

Difficulties in conducting health optimization are reflected in cancer. Cancer can be caused or aggravated by thousands of life factors. Some cancer instances might be primarily caused by cancer-inducing substances (there are thousands); some by exposure to waves and rays; some by exposure to heavy metals; some by excessive stress; some by bad habits or way of working; some by viruses and bacteria, etc. Each person might have been exposed to and is continuously being exposed to the same cancer-promoting substances, matter or mental factors. Let say, each person might be exposed to first 20 bad things, how can the person know what are they? It is impossible to find them. Now, most people might try everything he could think about. If a person is under a continuous exposure to a matrix of cancer-promoting substances and factors, none of the medical treatments can cure cancer. The tumor can be removed by an operation, but cancer in terms of the driving force is still there. It will come back in different locations, in different forms and in different times. Some cancer causes can be very non-obvious. For example, one's diet might be so unique that the diet promotes certain distinctive microorganisms which can release cancer-causing toxins. If this person can change his diet to one that does not help those cancer-promoting microorganisms, he would be in a far better position for self-resolving.

B. Drugs cannot help much

Medical researches have found thousands of things or substances that can cause or promote cancer, but this also poses a big challenge: how to use those findings? No way. All medical studies are based on the binary scale, what can cause cancer and what will not. In reality, such findings have little utilities. Each person lives among a massive number of cancer inducing substances. Due to flaws in medicine, it looks like none of them can cause one specific cancer. By using the binary approach, one would find that every cancer cannot be caused by any of the those cancer-inducing substances due to small concentrations. That is why we must use a holistic quantitative approach. We must focus on everything. It is like adding thousands of "little bits" to achieve a predictable cure.

C. All factors work in a quantitative scale

Even though we reject the binary scale, we need to use some threshold for determining the effects of each cancer causing substance solely for convenience. This poses considerable challenge. How do we know if one of those heavy metals or thousands harmful compounds are too much for a person and how to avoid them. It does need to make a quantitative determination for all potential factors in a relative scale. The yes-and-no conclusions from most medical studies do not help very much. Medicine researches have found thousands of yes-or-no conclusions, but very few of them can be applied to John Doe. We must point out that findings from clinical trials reflect some means (even though it is a mathematically wrong mean due to life phenomena), it is obvious that even through factors that are found to be bad or have no beneficial effects, may have actual benefits on certain people. This is because those factors with their means on the negative side, but can deliver positive effects on the passive side. In other words, they might have beneficial effects on some patients due to their unique circumstances even though the findings from clinical trials imply they are bad. One of such factors is copper. In most people, the amount of copper is enough. Intake of this heavy metal may cause all kinds of health problems. However, in some individuals, it may be in severe deficiency so that the energy production mechanism is impaired. Based on our studies in human immune functional dynamics, a lot of factors can affect tissue ecosystem, organ vital functional capacities, the CNS, and the immune system. Their overall benefits would depend on how they affect each of those properties on a long term basis.

D. Complication caused by personal differences

Since each person is distinctive in genes, growth environment and mental state, we must reject the idea of using population data to specific persons. However, population data is instructive. We note that most health properties can vary in a scale from 1% to 100%. A cure for Jack might be half a killer for John. Let say, that Jack Doe has vitamin A and Zinc deficiency and found a diet working well for him. Now, John Doe does not have vitamin A and Zinc deficiency. If he consume more food containing higher vitamin A and Zinc per Jack's success, he might make his own health worse. If we look at lifestyle, personal activities, living and working habits, we should see there are no two identical persons. Imitation does not always work.

E. Fixes are even harder

Assuming that John Doe found that he has very high compound X. So, he wants to avoid it. Now, he must examine how life histories and daily routine to see why he might have gotten it. It may come from the air he normally breathes, the food he eats, and utensils he uses, the place he works. There are thousands of possibilities. Even if he can find each of his activities, working places, and things he might contact, he still needs some background data for analysis. After he has found all exposed things and materials, he will need to determine the amount of the compound X. He will need basic data, a computing system, and computer algorithms for estimating its daily, monthly or yearly intake from all suspected sources. This may be they medicine avoid to address causes because they are too complex for a doctor. This kind of problem must be addressed in a unique way.

F. What do we really need?

Based on the above example, we note that idea health optimization would need massive databases containing details about all toxic substances, all microbe's effects, all location information, all environment parameters, plus the basic methodology for optimization. We also need a big computing capability to determine any aspect of health issue. Ideally, a centralized algorithm might be programmed to do the following functions: after a person enters his data to the system, it will estimate all cancer causing substances and the total amounts, flag all potential health issues for further analysis. After the large scale search is over, focus will be on specific substances, specific viruses or microbe, or specific activities or habits.... This is currently a mission impossible, but we must do it now. That is why personalized medicine cannot be put in practice because the required database, computing capability and skills are so high that no doctor office or hospital can provide required infrastructure. The database might contain nearly everything that can affect health or related to known diseases. If one enters the model number of a microwave, the person should see information about its risk and known pollutants. If one types in a pan's model, he should be able to tell if the pan might contain high level of lead from the production process. Of course, elementary data must be built by all people so that it can be used and reused by all people.

G. Costs

For deploying a central database with massive data, the initial cost is prohibitory. However, the cost for managing chronic diseases are also prohibitory. When cancer, pandemic and chronic diseases are about to strike all human beings, there are no other way to contain future diseases. If each algorithm is developed to benefit billions of people, then the costs for developing the algorithm are probably very low. I have long ago proposed a multiple state project for controlling cancer. But none of the states pay attention or see the urgent need for building the infrastructure.

It took years to build the infrastructure. More details will be provided in update.