HOW TO MEASURE CORONAVIRUS MUTATION USING DATA MODELLING TECHNIQUES

Written by Thomas Mutsimba, an author, an Enterprise Risk Management Professional endowed with advanced actuarial analysis and advanced forensic analysis©

The Coronavirus, dubbed “COVID-19” by Health researchers, medical laboratories and medical specialists has wreaked havoc as it has mutated a great deal killing a great number of people. What is challenging to the world is because there has not been sufficient research concerning this scourge. Data and related analysis have been based on few accumulated fundamentals that have insufficiently provided the markets worldwide with sufficient information. I have watched since an announcement was made on media platforms concerning this scourge, the coronavirus.

The revelation coming to me as I watched how the national governments of the world grapple with communicating the right and valid information concerning the velocity of mutation of the coronavirus. It is a nutty issue. Enterprising to me is my gift of advanced actuarial analysis and advanced forensic analysis calling me to showcase the knowledge embedded in this gift.

The coronavirus mutates and or develops from unknown realms as on this planet our judgment cannot find a cure for it. A need arises from an enterprise risk management perspective, wholesomely to configure and set nations for orderly amassing, recording, evaluation and analysis, monitoring and reporting of coronavirus research and experiment data to ensure the right, valid and accurate information is communicated to the economies at a rate of stage of development index.

Data modelling techniques are required, in fact there is deficient data management regarding the coronavirus mutation. This article seeks to cover risk dimension diametric concerning the mutation of the coronavirus in this world in the current status quo of things. I will expound data modelling covering the mutation of the so-called coronavirus. First of all, mutation of infectious diseases requires organized and orderly management of research data and or diagnosis that must outpace the stage of development of the diseases. Because some economies in Africa are already grappling with funding needed to monitor, research and deploy treatment of infectious diseases such as this one. This cannot happen without proper data management.

Coronavirus is not spared either. There are ten measurement bases which can be used, embedded in data modelling to deal with the corona virus mutation. Data modelling is the use of characteristic pattern to tenure or time when, how, where and for whom certain patterns posture themselves. Hence in this advent of “COVID-19” data modelling seeks to compartmentalize the disease stage of mutation and or development and establish the record management of disease to aid national governments Health departments in resource allocation and management. Hence the ten measurement bases are:

[1] Origination data.

[2] Mutation analytics using sensory motion.

[3] Risk diametric stage of development indicators .

[4] Generation classification indices.

[5]Analytics algorithm development.

[6] Disease mutation scientific indicators.

[7] Generic mutation indexing development.

[8] Disease categorical structures of data blocks interaction.

[9] Tenure of disease data block chain.

[10] Monitoring and reporting structures.

Now we will unpack the measurement bases listed above using data modelling techniques to track coronavirus mutation.

1. Origination Data

Origination data is a set of bits of pieces of inception patterns of the corona virus. This origination data must be known in terms of the actual year and or location where the corona virus was first detected. As it stands right now the data is limited. Why is it limited? It is because the disease emanates from unknown realms. The origination data is crucial for the following five reasons:

• Setting the measurement mutation foundation base mathematically notated to show the variant standard deviation of stage of mutation of disease characteristic patterns.
• Gives impetus to mutation categorization and or classes of characteristics for analysis,
• Origination data is important because it shows the origination hot spots where targeted focus may be set on. Hot spots are crucial for studying mutation of diseases. This is because hot spots show where coronavirus originated from. The characteristics of hotspots are crucial for building disease origination mutation factors.
• Origination data builds disease knowledge database for future reference when establishing trends for disease mutation.
• Disease mutation does not operate or cannot be effectively studied without proper data, let alone origination data.

Mutation Analytics using Sensory motion

Data relating to coronavirus mutation must be subject to what is known as mutation analytics using sensory motion. Diseases are not stagnant but instead due to their genetic corrosive action of either bacteria parasites or minute active parasites that populate under specific conditions or conditions that are promoted by more dominating disease conditions dominating agents. Mutation analytics are used by sensory motion. What is “sensory motion”? Sensory motion is the stage of development reengagement from one level to another. The reengagement being referred to is the bio-chemical reactive mutation of disease parasitic behavior that stand at a rate of development risk factor indexing.

How do you design the disease risk factor development index? To demonstrate this in the context of the coronavirus, I will use advanced actuarial data analysis that employs some advanced forensic analysis. To begin the illustration, we need to take note of the following scientifically bio-chemically notated conditions and or assumptions:

[1] Coronavirus research is limited

[2] The risk factors have to be identified by regional or location characteristics [disease-corona virus] mutation. Since these risk factors are not cast in stone but are notated using bio-chemical reactive analysis of environmental conditions that posture the mutation analytics behavioral patterns, it stands as a notation key.

[3] Genetic mutation of diseases is not a stand-alone consideration? Why is that so? It is so because controlled and uncontrolled conditions bio-scientifically posture mutation lead factors and lag factors. The lead factors are positive transfiguration tenets while the lag factors recede the ability of the disease to gravitate towards the origination environment where origination data was amassed.

[4] Coronavirus dubbed COVID-19 is a new trendsetter in killing factors. What is a killing factor? A killing factor is a factor that increases the probability of terminating life. How can that be measured or at least use risk analytics modelling to project life termination point?

[5] The center of focus of a disease. What is a center of focus? Every disease has a center of focus. It refers to the human nucleic center. The human nucleic center is the nervous system functional tenacity. How can the center of focus be determined? Research techniques are critical as the disease mutates at a rate, sometimes that cannot be detected early enough.

[6] Gravitationally, a disease like “COVID-19” hugely understood as a bad flu requires real time advanced research techniques. Health centers and or medical laboratories have to act as providers of real-time powerful health business intelligence.

[7] Technology synchronous component. Here we are not talking about business intelligence, but disease database designing must be synchronous. Algorithms written to proffer sensory motion of disease mutation must afford nations and or governments with simultaneous enablement of enactment of technology law and data sets that render mutation interrelationships of minute parasites as the jargonated medium of transmission and transfiguration.

[8] Consider profiling assumption and or risk factor-based indexing methods. These can be tested at a rate of mutation nucleic loss indices. What is a nucleic loss index? This refers to microscopic laboratory recording of test samples harboring coronavirus nucleic mutation centrage. This and its existence will be indicative of the behavioral virus. Actuarial extrapolation techniques may be used.

Example

Considering South Africa has recorded approximately a range of 2 to 4 cases of coronavirus. Topographical analysis of the regional location of the patients infected by the virus is key. Let’s say in ten provinces there is an average infection of 3 to 4 persons in each of the provinces.

To design data models for coronavirus mutation, the following can be considered:

[1] Stage of development tenet.

[2] Stage of development compartmentalization indexing.

[3] Mutation indexing focusing on tenacity index of coronavirus nucleic mutation.

[4] Gentric phased actuarial phasing of mutation characteristics.

[5] Scorecard using risk rating metrics.

[6] Budgetary resource ranking for Health actuarial funding reserve.

[7] National Statement of accounts for actuarial reserving associated with COVID-19 funding related reserving.

[8] Stage of completion of treatment reserving.

[9] National monitoring and reporting of infectious disease data analytics results.

[10] Risk response mechanisms for coronavirus or infectious diseases in economies [for instance developed and developing economies]

[1.1] Stage of Development

We will illustrate the simple example. Economies must look at the stage of development of the coronavirus and or other infectious diseases This is done using actuarial data amassment. What is this actuarial data in the health context? This refers to the characteristics of the coronavirus that are indicative of the stage of development. These characteristics according to our example are identified in each of the provinces of South Africa. As we have said there can be an average of 3 to 4 infections in each province over a certain tenure. Those characteristics that are indicative of the stage of development are postured to notated characteristic statements linked to the categorized stages of development. Bio-chemical reactive analysis done in samples taken into laboratories for testing will attest the characteristics recorded over a period of time. However, this actuarial data amassment is critical. The use of mathematical notation may be embedded into systems designed to record, store and monitor the mutation motion of disease stage of development characteristics.

However, with the current status quo in economies of the world investment in such is hardly organized infectious disease management and is a no feature. But we also note that inadequate advanced data management and monitoring to be specific gives impetus to the lack of trust by masses in public health insurance and management systems. Why is that so? It is so because resources are not linked to organized and informed decision making. Politics of leaders always wreak an ill-equipped platform for coronavirus mutation management.

[2.1] The Stage of Development compartmentalization indexing

Again, the fact that we are now talking about the coronavirus and or other infectious diseases  stage of development compartmentalization is a testament to much needed employment of actuarial input fundamental techniques. What are we talking about here? We are talking about identification of key disease [coronavirus or other injection disease] actuarial data. There is a certain need to compartmentalize the stage of development of a disease such as coronavirus of that nature. It is not worth to wholesomely look at the stage or just look at face value, but compartmentalization may focus on the following questions to measure and analyze as linked to stage of development:

• Compartment portion of the disease that populates the entire stage of development. In terms of coronavirus, it could be the type of food eaten, the hygiene standards where the food originated from, virus nucleic contamination rate, generic parasitic behavior patterns, factors that are unknown which the health professions can’t decipher.

• The stage of development entire population mechanism.

• The stage of development motion mechanism. The disease mutation motion mechanics is different from the population mechanism. The former refers to the parasitic bio-chemical reactive mutation as microscopic laboratories sensory view detects. The latter refers to the disease topographical location at or in a stage of development. These variables must be known and developed. Statements by health officials must not be political but they are given credence by such organization of stage of development compartmentalization techniques.

• Compartmentalization measurement techniques. What are these? These refer to the quotient dynamics factored by the most critically ranked factorial lead indicators of the emerging quotient. As a virus moves from one stage of development compartment to another, lead indicators evolve, and they change depending on a number of factors. Factors postured here are italically degenerated at velocity of mutation requiring sensory motion detection techniques powered by fast paced data banks of recording motions.

• Stage of development is based on a technique called stage dentures lacerated frontiers. What is this? It means every virus at each compartment in the stage of mutation depicts dentures lacerated frontiers. These frontiers posture how extravenous, reactive decapitating atoms of treatment cause mutation to fail. But it does not mean mutation fails; what fails is the failure of the virus nucleic center to keep producing perversion antigens. This coronavirus is also susceptible to stage denture lacerated frontiers. These lacerated frontiers are formed by four virus compounds that are interlinked by and through environmental conditions formation methodology.

• Stage of development nurtured at virus loading capacity indexing venerated for data origination skewness. What is this? Virus loading capacity indexing is the averaging of statistically notated characteristics of virus formation from one stage of development compartment to another compartment. Coronavirus disease data must be amassed at the loading capacity index. Standard deviation factorization against the origination data compartment mean is analyzed using actuarial statistical techniques. These scientific biological chemo analysis methodologies must be employed for analysis at stage of development compartments. Compartments against stage of development drill down to the basics and or fundamental inputs that give impetus or affect the mutation dynamics.

• Danger risk as a specific risk. This is a specific risk that should be reassessed at each compartment of the stage of development of the disease. The risk assessment should focus on risk factors; these are the compartment higher probability risk trigger events posing greatest danger risk.

[3.1] Mutation Indexing focusing on Tenacity Indexing of Coronavirus Mutation

Mutation indicing is the degenerate disease transformative indicators at a much-detailed level of measurement. But this indicing is propped up by digital data analytics using algorithms written specifically for Health insurance methodologies. Mutation indicing focusing on Tenacity indicing of coronavirus mutation is an advanced medical laboratory knowledge base. It works on the following manner that can also be used:

• Mutation indexing identifies three tri-partial components of the coronavirus mutation. These components are recorded at component exponential factor. The component exponential factor is a quantum disease risk posture that is based on microscopic medical actor that acts with bodily fluids interacting with the virus. How is this possible? Medical laboratories test for virus actors. These virus actors are the ones that will drive mutation antio-pathogens acting to exponentially multiply the factors to be used in the indexing. This is advanced medical laboratories statistical analysis that can be used conjoined with advanced actuarial analysis embedded in data modelling techniques.

• One of the tri-partial components venerates the pyramidal hierarchical elevation technique. This is a data analytic technique that focuses disease elevation danger based on mutation trends. Coronavirus is not spared; in other words, it is covered by this component. Virus of the corona nature is still new, at least regarded as a new virus. There could be an opportunity there to utilize it to develop data modelling monitoring techniques of elevation by mutation. Medical Health schemes and Risk data scientists must be able to employ some of these techniques acoustically as planning price and or fee modelling of medical aid contributions, employing these methodologies in a medical scheme benefit modelling and provide the tri-partial component for disease impact on medical schemes profiling of product development initiatives. One wonders how this is being done today.

• The third tri-partial component is indice notation and how the populative wholesome indice is eventually computed. Notation labelling is based on viral characteristic behavior pattern induced as a component to form the mutation indicing. Several techniques and methodologies may be used. Indicing is based on minute component that can be recapitulated as mutation environments evolve over a long period of time. Nudging to me is the mathematical probability modelling . This is the probabilistic tenet of mutation. National governments should be able to employ this critical component to forecast disease mutation capabilities. It is a definite issue that national governments lack such innovative datum banks for coronavirus mutation management. This may not be coronavirus only but other infectious diseases . Where are we as nations, concerning this?

[4.1] Gentric Phased Actuarial Phasing of Mutation Characteristics

What is this Gentric Phased Actuarial phasing of mutation characteristics? This sounds complicated and jargon laden. But this refers to the asymptomatic employment of data modelling actuarial techniques of phasing mutation characteristics posturing survival behavioral tendencies of a killer disease. Data would have been amassed at a rate of notated disease [coronavirus in this case] characteristics phasing. Phasing being referred to is actuarial data phasing. Phasing involves withdrawal of component measurement basis from a bank of characteristics using actuarial data modelling. But how does it happen?

First it makes use of equilibrium and disequilibrium analysis dynamics. The bank of coronavirus characteristics has positive and negative contributory antio-pathogens. What are antio-pathogens? These are actors in viral load tenacity indice in each of the positive and negative characteristics. To ensure that this works best, equilibrium refers to the match equality between positive and negative balance bank characteristics while a disequilibrium can go either way where positive contributory antio-pathogens are greater than negative contributory antio-pathogens and vice-versa. However, a definition for coronavirus must be made to determine what it effectively means.

Data formulation of the coronavirus study: What is it under this tenet. It refers to how you make decisions for coronavirus treatment decisions. But where does it come from? It comes from a variety of sources concerning the aggregated stage of development of the disease.

[5.1] Scorecard using Risk rating metrics

Results of coronavirus risk assessments whether done at stage of development level or compartment level within the stage of development level requires recording, computation and evaluation or analysis. All of these processes of coronavirus effective nature are bound by recording . Recording may be done on designated scorecards using metrics identified from the coronavirus and other infectious diseases. Because a scorecard is widely used in other fields, at this phase of development it is nurtured at a bio-medical understanding of the effectual nature of the coronavirus.

[6.1] Budgetary Resource Ranking for Health Actuarial Funding Reserve

The virus, coronavirus dubbed COVID-19 is here and it is mutating asymptomatically. Funding can be an issue for National governments and that may boggle their minds. But why is budgetary resource ranking for Actuarial funding, a reserve measurement base? It is a measurement base because the health insurance and investment bill require mutation stage of development allocation. The National governments must look at how the virus funding is determined .

More so it is not just about the funding, but it is also about budgetary resource ranking to posture funding votes. Posturing funding votes in National governments is not just about supporting funding release but it is about the actuarial reserving of such funds. In most cases National governments set up actuarial reserving through consulting actuaries’ prescriptive direction.

It is crucial to reserve funding actuarially, at degenerate input fundamentals deceleration and acceleration. Determining the velocity of approach of the coronavirus requires acceleration of the virus treatment funding using acceleration techniques in the coronavirus data models deciphered as new and continuous flows of data are experienced. The deceleration also of the virus resource driven input fundamentals will ensure that mutation is managed using resource bound modelling techniques.

[7.1] National Statement of Accounts for Actuaries Reserving associated with COVID-19 Funding related reserving

Nations, as they grapple with the scourge of the coronavirus also almost simultaneously are concerned with the impact of COVID-19 funding related reserving on National Statement of Accounts. I pose two questions as follows:

• Why is budgetary resource ranking critical for Health Institutions?
• How is the budgetary resource ranking linked to coronavirus funding-related reserving?

Budgetary resource ranking is critical for the stage of development of the coronavirus, mutation to be specific. Using data metrics of the disease impacts and effects, resources which may be needed in financial form may be ranked. National governments: if truth be told must rank budgetary resources for allocation using actuarial techniques that stand to venerate the criticality of the stage of development of the coronavirus. Mutation supported by such quantum driven analyses stand to be tackled together. Budgetary resource ranking stands to be linked to the coronavirus reserving. How? It does so through identified data actuarial input deceleration and acceleration that we spoke about. The health care and health departments must improve on modelling of approaches to mutation of coronavirus or other infectious diseases.

[8.1] Stage of Completion of Treatment reserving

The stage of completion of Treatment reserving refers to the mutation fundamental treatment resource allocation. It is reserving actuarially for that matter, that is done at the quest to complete treatment. Data is amassed at a rate that actualize compartmental data amassment of

 the disease origination data to the stage of completion. Treatment reserving is a specialized amassing of resources that are deployed to the field using actuarial reserving techniques. The technicalities of stage of completion of Treatment reserving are:

[8.1.1] Life cycle of disease [coronavirus] mutation.

[8.1.2] National Health department tenders’ specificity.

[8.1.3] Risk indicators conclusive assessment.

[8.1.4] Treatment acupuncture methodologies.

[8.1.5] Treatment progress measurement tools.

[8.1.6] Economic impact assessment tools.

[8.1.7] The relegation of disease adverse effects to non-critical zones.

[8.1.8] Coronavirus or other infectious diseases stature.

[8.1.9] New rehabilitation measures of societies in other words post treatments measures.

[9.1] National Monitoring and Reporting of infectious diseases

This is a measurement base in its own right that focuses on monitoring and reporting of infectious diseases. Degeneration of a disease can happen at a fast-paced environment. This activity is generically important in the process of managing mutation using data modelling techniques. It is a fast-paced populated mechanism. Monitoring and evaluation of mutation of national monitoring and reporting of infectious diseases. This phase comprises of continuous amassing of data mutation data as specific points. These are disease mutation compartments that are of a remnant nature that come after the official initially diagnosed characteristic patterns.

[10.1] Risk Response Mechanisms for Coronavirus or Infectious diseases in economies  

After everything is said and done, National governments and or Health care boards, Authorities should have a raft of risk response measures for mutation technicalities and or threats identified that may already be wreaking havoc. Risk response mechanisms for coronavirus and other infectious diseases are of a various nature. They are not cast in stone, but the most important issue is for anyone to know how to get there. Mutation equilibrium and disequilibrium analysis dynamics will point to a raft of measures. Risk events and factor analyses that are dominating the mutation compartments will probably give impetus to the tenure of the disease on mutation diametric sensitivity path. Nurturing the mutation path on diametric dimension.

There is a lot I could cover on this article, but it is imperative I cover piecemeal nuggets that expose locations in the mutation of the coronavirus that can be exploited to deal with it once and for all.

For this revelation comes to me in unimaginable proportions espousing advanced actuarial analysis and advanced forensic analysis . In my next issue I will contribute to deal with the measurement bases for coronavirus mutation.

Disclaimer: All views expressed in this article are my own and do not represent the opinion of an entity whatsoever, with which I have been, am now, or will be affiliated with. ©