Epidemiological Forensic Investigation Methodology Statement
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The entire 25-page document Top-Down Investigation, Bottom-Up Quantification – Epidemiological Forensic Investigation Methodology Statement will be open to the world likely by December 15, 2024.
The one-page Concluding Remarks from the statement below republished have slight corrections (4 words added) from the original that was sent to Dr. Joseph Ladapo, Governor Ron DeSantis, Attorney General Ashley Moody, and Robert F. Kennedy, Jr..
Acronyms and other items described earlier in the document will be in square brackets in this republication.
VII. Concluding Remarks
Epidemiology seems to rely almost exclusively on EBM [Evidence-Based Medicine] for methodology and ISM [Inferential Statistical Methods] for modeling. Epidemiologists, including many doctors who take a class in epidemiology, self-describe as “scientists.”
ISM modeling and EBM methods they call “science” are not symbiotic with real world project planning and real time project execution to achieve successful disease investigation and quantification.
“Public health” requires strategic plans for disease response and vigilance. TInBUQ is a project planning methodology for public health response and vigilance. TInBUQ utilizes far more modeling techniques than ISM.
If the objective is to determine causality and quantify those affected by the cause, then EBM and ISM fall short of that mark. Poor methodology and modeling are the likely reasons that the vaccine debate lingers after decades of research and publication.
TInBUQ can solve that debate in a week.
One example of incorrect modeling and methodology is the use of randomized controlled trials (RCT) and peer reviewed research papers to determine everything. If all you have is a hammer, everything looks like a nail.
For example, hubris was on display in the use of RCT and peer review to determine mask effectiveness. Before RCT and trials with dozens of confounding variables, someone should ask an engineer.
The question is easily answered by engineers who develop the specifications for masks, design the masks, develop the manufacturing process for the masks, and develop the quality assurance test fixtures for the masks.
Doctors might read the spec on the box. Ask a surgeon the tensile strength of his new scalpel.
The TInBUQ methodology laid out herein was prototyped via the work on Massachusetts, Minnesota, and Connecticut death records databases. Unique insights and findings no one else in the world found are in publications from Summa Logica LLC.
Research papers into Covid-19 and vaccine issues have been one (1) to two (2) years behind the results provided by the TInBUQ methodology.
The TInBUQ methodology produced new visualizations of anomalies likely caused by serious adverse externalities. For example, Time-Window Shifting, Prevalence-of-Cause, and Simpson’s paradoxes found anomalies that no other researcher in the world found.
TInBUQ found massive numbers of excess Acute Renal Failure involved deaths back in the middle of 2022. TInBUQ also showed back in mid-2022 that lymph node cancer and bone marrow cancer were excessive and climbing.
Lymph node cancer in Massachusetts was 400% of normal in 2023.
TInBUQ also showed in mid-2022 that in Massachusetts greater excess deaths in 2020 involved respiratory ICD-10 codes, while greater excess deaths involving clotting and bleeding occurred in 2021.
Again, a disease does not change how it kills on a year boundary. Societal profile of causes-of-death did change starkly upon introduction of a new technology gene therapy drug rebranded as a “vaccine.”
In addition to offering new techniques in finding data paradoxes, new visualizations to determine timing of anomalies, new profiles of seasonality in waveforms using frequency domain analyses, new age profile of excess deaths methods, and other world firsts in epidemiological findings, TInBUQ provides insight into fraud detection, custom and practice change detection, and other effects on data integrity.
Most importantly, TInBUQ produces a path to find the best records for deep inspection, which yields important answers derived from evidence such as vaccine dates from VAERS reports and Medicare/Medicaid reports, number days since vaccination, express statements by medical examiners that the vaccine is a cause-of-death, and medical files that contain times of medications, blood anomalies, and other diagnostics.
There is no method in the world that comes close to TInBUQ. One engineer produced more accurate and ground-breaking findings than hundreds of thousands of public health employees and PhD epidemiologists around the world.
ISM cannot prove anything conclusively. However, TInBUQ, using RLSD [Record-Level Source Data] investigation, can conclusively determine causality and quantify those affected.
Adopt TInBUQ. The People will then have an answer on the TRUTH of “safe and effective” in one man-week and a methodology path for “public health” that will last ages.
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Header image: GCG Jhanjeri
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