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A Comparative Perceptualization Study
of Global Death Data attributed to Coronavirus Disease 2019 (COVID-19) and other factors
by Dr David Worrall

References

Covid-19 Statistical Data

The Covid Tracking Project. Reportedly, the most complete data available about COVID-19 in the US.
John Hopkins University's COVID-19 Data Repository from the Center for Systems Science and Engineering (CSSE).
John Hopkins University's World Country/State Data
NewYork Times US State Data
NewYork Times US County Data
Our World in Data corona virus data
Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21
Data for the Excess mortalitity study (above).
This dataset contains estimates of excess mortality from the COVID-19 pandemic for global populations during the period of January 1, 2020 – December 31, 2021. Excess mortality is defined as the net difference between the number of deaths during the pandemic (measured by observed or estimated all-cause mortality) and the number of deaths that would be expected based on past trends in all-cause mortality. The dataset also includes reported COVID-19 deaths (or deaths attributable to the virus), the reported COVID-19 mortality rate and the ratio between excess mortality rate and reported COVID-19 mortality rate rates for the same time period. The ratio of excess mortality rate to reported COVID-19 mortality is a measurement of undercounting of the true mortality impact of the pandemic. Methods and limitations for the model for estimating excess mortality can be found in detail in the publication.

Geographic & Demographic Data

Internet Usage Statistics and internetworldstats.com
World Factbook Data

Programming tools

Le Forestier, B. 2019. Yattag: A Python library for generating HTML or XML in a pythonic way.
Huang, X. 2019.
______ Anomoly Detection for Python
______ Genetic Algorithm in Python, which could be used for Sampling, Feature Select, Model Select, etc in Machine Learning.
Kejariwala‎, A. 2015.Introducing practical and robust anomaly detection in a time series.

Other useful resources

The following references are peripherally related to the perceptualization aims of this project, in as much as they have, or continue to inform its priorities and approaches.

Public discussion of covid-related research findings

Our World in Data has frequent discussions on current covid-19 data-related topics.
See, for example, their discussion on How do key COVID-19 metrics compare to earlier peaks?
The Great Darringtion Declaration
A delcaration by numerous infectious disease epidemiologists and public health scientists who have grave concerns about the damaging physical and mental health impacts of the prevailing COVID-19 policies, and recommend an approach they call Focused Protection.
Dr John Campbell's podcast on Youtube currently almost daily)
______ Vitamins D, K and zinc-related
______ Immunology with Professor Robert Clancy Eminent Australian Immunologist Robert Clancy discusses the science and clinical application of immunity, including the role of swallowing viruses in triggering various immune responses.
______ 18 million excess deaths.
Drs Bret Weinstein and Heather Heying (evolutionary biologists) The Dark Horse Podcast Covid/Vitamin D playlist
Seheult, R. 2020. Vitamin D and COVID 19: The Evidence for Prevention and Treatment of Coronavirus (SARS CoV 2))
Dr. Peter McCullough, with Anthony Pompliano. 2022. FDA Approval Never Happened For The Vaccines?
US Senator Ron Johnson, 2022. COVID-19: A Second Opinion (38 minutes) On January 24, 2022 Senator Ron Johnson invited a group of world renowned doctors and medical experts to the U.S. Senate to provide a different perspective on the global pandemic response, the current state of knowledge of early and hospital treatment, vaccine efficacy and safety, what went right, what went wrong, what should be done now, and what needs to be addressed long term. This 38 minute video highlights the 5-hour discussion.

Suggestions for inclusion in this list are welcome!

The suppression of information and the propogation of mis-information about this disease seems prevalent, including by corporate media, big-tech, and government agencies in various countries. Obvious examples include the efficacy of treatments using anti-virals and immune-system boosters.
If you know a reference that you think might be useful (wild conspiracy theories not being applicable in this context, please feel free to email the reference to sonipywiki_at_avatarDOTcomDOTau. Thanks!


Last update of this page: 2022-06-07

Banner images from Wikipedia. The 3rd image (blue) is a scientifically accurate atomic model of coronavirus (SARS-CoV-2) in which each ball is an atom.
3rd image credit: Alexey Solodovnikov (Idea, Producer, CG, Editor), Valeria Arkhipova (Scientific Сonsultant) CC BY-SA 4.0, via Wikimedia Commons