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

sonification.com.au/covid-19/

polymedia perceptualizations (sonifications and visualizations)

by

David Worrall

Audio Arts and Acoustics Department
Columbia College Chicago
dworrall_at_colum_dot_edu

SITE UNDER CONSTRUCTION
Last updated: 2023-03-12

Direct links to charts of raw reported data of daily death numbers,by first letter of region or Country name:

| A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z |

Introduction

Coronavirus Disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first case was identified in Wuhan, China, in December 2019. It has since spread worldwide, leading to an ongoing pandemic that spread globally in 2020.

This is a polymedia perceptualization study of data, reported daily, of global deaths that have been attributed to COVID-19.

Note: 'Region' is used here as a generic term to mean 'State', 'Province', 'Territory'. etc. In this study, for countries without separate regions, the Region Name is equivalent to the Country Name.

The data is... Some more guff about the methods etc

Regions with NO deaths due to Covid-19 reported

Of the 347 regions tracked in this study, the following 16 are reported as having NO deaths due to Covid-19:

 Antarctica Channel Islands [United Kingdom] Falkland Islands (Malvinas) [United Kingdom]
  Grand Princess [Canada] Jiangsu [China] Ningxia [China]
  Niue [New Zealand] Pitcairn Islands [United Kingdom] Qinghai [China]
  Repatriated Travellers [Canada] Saint Helena & Ascension & Tristan da Cunha [United Kingdom] Summer Olympics 2020
  Tibet [China] Tuvalu Vatican
  Winter Olympics 2022  

Regions reporting deaths due to Covid-19

Because of the wildly varying ways in which this virus spread globally, and the methods exployed to attempt to control the spread within Regions has also varied, Regions have been grouped in various ways. The principle grouping is by color-coding their daily chart according to the maximum number of deaths in any one day, as follows:

ColorMax. Daily Death rate
1 to 20
21 to 40
41 to 80
81 to 160
161 to 320
321 to 640
641 to 1280
1281 to 2560
2561 to 5120
5121 & above
Fig. Table of color-codes indicating
a region's maximum daily death rates.

In the following, the individual LETTERS on the Left are links to a raw listing charts for all regions being studied whose name begins with that letter.The region-names in the list are colored according to the above Figure. They are links to the individual bar charts.

 A   Afghanistan, Alabama, Alaska, Albania, Alberta, Algeria, American Samoa, Andorra, Angola, Anguilla, Anhui, Antarctica, Antigua and Barbuda, Argentina, Arizona, Arkansas, Armenia, Aruba, Australia, Australian Capital Territory, Austria, Azerbaijan,
 B   Bahamas, Bahrain, Bangladesh, Barbados, Beijing, Belarus, Belgium, Belize, Benin, Bermuda, Bhutan, Bolivia, Bonaire & Sint Eustatius & Saba, Bosnia and Herzegovina, Botswana, Brazil, British Columbia, British Virgin Islands, Brunei, Bulgaria, Burkina Faso, Burma, Burundi,
 C   Cabo Verde, California, Cambodia, Cameroon, Canada, Cayman Islands, Central African Republic, Chad, Channel Islands, Chile, China, Chongqing, Colombia, Colorado, Comoros, Congo-Brazzaville, Congo-Kinshasa (DR), Connecticut, Cook Islands, Costa Rica, Cote dIvoire, Croatia, Cuba, Curacao, Cyprus, Czechia,
 D   Delaware, Denmark, Diamond Princess, District of Columbia, Djibouti, Dominica, Dominican Republic,
 E   Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia,
 F   Falkland Islands (Malvinas), Faroe Islands, Fiji, Finland, Florida, France, French Guiana, French Polynesia, Fujian,
 G   Gabon, Gambia, Gansu, Georgia, Germany, Ghana, Gibraltar, Grand Princess, Greece, Greenland, Grenada, Guadeloupe, Guam, Guangdong, Guangxi, Guatemala, Guernsey, Guinea, Guinea-Bissau, Guizhou, Guyana,
 H   Hainan, Haiti, Hawaii, Hebei, Heilongjiang, Henan, Honduras, Hong Kong, Hubei, Hunan, Hungary,
 I   Iceland, Idaho, Illinois, India, Indiana, Indonesia, Inner Mongolia, Iowa, Iran, Iraq, Ireland, Isle of Man, Israel, Italy,
 J   Jamaica, Japan, Jersey, Jiangsu, Jiangxi, Jilin, Jordan,
 K   Kansas, Kazakhstan, Kentucky, Kenya, Kiribati, Kosovo, Kuwait, Kyrgyzstan,
 L   Laos, Latvia, Lebanon, Lesotho, Liaoning, Liberia, Libya, Liechtenstein, Lithuania, Louisiana, Luxembourg,
 M   MS Zaandam, Macau, Madagascar, Maine, Malawi, Malaysia, Maldives, Mali, Malta, Manitoba, Marshall Islands, Martinique, Maryland, Massachusetts, Mauritania, Mauritius, Mayotte, Mexico, Michigan, Micronesia, Minnesota, Mississippi, Missouri, Moldova, Monaco, Mongolia, Montana, Montenegro, Montserrat, Morocco, Mozambique,
 N   Namibia, Nauru, Nebraska, Nepal, Netherlands, Nevada, New Brunswick, New Caledonia, New Hampshire, New Jersey, New Mexico, New South Wales, New York, New Zealand, Newfoundland and Labrador, Nicaragua, Niger, Nigeria, Ningxia, Niue, North Carolina, North Dakota, North Korea, North Macedonia, Northern Mariana Islands, Northern Territory, Northwest Territories, Norway, Nova Scotia, Nunavut,
 O   Ohio, Oklahoma, Oman, Ontario, Oregon,
 P   Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Pennsylvania, Peru, Philippines, Pitcairn Islands, Poland, Portugal, Prince Edward Island, Puerto Rico,
 Q   Qatar, Qinghai, Quebec, Queensland,
 R   Repatriated Travellers, Reunion, Rhode Island, Romania, Russia, Rwanda,
 S   Saint Barthelemy, Saint Helena & Ascension & Tristan da Cunha, Saint Kitts and Nevis, Saint Lucia, Saint Pierre and Miquelon, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saskatchewan, Saudi Arabia, Senegal, Serbia, Seychelles, Shaanxi, Shandong, Shanghai, Shanxi, Sichuan, Sierra Leone, Singapore, Sint Maarten, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Australia, South Carolina, South Dakota, South Korea, South Sudan, Spain, Sri Lanka, St Martin, Sudan, Summer Olympics 2020, Suriname, Sweden, Switzerland, Syria,
 T   Taiwan, Tajikistan, Tanzania, Tasmania, Tennessee, Texas, Thailand, Tianjin, Tibet, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turks and Caicos Islands, Tuvalu,
 U   US, USA, Uganda, Ukraine, United Arab Emirates, United Kingdom, Unknown, Uruguay, Utah, Uzbekistan,
 V   Vanuatu, Vatican, Venezuela, Vermont, Victoria, Vietnam, Virgin Islands, Virginia,
 W   Wallis and Futuna, Washington, West Bank and Gaza, West Virginia, Western Australia, Winter Olympics 2022, Wisconsin, Wyoming,
 X   Xinjiang,
 Y   Yemen, Yukon, Yunnan,
 Z   Zambia, Zhejiang, Zimbabwe,

Types of Region/Country groupings on this Site

States, Provinces, Regions and Overseas Territories

COVID-19 Perceptualization
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HOME  |  States:USA  |  otherRegions: raw  |  Geographical regions  |  Latitude-adjusted  |  Density-adjusted  |  cause comparisons  |  Data  |  References

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: 2023-03-12

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