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Record W3153201869 · doi:10.18103/mra.v9i4.2371

COVID-19 Attributed Cases and Deaths are Statistically Higher in States and Counties with 5th Generation Millimeter Wave Wireless Telecommunications in the United States.

2021· article· en· W3153201869 on OpenAlexaff
angela tsiang, Magda Havas

Bibliographic record

VenueMedical Research Archives · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsTrent University
Fundersnot available
KeywordsDemographyCoronavirus disease 2019 (COVID-19)PopulationMedicineMortality rateExtremely high frequencyStatisticsTelecommunicationsMathematicsEnvironmental healthInternal medicineEngineering

Abstract

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COVID-19-attributed case and death rates for the U.S.A. were analyzed through May 2020 in three ways – for all 50 states, the country’s largest counties, and the largest counties in California – and found to be statistically significantly higher for states and counties with compared to those without 5G millimeter wave (mmW) technology. 5G mmW index was a statistically significant factor for the higher case and rates in all three analyses, while population density, air quality and latitude were significant for only one or two of the analyses. For state averages, cases per million were 79% higher (p = 0.012), deaths per million were 94% higher (p = 0.049), cases per test were 68% higher (p = 0.003) and deaths per test were 81% higher (p = 0.025) for states with vs. without mmW. For county averages, cases per million were 87% higher (p = 0.005) and deaths per million were 165% higher (p = 0.012) for counties with vs. without mmW. While higher population density contributed to the higher mean case and death rates in the mmW states and counties, exposure to mmW had about the same impact as higher density of mmW states on mean case and death rates and about three times as much impact as higher density for mmW counties on mean case and death rates. Based on multiple linear regression, if there was no mmW exposure, case and death rates would be 18-30% lower for 5G mmW states and 39-57% lower for 5G mmW counties. This assessment clearly shows exposure to 5G mmW technology is statistically significantly associated with higher COVID-19 case and death rates in the U.S.A. The mechanism–should this be a causal relationship–may relate to changes in blood chemistry, oxidative stress, an impaired immune response, an altered cardiovascular and/or neurological response. 1. Introduction The first documented case of COVID-19 was reported in Wuhan, China in December 2019. To prevent its spread, the U.S. blocked travel from China on January 31st and declared a National Emergency on March 13th, 2020. After the World Health Organization (WHO) declared it a pandemic on March 19, 2020, the U.S. began quarantine and stay-at-home orders to slow the virus’ spread and to “flatten the curve”. Despite these precautions, the virus spread quickly in the U.S. and around the globe. The infectious agent was named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to genetic similarity to SARS-CoV that caused a pandemic in 2002-4. The disease associated with SARS-CoV-2 is COVID-19, which is an abbreviation for Coronavirus Disease 2019 associated with SARS-CoV-2. According to the U.S. Centers for Disease Control the epidemiological triangle for infectious diseases consists of the agent, the host and the environment. While attention has focused on the agent (genetics, modes of infection, etc.) and the host (age and comorbidities), little attention has focused on key environmental factors. These include but are not limited to air quality since this was initially identified as a respiratory illness, population density for person to person transmission, and electromagnetic radiation since COVID-19 appeared after 5G was implemented and many of the COVID-19 symptoms resemble those of microwave sickness. As of September 18, 2020, according to Johns Hopkins University, the cases are not uniformly distributed globally (Figure 1). Many factors may account for this: testing differences, per capita income, standard of health care, population demographics, and environmental factors among others. This paper focuses on four environmental factors that may relate to the spread and fatality of this disease: population density, air pollution, latitude (which determines potential endogenous vitamin D production) and presence of 5G mmW technology, which is present in combination with frequencies used in previous generations of wireless communications from 1G to 4G and does not replace them. These data, along with COVID-19 case and death data, were readily available for the United States. Figure 1. Data for COVID-19 (as of September 18, 2020) and rollout of 5G as of September 2020. As of August 9, 2020, the U.S. was #1 out of 213 nations in the world for the highest number of total COVID-19 cases at 5.2 million, with 15,698 cases per million (9th highest) and 500 deaths per million (10th highest) [1]. The rollout of 5G technology is to support the Internet of things (IoT). As of January 2020, 31 countries had working 5G networks globally [2-5] In the top quartile of the highest ranking countries for COVID-19 deaths per million, 16 of them had working 5G networks; while only 7 countries had 5G in the 2nd highest quartile; 6 in the 3rd highest quartile and only 2 in the bottom quartile. In the top quartile, the 5G countries with higher deaths per million than the U.S. were San Marino (1238), Belgium (851), U.K. (686), Spain (610) and Italy (582). The other countries with 5G in the top quartile with fewer deaths per million than the U.S. were Ireland (358), Switzerland (229), South Africa (175), Romania (140), Germany (110), Denmark (106), Monaco (102), Oman (100), Bahrain (95), and Saudi Arabia (91). Three radio frequency bands are used in 5th Generation (5G) wireless communications. The low band refers to frequencies below 1 GHz; the mid band to frequencies between 1 GHz and 6 GHz, and the high band to the millimeter waves (mmW), which are 24 GHz and above. The U.S. telecommunication companies began using mmW for 5G wireless communications in 2019 after their acquisition of the mmW spectrum, making the U.S. the first country in the world to use mmW for 5G. In June 2019, FCC’s Auction 101 for 28 GHz sold for $700 million and Auction 102 for 24 GHz sold for $2 billion [6], and in March 2020, 37, 39 and 47 GHz bands in Auction 103 sold for $7.5 billion [7], generating a total of $10 billion for the U.S. government. As of February 2020, European countries were still not using mmW for 5G [8], and other countries have used only the low and mid band frequencies for 5G. To achieve higher speeds for 5G, densification of antennas has occurred worldwide. Also, because mmW have shorter wavelengths (higher frequencies) than that used for 1G to 4G, they are more susceptible to interference from obstructions, thus requiring more transmitters closer to users, which have been added to streetlamps and utility poles in some cities. The shorter distance and higher density of mmW antennas translates into higher radiation exposures, as acknowledged by the FCC’s 2019 Notice of Proposed Rulemaking 19-126 [9] to increase the current RF exposure limits four-fold to accommodate 5G mmW devices and infrastructure. If environmental exposure to 5G mmW increases the severity of COVID-19 or other viral infections, then the rapid rollout of 5G technology should be reconsidered. 2. Methods 2.1 COVID-19 Attributed Cases and Deaths Data for number of cases, deaths, and tests for COVID-19 from Worldometer was assessed on April 22, 2020, May 15, 2020, and May 31, 2020 [1]. Data collection was stopped on May 31, 2020 because the nationwide quarantine effectively ended by that time as people in major cities all around the country broke quarantine when they gathered in crowds and some states began lifting their stay-at-home orders. 2.2 Variables: Air Quality Index, Latitude, Population Density and mmW Index A mmW exposure index was calculated based on the sum of the total population of the cities serviced by mmW 5G by each provider in a county or state, divided by the total population of that county or state. This factor is not a calculation of the mmW exposure level but a differentiation between the different exposure levels in each state and county based on the number of mmW providers and the number of mmW cities and their population in those counties or states, which is necessary for statistical analysis. Population density data were obtained from Wikipedia, which are calculated from population data from the U.S. Census divided by the area of the state or county. Air Quality Index (AQI) data from 2019 from the EPA were included in the analysis for states and counties. Latitude, which may relate to potential production of endogenous vitamin D associated with sun exposure, was also included in the analysis for counties. 2.3 States and Counties with and without 5G mmW Networks Cities with 5G mmW networks were chosen for analysis because the most frequencies for wireless communications (5G mmW plus low and mid band 5G as well as frequencies from previous generations 1G to 4G) and the highest RF exposures due to the increased number of small cell antennas for 5G and their placement close to users would be present there. Even though urbanization and high density may be part of the criteria for choosing where to locate 5G mmW, and therefore it may seem appropriate to adjust the case and death rate data for urbanization and density, it is actually NOT appropriate to do so for this analysis. The higher the urbanization and density in an area, the higher the levels of RF radiation present because of the higher density of cell phone towers, Wi-Fi hot spots, cell phones and Wi-Fi routers present in highly urbanized or dense areas. To adjust the data for urbanization and density would therefore remove the effect of higher levels of RF radiation present in highly urbanized or dense areas. Therefore, case and death rate data and charts were not adjusted for density or urbanization. However, multi-variate analysis was done to determine if urbanization or density, along with AQI and latitude, were statistically significant factors in the case and death rates using multiple linear regression, and then their contributions relative to the contribution from 5G mmW to the case and death rates were calculated. Counties and states with mmW 5G service were determined from the websites of the wireless providers AT&T [10], T-Mobile [11], and Verizon [12] which specified the cities that they service with mmW 5G

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.237
GPT teacher head0.467
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations9
Published2021
Admission routes1
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