The CDC’s Grossly Contradictory Death Numbers (Click on Image to View the Video)
The CDC uses two grossly contradictory numbers of annual deaths from pneumonia and influenza: about 55,000 in the annual leading causes of the death report and about 188,000 in National Center for Health Statistics (NCHS) data used on the FluView web site to report the percentage of deaths each week due to pneumonia and influenza. These differ by a factor of OVER THREE. The larger FluView number is comparable to the current cumulative total COVID-19 deaths in the United States (Aug 30, 2020).
Since it is generally agreed that lockdowns and quarantines are not justified for a disease similar to typical annual pneumonia and influenza deaths, the reasons for this gross contradiction in the two annual death numbers should be resolved. Is it correct to compare the COVID-19 death numbers to the FluView number, the leading causes of death number, or some other number and, if so, exactly why and how?
Video Transcript: The CDC uses two grossly contradictory numbers of annual deaths from pneumonia and influenza: about 55,000 in the annual leading causes of the death report and about 188,000 in National Center for Health Statistics (NCHS) data used on the FluView web site to report the percentage of deaths each week due to pneumonia and influenza. These differ by a factor of OVER THREE.
This is the leading causes of death report for 2017 on the CDC web site. Table C: Deaths and percentage of total deaths for the 10 leading causes of death: United States, 2016 and 2017 on Page Nine. Note line item number 8 “pneumonia and influenza” with 55,672 deaths in 2017. Also note 2,813,503 deaths from all causes in 2017.
This is the CDC FluView web site. The red line purports to be the percentage of weekly deaths caused by pneumonia and influenza. It varies seasonally and averages about six percent over a year. Six percent of the 2,813,503 deaths in 2017 is 168,810 deaths, over three times the 55,672 deaths in the leading causes of death report.
The actual numbers are available here in data files from the National Center for Health Statistics (NCHS). These give about 188,000 deaths from pneumonia and influenza in 2017. The death numbers for other years are quite similar.
To be clear, the leading causes of deaths report gives 55,672 deaths from pneumonia and influenza in 2017.
The average six percent of deaths from the FluView Graph means about 170,000 deaths must have been due to pneumonia and influenza — NOT 55,000. In fact, the raw data from the NCHS on the sites gives just about 188,000 deaths due to pneumonia and influenza in 2017, over THREE TIMES the number of deaths in the leading causes of death report and the widely quoted estimated deaths from flu from the CDC.
This means the number of pneumonia and influenza deaths must be highly arbitrary, dependent on unstated definitions, or there are gross counting errors. The larger FluView number of 188,000 is comparable to the current total of COVID-19 deaths in the US which is often compared to a smaller number of flu deaths each year similar to the leading causes of deaths number of 55,000.
Since it is generally agreed that lockdowns and quarantines are not justified for a disease similar to typical annual pneumonia and influenza deaths, the reasons for this gross contradiction in the two annual death numbers should be resolved. Is it correct to compare the COVID-19 death numbers to the FluView number, the leading causes of death number, or some other number and, if so, exactly why and how?
The most recent raw data appears to still be accessible on the FluView Pneumonia and Influenza Mortality web page:
Subscribers gain access to the advanced professional features of our censored search web site and service — censored-search.com — a search engine for censored Internet content banned or shadow-banned by increasingly censored, advertising beholden social media and search engines such as Google, YouTube, and Facebook. The free version of censored-search.com — available to all — uses a modified page rank algorithm, essentially a popularity contest. The paid professional version includes advanced search algorithms to find and prioritize content that is probably being censored by vested interests because it is useful and true — for example, evidence that a product or service is harmful to users.
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
When I searched on YouTube for “peter doshi flu vaccine” I got a dozen videos apparently promoting the flu vaccine unrelated to Peter Doshi, and this video which actually is about Peter Doshi and the flu vaccine buried in the “Related to your search.” section on May 30, 2020.
Peter Doshi appears in several videos still on YouTube related to the flu vaccine. He is a noted critic of the US Centers for Disease Control’s contradictory and confusing language and numbers on influenza and pneumonia.
Note that the picture of Peter Doshi is almost certainly incorrect as can easily be seen by viewing other videos on YouTube with Peter Doshi. It may be a picture of Tom Jefferson, a more senior researcher with whom Doshi has worked.
(C) 2020 by John F. McGowan, Ph.D.
About Me
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
This is a short post on the critical distinction between the Case Fatality Rate (CFR) of a disease such as the SARS-COV-2 coronavirus thought to cause COVID-19 and the Infection Fatality Rate (IFR), also sometimes known as the actual mortality rate or lethality. This remains a source of confusion and perhaps deliberate obfuscation several months into the crisis.
The case fatality rate or CFR is the number of deathsattributed to the disease usually among those diagnosed with the disease divided by the number of diagnosed casesaccording to some diagnostic criterion, for example a “positive” RT-PCR (Reverse Transcriptase-Polymerase Chain Reaction) test.
The infection fatality rate or IFR is the number of deaths attributed to the disease divided by the actual number of people infected, which generally includes mild or asymptomatic infections that are not diagnosed. Most diseases have many mild or asymptomatic infections. This is not unusual and is the case for the coronavirus SARS-COV-2.
The CFR generally reflects those with more serious infections who seek medical attention, go to a hospital emergency room, etc. It is generally biased, usually higher than the IFR for most diseases, and also can vary a lot depending on the availability of tests and on other causes unrelated to the genuine lethality of the disease.
A disease that kills everyone who exhibits symptoms and no one who has no symptoms even though actually infected can have a case fatality rate (CFR) of 100 percent and and an infection fatality rate (IFR) of nearly 0.0 percent.
For example, an exotic disease that produces distinctive green and purple spots in those it kills — easily identifiable even without advanced tests like RT-PCR — but in fact kills only 100 people out of a United States population of 330 million even though most are infected for some reason.
Although there are a number of subtleties in the definition and computation of these numbers that I have omitted for clarity, the infection fatality rate (IFR), ideally broken down by age, medical conditions, and other risk factors, is key to evaluating the proper public health response to an outbreak of an infectious disease. Not the case fatality rate or CFR.
(C) 2020 by John F. McGowan, Ph.D.
About Me
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
A key issue in the current COVID-19 coronavirus pandemic is the role of aerosol transmission which is virtually unstoppable in the spread of the virus. Aerosol transmission is transmission by tiny particles only a few microns in size that float indefinitely or nearly indefinitely in the air. The finest human hair is about twenty microns in diameter.
Asymptomatic carriers which may comprise about eighty percent of cases mostly don’t cough and sneeze which produces larger particles that fall to the ground under gravity. Asymptomatic carriers probably spread the disease primarily through aerosol transmission or physical contact.
Aerosol transmission is virtually unstoppable except by the equivalent of wearing a space suit. If it is a substantial mode of transmission, lockdowns, quarantines, sheltering in place, most face masks, etc. are not effective and cannot explain low death numbers in regions like Santa Clara County, California where I live. One hundred and twenty-eight (128) reported COVID-19 deaths as of May 10, 2020 in a county of almost two million residents, probably with the closest ties to China of any region in the United States.
Santa Clara County COVID-19 Cases Dashboard on May 10, 2020
If aerosol transmission is a substantial mode of transmission, confining large numbers of people to apartment complexes and buildings is likely to spread the disease efficiently through hallways, lobbies, laundry rooms, other shared spaces, and the ventilation system of the building. Similarly, shopping at the few giant stores such as Walmart and Safeway left open as “essential” is likely to spread the disease efficiently.
Indeed more extensive testing appears to be showing the disease is much wider spread than originally thought/expected which also means that it is much less deadly than original reports and claims. The seeming dramatic spread in the New York City area is easy to understand with substantial aerosol transmission.
Aerosol Transmission of Influenza
Given the general panic and newness of the COVID-19 coronavirus, one should examine what is known about aerosol transmission of other, ostensibly well-studied viruses such as influenza. Remarkably, it remains unclear how much aerosol transmission contributes to the spread of influenza and apparently the subject of some controversy.
Given that the devastating “Spanish” or “swine” flu epidemic in 1918 is usually blamed on an influenza virus (as well as high profile “swine flu” scares in 1976 and 2009) this lack of knowledge is troubling: what have the NIH, CDC, and other agencies been doing with billions of dollars in funding specifically to prevent or contain a deadly influenza pandemic?
Some recent references which indicate that aerosol transmission is probably a major route of transmission for influenza.
Aerosol transmission is an important mode of influenza A virus spread
Benjamin J. Cowling, Dennis K. M. Ip, Vicky J. Fang, Piyarat Suntarattiwong, Sonja J. Olsen, Jens Levy, Timothy M. Uyeki, Gabriel M. Leung, J. S. Malik Peiris, Tawee Chotpitayasunondh, Hiroshi Nishiura & James Mark Simmerman
Influenza A viruses are believed to spread between humans through contact, large respiratory droplets and small particle droplet nuclei (aerosols), but the relative importance of each of these modes of transmission is unclear. Volunteer studies suggest that infections via aerosol transmission may have a higher risk of febrile illness. Here we apply a mathematical model to data from randomized controlled trials of hand hygiene and surgical face masks in Hong Kong and Bangkok households. In these particular environments, inferences on the relative importance of modes of transmission are facilitated by information on the timing of secondary infections and apparent differences in clinical presentation of secondary infections resulting from aerosol transmission. We find that aerosol transmission accounts for approximately half of all transmission events. This implies that measures to reduce transmission by contact or large droplets may not be sufficient to control influenza A virus transmission in households. (EMPHASIS ADDED)
Aerosol transmission of influenza A virus: a review of new studies
Raymond Tellier
Abstract
Over the past few years, prompted by pandemic preparedness initiatives, the debate over the modes of transmission of influenza has been rekindled and several reviews have appeared. Arguments supporting an important role for aerosol transmission that were reviewed included prolonged survival of the virus in aerosol suspensions, demonstration of the low infectious dose required for aerosol transmission in human volunteers, and clinical and epidemiological observations were disentanglements of large droplets and aerosol transmission was possible. Since these reviews were published, several new studies have been done and generated new data. These include direct demonstration of the presence of influenza viruses in aerosolized droplets from the tidal breathing of infected persons and in the air of an emergency department; the establishment of the guinea pig model for influenza transmission, where it was shown that aerosol transmission is important and probably modulated by temperature and humidity; the demonstration of some genetic determinants of airborne transmission of influenza viruses as assessed using the ferret model; and mathematical modelling studies that strongly support the aerosol route. These recent results and their implication for infection control of influenza are discussed in this review.
J R Soc Interface. 2009 Dec 6; 6(Suppl 6): S783–S790.
Review of Aerosol Transmission of Influenza A Virus
Raymond Tellier
In theory, influenza viruses can be transmitted through aerosols, large droplets, or direct contact with secretions (or fomites). These 3 modes are not mutually exclusive. Published findings that support the occurrence of aerosol transmission were reviewed to assess the importance of this mode of transmission. Published evidence indicates that aerosol transmission of influenza can be an important mode of transmission, which has obvious implications for pandemic influenza planning and in particular for recommendations about the use of N95 respirators as part of personal protective equipment.
Much of the published literature on aerosol transmission of SARS-COV-2 focuses on possible aerosol transmission during medical procedures and the risks to doctors, dentists, and other health professionals. This has been part of the justification for aggressive use of intubation in treatment of the disease. Intubation is an extremely risky, dangerous medical procedure.
There have been some scientific and scholarly articles on aerosol transmission in non-medical settings — the general spread of the disease etc. It should be noted that all articles on COVID-19 in the last few months are the product of a high stress crisis atmosphere where the fight-or-flight response is almost certainly activated at a high level. The fight-or-flight response generally degrades much higher cognitive function in favor of short term thinking optimized for physical combat in ancient times.
Airborne transmission of SARS-CoV-2: the world should face the reality
Lidia Morawskaa,⁎ and Junji Caob
Hand washing and maintaining social distance are the main measures recommended by the World Health Organization (WHO) to avoid contracting COVID-19. Unfortunately, these measured do not prevent infection by inhalation of small droplets exhaled by an infected person that can travel distance of meters or tens of meters in the air and carry their viral content. Science explains the mechanisms of such transport and there is evidence that this is a significant route of infection in indoor environments. Despite this, no countries or authorities consider airborne spread of COVID-19 in their regulations to prevent infections transmission indoors. It is therefore extremely important, that the national authorities acknowledge the reality that the virus spreads through air, and recommend that adequate control measures be implemented to prevent further spread of the SARS-CoV-2 virus, in particularly removal of the virus-laden droplets from indoor air by ventilation.
Airborne route and bad use of ventilation systems as non-negligible factors in SARS-CoV-2 transmission
G. Correia,a,b,⁎ L. Rodrigues,b M. Gameiro da Silva,c and T. Gonçalvesa,b
Summary
The world is facing a pandemic of unseen proportions caused by a corona virus named SARS-CoV-2 with unprecedent worldwide measures being taken to tackle its contagion. Person-to-person transmission is accepted but WHO only considers aerosol transmission when procedures or support treatments that produce aerosol are performed. Transmission mechanisms are not fully understood and there is evidence for an airborne route to be considered, as the virus remains viable in aerosols for at least 3 h and that mask usage was the best intervention to prevent infection.
Heating, Ventilation and Air Conditioning Systems (HVAC) are used as a primary infection disease control measure. However, if not correctly used, they may contribute to the transmission/spreading of airborne diseases as proposed in the past for SARS.
The authors believe that airborne transmission is possible and that HVAC systems when not adequately used may contribute to the transmission of the virus, as suggested by descriptions from Japan, Germany, and the Diamond Princess Cruise Ship. Previous SARS outbreaks reported at Amoy Gardens, Emergency Rooms and Hotels, also suggested an airborne transmission.
Further studies are warranted to confirm our hypotheses but the assumption of such way of transmission would cause a major shift in measures recommended to prevent infection such as the disseminated use of masks and structural changes to hospital and other facilities with HVAC systems.
Consideration of the Aerosol Transmission for COVID‐19 and Public Health
Elizabeth L. Anderson Paul Turnham John R. Griffin Chester C. Clarke Risk Analysis: An International Journal (First published: 01 May 2020)
Abstract
This article analyzes the available evidence to address airborne, aerosol transmission of the SARS-CoV-2. We review and present three lines of evidence: case reports of transmission for asymptomatic individuals in association with studies that show that normal breathing and talking produce predominantly small droplets of the size that are subject to aerosol transport; limited empirical data that have recorded aerosolized SARS‐CoV‐2 particles that remain suspended in the air for hours and are subject to transport over distances including outside of rooms and intrabuilding, and the broader literature that further supports the importance of aerosol transmission of infectious diseases. The weight of the available evidence warrants immediate attention to address the significance of aerosols and implications for public health protection.
There is a remarkable lack of key measurements in the current coronavirus COVID-19 pandemic. These include the actual mortality rate (aka infection fatality rate) broken down by age, sex, race, pre-existing medical conditions, ambient temperature, sunlight levels, pollution levels, other risk factors and medical treatment used (e.g. intubation). The false positive and false negative rates of the tests for the disease, both the tests for an active infection such as the RT-PCR tests and tests for past infection such as the antibody tests. The methods and rates of transmission for the disease. Aerosol transmission probably occurs at least at a low level and is virtually unstoppable.
The CDC and the National Security bioweapons defense programs should have been set up to quickly and efficiently collect these key data and parameters as soon as a possible outbreak or attack was detected, independent of warnings and information provided by a potential adversary such as China or from the World Health Organization (WHO).
These key measurements of the properties of the virus and disease should be collected as soon as possible by anyone who can and shared with the world.
(C) 2020 by John F. McGowan, Ph.D.
About Me
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
A key issue in the current coronavirus COVID-19 pandemic is how it compares to “seasonal flu,” “flu,” “influenza” or “pneumonia and influenza,” terms that are often used interchangeably but have different definitions or implied definitions in different contexts.
An overlapping key issue is whether false positives from the coronavirus RT-PCR test or diagnoses without the test (e.g. lung x-rays or examination of a patient by a doctor) has attributed a substantial number of conventional pneumonia deaths and heart attacks to the COVID-19 coronavirus.
Remarkably, the United States Centers for Disease Control (CDC) appears to use two different counts (or model outputs?) of annual deaths from “influenza and pneumonia” or “pneumonia and influenza” that differ by over a factor of three.
The “Deaths: Final Data for 2017” report (Page Six, Table B) lists “influenza and pneumonia” as the eighth leading cause of death with 55,672 deaths in 2017.
Influenza and pneumonia (8th Leading cause of death in Deaths: Final Data for 2017)
In contrast, the Weekly Pneumonia and Influenza (P&I) Mortality Surveillance lists over 180,000 deaths from “pneumonia and influenza” (mostly pneumonia) in 2017 in the data files on the site apparently used to generate the FluView plot displayed. The weekly surveillance number provides a much larger pool of potential false positives than the more widely quoted number of about 50,000 “flu” deaths per year.
Influenza: a study in contemporary medical politics by Peter Doshi
This is a well written but long (312 pages) dissertation. All of it is relevant to the current pandemic crisis, but it is a lot to digest. The most important and most relevant to the current pandemic section is Chapter 4: False Assumptions: a Shaky Foundation for Consensus (Pages 151-212, including tables and figures).
Key topics discussed in detail in this chapter include:
The CDC uses models to assign many deaths to influenza (the influenza viruses) even though doctors rarely diagnose influenza, rarely list influenza as a cause of death on death certificates, and most laboratory tests of samples from patients with respiratory illnesses (often called Influenza Like Illnesses or ILI) do not confirm the presence of the influenza viruses and often identify other viruses such as rhinovirus, adenovirus, various coronaviruses, etc. as present instead. These models may even assign deaths listed on death certificates as heart attacks to the total.
The models differ from researcher and publication to researcher and publication, have changed dramatically over the years, notably a jump from 20,000 estimated “flu” deaths in 2002 to a widely quoted estimate of 36,000 in 2003.
The evidence that flu vaccines work is weak and contradictory.
Conclusion
There is a remarkable lack of key measurements in the current coronavirus COVID-19 pandemic. These include the actual mortality rate (aka infection fatality rate) broken down by age, sex, race, pre-existing medical conditions, ambient temperature, sunlight levels, pollution levels, and other risk factors. The false positive and false negative rates of the tests for the disease, both the tests for an active infection such as the RT-PCR tests and tests for past infection such as the antibody tests. The methods and rates of transmission for the disease. Aerosol transmission probably occurs at least at a low level and is virtually unstoppable.
The confusing language and numbers on pneumonia and influenza on the CDC web site and in various official reports and documents seem to be primarily for marketing the flu vaccines rather than enabling informed decisions by patients and doctors or supporting external scientific research into the influenza viruses or other diseases.
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
A key question about pneumonia and influenza (including the COVID-19 Sars-Cov-2 coronavirus disease) is the role of weather and temperature on the incidence, severity, and mortality rates from the diseases. Pneumonia and influenza cases and deaths are seasonal, peaking in the winter when sunlight levels and temperatures are lower. The curve for pneumonia and influenza deaths is roughly sinusoidal, which would be expected from something connected to sunlight levels. This is not what one would naively expect from children spreading the disease during the school year; we would expect an abrupt step up in the fall when kids return to school and a step down in the spring when school closes.
A previous post listed a number of resources on the possible direct effects of sunlight through vitamin D production and direct destruction of viruses and bacteria by sunlight, especially the ultraviolet component.
Seasonal Variation in Deaths from Pneumonia and Influenza (2014-2020)
There is a fair amount of research on the role of weather and temperature in the incidence, severity and mortality of pneumonia and influenza. Generally the research seems to support a positive correlation between lower temperatures and also rapid changes in temperature with higher incidence, severity and mortality from pneumonia and influenza as well as other causes of death, notably coronary disease. It also suggests extreme heat “heat waves” is positively correlated with pneumonia. Below are several scientific and scholarly articles; the interested reader can find more articles and details at PubMed (enter “pneumonia and weather” for example in the search box).
Note that correlation does not prove causation.
Scientific and Scholarly Articles
The Lancet
Volume 315, Issue 8183, 28 June 1980, Pages 1405-1408
Journal home page for The Lancet
Occasional Survey
THE WEATHER AND DEATHS FROM PNEUMONIA
Author links open overlay panelG.M.Bull
https://doi.org/10.1016/S0140-6736(80)92666-5
Age Ageing. 1978 Nov;7(4):210-24.
Environment, temperature and death rates.
Bull GM, Morton J.
Abstract
Analysis of recorded monthly deaths in England and Wales shows a close association of death rates with external temperature in most diseases other than the cancers. Analysis of daily deaths in England and Wales and in New York shows the following relationships between temperature and deaths from myocardial infarction, strokes and pneumonia. Between -10 degrees and +20 degrees C mimimum temperature there is a nearly linear fall in deaths as the temperature rises. Above 20 degrees C deaths rise steeply as the temperature rises and below -10 degrees C rise steeply as temperature falls. These associations of deaths with temperature are much stronger in the elderly than in younger subjects. Detailed analysis of the daily deaths in England and Wales from myocardial infarction, strokes and pneumonia show that short-term (1–2 days) temperature changes have little effect on death rates but medium-term (7–10 days) and longer-term (three or more weeks) changes associated with very significant changes in death rates. The three diseases vary in the time relations between temperature change and change in death rates. In all three there is an interval between the change in temperature and death and this is shortest in the case of myocardial infarction (1–2 days before death), longest in the case of pneumonia (about a week before death) and intermediate in the case of strokes (about 3–4 days before death). At low temperatures death rates increase as the duration of temperature change increases, while at high temperatures (but below +20 degrees C) death rates decrease as the period of temperature change is longer. The implications of these findings are discussed and it is postulated that there is probably causal relationship between temperature change and deaths from a wide variety of diseases. A proximal link in the chain is probably a failure of autonomic control of body temperature in the elderly leading to a change in body temperature and some humoral change which in turn leads to death. It is not appropriate to concentrate on hypothermia as the relationship between temperature and death is seen at all temperatures.
================================================= Age Ageing. 1975 Feb;4(1):19-31. Seasonal and short-term relationships of temperature with deaths from myocardial and cerebral infarction. Bull GM, Morton J. Abstract
In subjects over 60, changes in temperature lasting two or more days are associated with highly significant changes in death rates from myocardial infarction and cerbral vascular accidents. In both cases, the lower the temperature the higher the death rate and vice versa. Moreover the temperatures one to four days prior to the clinical onset of infarction are more relevant than that on the day of onset, a fact which may have a bearing on prophylaxis. In the case of strokes, a high temperature on the day of onset is also associated with an increase in deaths on that day. The relevance of these findings to possible mechanisms and prophylaxis is discussed.
Lancet. 1979 May 5;1(8123):982-3. No abstract available.
PMID:
87658
J Intern Med. 1991 Dec;230(6):479-85.
High coronary mortality in cold regions of Sweden.
Gyllerup S(1), Lanke J, Lindholm LH, Scherstén B.
Author information:
(1)Health Sciences Centre, Lund University, Dalby, Sweden.
The hypothesis that cold climate is associated with high coronary mortality in
Sweden is tested. Cold exposure was calculated in each of the 284 municipalities
of Sweden. There was a significant association between cold exposure and coronary
mortality in both sexes in all age groups. The strongest association was found in
men aged 40-64 years (coefficient of determination k = 0.39). The decile of men
aged 40-64 years who lived in the coldest municipalities had a 40% excess
mortality. A significant association was also found between cold exposure and
mortality from cerebrovascular diseases. We conclude that there is a strong
regional association between cold exposure and high coronary mortality.
DOI: 10.1111/j.1365-2796.1991.tb00478.x
PMID: 1748856 [Indexed for MEDLINE]
Author information:
(1)Husensjö Group Practice, Helsingborg, Sweden.
In many European countries there is a tendency towards higher coronary mortality
in the northern parts of the country. Furthermore the highest coronary mortality
rates are found in the colder parts of Europe. We studied the regional variation
in coronary mortality in the 284 Swedish municipalities during a ten-year period
and the relation to the cold exposure in each municipality during the same time
period.METHODS: Mortality rates for each municipality were acquired from the
death certificates and indirectly standardised against the country. Temperature
readings from measurements 5 times a day during daytime were used to form a cold
index. We also compensated for wind chill by using Siples wind chill index.
Multiple regression models were used. Second degree polynomials were used for the
explanatory variables.
RESULTS: There was a strong relation between the cold exposure in a municipality
and coronary mortality. The cold index alone could explain 39% of the regional
variation in coronary mortality. In a multiple regression model, cold index was
the strongest explanatory variable. The coronary mortality in the coldest decile
of the population was 40% higher than in the country as a whole.
CONCLUSIONS: There is a strong regional association between cold exposure and
coronary mortality in Sweden. However, in this type of study, it is not possible
to determine whether this association is a causal one or not.
Cold climate is an important factor in explaining regional differences in
coronary mortality even if serum cholesterol and other established risk factors
are taken into account.
Gyllerup S(1), Lanke J, Lindholm LH, Schersten B.
Author information:
(1)Health Sciences Centre, Lund University, Dalby Sweden.
Earlier studies have shown a strong regional association between cold climate and
coronary mortality in Sweden and that coronary mortality is more strongly
associated with cold climate than with other explanatory factors such as drinking
water hardness, socioeconomic factors, tobacco and sales of butter. To examine
the joint impact of these factors and to investigate regional differences in
serum cholesterol and their relation to cold climate and coronary mortality,
regression analyses were performed with 259 municipalities in Sweden as units.
Mortality from acute myocardial infarction in men aged 40-64 during 1975-1984 was
used as the dependent variable. A cold index was calculated, this index and the
above mentioned factors were used as explanatory variables. The main results
were: Cold index was the strongest factor when introduced into a multiple
regression model. Four other strong factors had to be used to obtain the same
explanatory strength as cold index did alone, and even when introduced as the
last factor, cold index increased the coefficient of determination substantially.
In a subsample of 37 municipalities, serum cholesterol was not significantly
associated with coronary mortality. However, there was a significant correlation
between cold index and serum cholesterol.
DOI: 10.1177/003693309303800604
PMID: 8146634 [Indexed for MEDLINE]
Am J Epidemiol. 2016 Oct 15;184(8):555-569. Epub 2016 Oct 6.
Pneumonia Hospitalization Risk in the Elderly Attributable to Cold and Hot
Temperatures in Hong Kong, China.
Qiu H, Sun S, Tang R, Chan KP, Tian L.
The growth of pathogens potentially relevant to respiratory tract infection may
be triggered by changes in ambient temperature. Few studies have examined the
association between ambient temperature and pneumonia incidence, and no studies
have focused on the susceptible elderly population. We aimed to examine the
short-term association between ambient temperature and geriatric pneumonia and to
assess the disease burden attributable to cold and hot temperatures in Hong Kong,
China. Daily time-series data on emergency hospital admissions for geriatric
pneumonia, mean temperature, relative humidity, and air pollution concentrations
between January 2005 and December 2012 were collected. Distributed-lag nonlinear
modeling integrated in quasi-Poisson regression was used to examine the
exposure-lag-response relationship between temperature and pneumonia
hospitalization. Measures of the risk attributable to nonoptimal temperature were
calculated to summarize the disease burden. Subgroup analyses were conducted to
examine the sex difference. We observed significant nonlinear and delayed
associations of both cold and hot temperatures with pneumonia in the elderly,
with cold temperatures having stronger effect estimates. Among the 10.7% of
temperature-related pneumonia hospitalizations, 8.7% and 2.0% were attributed to
cold and hot temperatures, respectively. Most of the temperature-related burden
for pneumonia hospitalizations in Hong Kong was attributable to cold
temperatures, and elderly men had greater susceptibility.
Influenza Other Respir Viruses. 2016 Jul;10(4):310-3. doi: 10.1111/irv.12369.
Epub 2016 May 17.
Cold, dry air is associated with influenza and pneumonia mortality in Auckland,
New Zealand.
Davis RE(1), Dougherty E(1), McArthur C(2), Huang QS(3), Baker MG(4).
Author information:
(1)Department of Environmental Sciences, University of Virginia, Charlottesville,
VA, USA.
(2)Auckland City Hospital, Auckland, New Zealand.
(3)Institute of Environmental Science and Research, Wellington, New Zealand.
(4)University of Otago-Wellington, Wellington, New Zealand.
The relationship between weather and influenza and pneumonia mortality was
examined retrospectively using daily data from 1980 to 2009 in Auckland, New
Zealand, a humid, subtropical location. Mortality events, defined when mortality
exceeded 0·95 standard deviation above the mean, followed periods of anomalously
cold air (ta.m. = -4·1, P < 0·01; tp.m. = -4·2, P < 0·01) and/or anomalously dry
air (ta.m. = -4·1, P < 0·01; tp.m. = -3·8, P < 0·01) by up to 19 days. These
results suggest that respiratory infection is enhanced during unusually cold
conditions and during conditions with unusually low humidity, even in a
subtropical location where humidity is typically high.
Environ Res. 2019 Feb;169:139-146. doi: 10.1016/j.envres.2018.10.031. Epub 2018
Oct 30.
Impacts of cold weather on emergency hospital admission in Texas, 2004-2013.
Chen TH(1), Du XL(1), Chan W(2), Zhang K(3).
Author information:
(1)Department of Epidemiology, Human Genetics and Environmental Sciences, School
of Public Health, The University of Texas Health Science Center at Houston,
Houston, TX 77030, USA.
(2)Department of Biostatistics and Data Science, School of Public Health, The
University of Texas Health Science Center at Houston, Houston, TX, USA.
(3)Department of Epidemiology, Human Genetics and Environmental Sciences, School
of Public Health, The University of Texas Health Science Center at Houston,
Houston, TX 77030, USA; Southwest Center for Occupational and Environmental
Health, School of Public Health, The University of Texas Health Science Center at
Houston, Houston, TX, USA. Electronic address: kai.zhang@uth.tmc.edu.
Cold weather has been identified as a major cause of weather-related deaths in
the U.S. Although the effects of cold weather on mortality has been investigated
extensively, studies on how cold weather affects hospital admissions are limited
particularly in the Southern United States. This study aimed to examine impacts
of cold weather on emergency hospital admissions (EHA) in 12 major Texas
metropolitan statistical areas (MSAs) for the 10-year period, 2004-2013. A
two-stage approach was employed to examine the associations between cold weather
and EHA. First, the cold effects on each MSA were estimated using distributed lag
non-linear models (DLNM). Then a random effects meta-analysis was applied to
estimate pooled effects across all 12 MSAs. Percent increase in risk and
corresponding 95% confidence intervals (CIs) were estimated as with a 1 °C (°C)
decrease in temperature below a MSA-specific threshold for cold effects.
Age-stratified and cause-specific EHA were modeled separately. The majority of
the 12 Texas MSAs were associated with an increased risk in EHA ranging from 0.1%
to 3.8% with a 1 ⁰C decrease below cold thresholds. The pooled effect estimate
was 1.6% (95% CI: 0.9%, 2.2%) increase in all-cause EHA risk with 1 ⁰C decrease
in temperature. Cold wave effects were also observed in most eastern and southern
Texas MSAs. Effects of cold on all-cause EHA were highest in the very elderly
(2.4%, 95% CI: 1.2%, 3.6%). Pooled estimates for cause-specific EHA association
were strongest in pneumonia (3.3%, 95% CI: 2.8%, 3.9%), followed by chronic
obstructive pulmonary disease (3.3%, 95% CI: 2.1%, 4.5%) and respiratory diseases
(2.8%, 95% CI: 1.9%, 3.7%). Cold weather generally increases EHA risk
significantly in Texas, especially in respiratory diseases, and cold effects
estimates increased by elderly population (aged over 75 years). Our findings
provide insight into better intervention strategy to reduce adverse health
effects of cold weather among targeted vulnerable populations.
Environ Res. 2014 Jul;132:334-41. doi: 10.1016/j.envres.2014.04.021. Epub 2014
May 14.
Impact of temperature on childhood pneumonia estimated from satellite remote
sensing.
Xu Z(1), Liu Y(2), Ma Z(2), Li S(3), Hu W(1), Tong S(4).
Author information:
(1)School of Public Health and Social Work & Institute of Health and Biomedical
Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
(2)Rollins School of Public Health, Emory University, Atlanta, GA, United States.
(3)School of Public Health, Shanghai Jiaotong University School of Medicine,
Shanghai, China.
(4)School of Public Health and Social Work & Institute of Health and Biomedical
Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
Electronic address: s.tong@qut.edu.au.
The effect of temperature on childhood pneumonia in subtropical regions is
largely unknown so far. This study examined the impact of temperature on
childhood pneumonia in Brisbane, Australia. A quasi-Poisson generalized linear
model combined with a distributed lag non-linear model was used to quantify the
main effect of temperature on emergency department visits (EDVs) for childhood
pneumonia in Brisbane from 2001 to 2010. The model residuals were checked to
identify added effects due to heat waves or cold spells. Both high and low
temperatures were associated with an increase in EDVs for childhood pneumonia.
Children aged 2-5 years, and female children were particularly vulnerable to the
impacts of heat and cold, and Indigenous children were sensitive to heat. Heat
waves and cold spells had significant added effects on childhood pneumonia, and
the magnitude of these effects increased with intensity and duration. There were
changes over time in both the main and added effects of temperature on childhood
pneumonia. Children, especially those female and Indigenous, should be
particularly protected from extreme temperatures. Future development of early
warning systems should take the change over time in the impact of temperature on
children’s health into account.
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
I have added a video showing the CDC Pneumonia and Influenza Weekly Deaths web site as it is (was) on April 15, 2020. In this video I show the different web site sections I have discussed, download theNCHSData14.csvweekly deaths data file, go through the analysis briefly in a spreadsheet, and show the difference between the numbers in 2017 in the file and the Final Death (Leading Causes of Deaths) numbers in 2017.
The weekly pneumonia and influenza deaths data shows fewer deaths in weeks one through thirteen, the latest week in the file ending March 28, 2020, than in the comparable weeks in 2019 — last year. This despite the COVID-19 pandemic, lack of testing in the United States, asymptomatic carriers, and other issues.
The weekly pneumonia and influenza deaths data also show about 188,000 deaths from pneumonia and influenza in 2017, over THREE TIMES the about 55,000 deaths listed as “influenza and pneumonia” in the 2017 leading causes of death.
NOTE: If you are concerned about these odd numbers, please consider sharing the original post and/or this one by e-mail, a link on your web site or blog, or other methods in addition to advertising-funded and other big company social media. My original post of this on Hacker News soared for a few hours and then was flagged and shut down, for example. I have also encountered social media mobs that engage in name calling and do not address the substantive issues.
CDC Web Site Video
It seems likely to me that the CDC web site will change in response to questions about the confusing numbers and language. Hopefully, the CDC will clarify the language and numbers in an open, “transparent,” and genuinely honest way that survives critical scrutiny. Especially given the life and death situation.
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
Doomsday Virus? Coronavirus Cases NOT Boosting Weekly Death Numbers…YET
Doomsday Virus? Coronavirus cases are NOT boosting the weekly death numbers for pneumonia and influenza from the CDC and National Center for Health Statistics yet. This would be expected if the coronavirus is unusually deadly compared to other diseases that contribute to deaths categorized as pneumonia and influenza… YET! (Based on data through March 14, 2020)
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).
