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Epidemiologic measurement on COVID-19 pandemic may have statistical biases which might affect next variant responses

Posted in Biomarkers: Inflammation, COVID-19, number of asymptomatic infections, Population Health Management, Genetics & Pharmaceutical, Population Health Management, Nutrition and Phytochemistry, SARS-CoV-2, SARS-CoV-2 Viral Variants, Treatment Protocols for COVID-19, tagged Bias measurement tools, bias minimization, bioethics, COVID-19, COVID-19 SARS-CoV-2, COVID-19 Treatment, SARS-CoV-2 on November 7, 2021| Leave a Comment »

Epidemiological measurement on COVID-19 pandemic may have statistical biases which might affect next variant responses

Reporter: Stephen J. Williams Ph.D.

Source: https://www.science.org/doi/10.1126/science.abi6602

From the jounal Science

Tackling the pandemic with (biased) data

CHRISTINA PAGEL AND CHRISTIAN A. YATESSCIENCE•22 Oct 2021•Vol 374, Issue 6566•pp. 403-404•DOI: 10.1126/science.abi6602 7,757

Accurate and near real-time data about the trajectory of the COVID-19 pandemic have been crucial in informing mitigation policies. Because choosing the right mitigation policies relies on an accurate assessment of the current state of the local epidemic, the potential ramifications of misinterpreting data are serious. Each data source has inherent biases and pitfalls in interpretation. The more data sources that are interpreted in combination, the easier it is to detect genuine changes in an epidemic. Recently, in many countries, this has involved disentangling the varying impact of rising but heterogeneous vaccination rates, relaxation of mitigations, and the emergence of new variants such as Delta.The exact data collected and their accuracy will vary by country. Typical data common to many countries are numbers of tests, confirmed cases, hospital and intensive care unit (ICU) admissions and occupancy, deaths, and vaccinations (1). Many countries additionally sequence a proportion of new positive tests to identify and track emerging variants. Some countries also now collect and publish data on infections, hospitalizations, and deaths by vaccination status (e.g., Israel and the UK). Stratifying all available data by different demographic factors (e.g., age, location, measures of deprivation, and ethnicity) is crucial for understanding patterns of spread, potential impact of policies, and efficacy of vaccines (age, timing of breakthrough infections, and prevalent variants).It is also necessary to be aware of what data are not being collected. For example, persistent symptoms of COVID-19 (Long Covid) were recognized as a long-term adverse outcome by the autumn of 2020. However, no simple diagnostic test has been associated with the up to 200 different reported symptoms (2). Counting Long Covid relies on a clinical diagnosis, based on a history of having had COVID-19 and a failure to fully recover, with development of some characteristic symptoms and with no obvious alternative cause (3). These features make it very difficult to measure routinely, and so it rarely is. As a result, Long Covid is often neglected in decision-making. Failure to account for the disease load associated with Long Covid may lead to an unnecessary long-term societal health burden.The feedback between different types of outcomes, different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, different mitigation policies (including vaccination), and individual risks (a combination of exposure and clinical risk) is complex and must be factored into both interpretation of data and the development of policy. Using all available data to quantify transmission is crucial to ensuring rapid and effective responses to early phases of renewed exponential growth and to evaluating mitigation measures. Relying too much on a single data source, or without disaggregating data, risks fundamentally misunderstanding the state of the epidemic.The inherent biases and lags in data are particularly important to understand from the point of view of policy-makers. Because of the natural time scales of COVID-19 disease progression (see the figure), policy changes can take several weeks to show up in the data. Purely reactive policy-making is likely to be ineffective. When cases are rising, increases in hospital admissions and deaths will follow. When a new variant is outcompeting existing strains, it is likely to become dominant without action to suppress. The precautionary principle suggests acting early and emphatically. Conversely, when releasing restrictions, governments must wait long enough to assess them before continuing with re-opening.The most up-to-date indicator of the state of the epidemic is typically the number of confirmed cases, as ascertained through testing of both symptomatic individuals and those tested frequently regardless of symptoms. Symptom-based testing is likely to pick up more adults and fewer younger individuals (4). Infections in children are harder to detect: children are more likely to be asymptomatic than adults, are harder to administer tests to (particularly young children), are often exposed to other viruses with similar symptoms, and can present with symptoms that are atypical in adults (e.g., abdominal pain or nausea). Children under 12 are not routinely offered the COVID-19 vaccination, and their mixing in schools provides ongoing opportunities for the virus to circulate, so it will be important for countries to track infections in children as accurately as possible. Other testing biases include accessibility, reporting lags, and the ability to act lawfully upon receiving a positive result. Substantial changes in the number of people seeking tests may further confound case figures (5). Case positivity rates may provide a more accurate reflection of the state of the epidemic (6) but are dependent on the mix of symptomatic and asymptomatic people being tested.SARS-CoV-2 variants have been an important driver of local epidemics in 2021. The four main SARS-CoV-2 variants of concern, to date, are B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta). Some have been more transmissible (Alpha), some have substantial resistance to previous infection or vaccines (Beta), and some have elements of both (Gamma and Delta) (7). Currently, the high transmissibility of Delta combined with some immune evasion has made it the world’s dominant variant. Determining which variants pose a substantial threat is difficult and takes time, particularly when many variants cocirculate. This is especially true for situations in which a dominant variant is declining, and a new one growing. While the declining variant remains dominant, its decrease masks increases in the new variant because case numbers remain unchanged or fall overall. Only when a new variant becomes dominant does its growth become apparent in aggregated case data, by which time it is, by definition, too late to contain its spread. This dynamic has been observed across the world with Delta over the latter half of 2021.With multiple variants circulating, there are, effectively, multiple epidemics occurring in parallel, and they must be tracked separately. This typically requires the availability of sequencing data, which is unfortunately limited in most countries. Sequencing takes time and so is typically a few weeks out of date. These lags, and the uncertainty in sampling, can lead to hesitancy in acting. The rapid path to dominance of the Delta variant in the UK highlights the need for action when a quickly growing variant represents a few percent (or less) of overall cases.Hospital admissions or occupancy data do not suffer the same biases associated with testing behaviors and provide unequivocal evidence of widespread transmission, its geography, and demographics. However, hospital admissions lag infections more than reported cases do, rendering these data less useful for proactive decision-making. Hospital data are also biased toward older people, who are more likely to suffer severe COVID-19, and now, unvaccinated populations. ICU occupancy data show a younger age profile than admissions because younger patients have a better chance of benefitting from the invasive treatment procedures (8).Deaths are the most lagged indicator, typically occurring 3 or more weeks after infection and with an additional lag in registration and reporting. Death data should never be used to inform real-time policy decisions. Instead, death figures can act as an eventual measure of the success of a country’s epidemic strategy and implementation. The age distribution of those who eventually die from COVID-19 is different from other metrics of the epidemic—skewed furthest toward older age groups (9). Those with clinical risk factors (such as immunodeficiency, obesity, or existing lung conditions), high exposure (health care workers and low-income workers), and the unvaccinated are overrepresented in COVID-19 deaths.In countries with high vaccination rates, vaccination has had a substantial impact—reducing COVID-19 cases, hospitalizations, and deaths. However, when looking at the raw numbers in highly vaccinated populations, it can be the case that more fully vaccinated people are dying of COVID-19 than unvaccinated. If these raw statistics are misinterpreted—or worse, deliberately misused—they can damage vaccine confidence. More vaccinated people may die than unvaccinated because such a high proportion of people are vaccinated (10). This does not mean vaccines are not effective at preventing death. Looking at the rates of death in vaccinated and unvaccinated individuals separately within age groups demonstrates that vaccines provide considerable protection against severe disease and death. This example illustrates how important it is to curate and manage the way in which data are presented.

COVID-19 progressionAn approximate timeline from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to various outcomes. When current infections show up in different data sources depends on this timeline. Collecting data for Long Covid, asymptomatic infection, and vaccine history will improve understanding of the pandemic.GRAPHIC: N. CARY/*SCIENCE*

Each country has established its own vaccination priority lists and dosing schedules to best achieve its goals (11, 12). Each of these strategies will manifest differently in the data. Additionally, many countries are using multiple vaccines in tandem and administer them differently for different demographics. Some countries are vaccinating adolescents, and others are not or not offering them the full approved dose. Most vaccines require two doses, spaced between 3 and 12 weeks apart, except for the Johnson & Johnson single-dose vaccine. This matters, particularly as variants spread, because different vaccines have different effectiveness after one and two doses, different timelines to full effectiveness, and different effectiveness against variants (13).Data published on the vaccination delivery itself must thus go beyond the raw numbers of people vaccinated. Vaccine uptake must be reported by whether fully or partially (one-dose in a two-dose regimen) vaccinated and using the whole population as a denominator. It is vital to disaggregate vaccine data by age, gender, and ethnicity as well as location so that it is possible, for example, to understand the impact of deprivation on vaccine coverage or vaccine hesitancy in particular demographics. When interpreting vaccination data, it is important to remember that there is also a lag between delivery and the build-up of immunity.Data on reinfection and post-vaccination (breakthrough) infection are also important to determine the relative benefits of infection-mediated and vaccine-mediated immunity and the length of protection offered. Studies that show those who were immunized earlier were acquiring COVID-19 with higher rates than those vaccinated more recently may suggest waning vaccine protection (14). Such studies have already prompted vaccine booster programs in some countries. However, any study that suggests waning immunity must be extremely careful to ensure that the “early” and “recent” subgroups are properly controlled. Differences in prior exposure, affluence, education level, age, and other demographic factors between these cohorts may be enough to explain the disparities in SARS-CoV-2 infection rates, even in the absence of waning immunity. Waning immunity must also be reported separately for different outcomes; for example, there might be waning in terms of preventing symptomatic infection but far less or none in preventing death (15). Additionally, there are ethical concerns about mass booster programs in high-income countries while many lower-income countries have been unable to procure vaccines.Moving into the vaccination era, reported cases, hospitalizations, and deaths should also be disaggregated by vaccination status (and by which vaccine), which will be easier in countries where national linked datasets exist. Additionally, incorporating Long Covid into routine reporting and policy-making is crucial. Consistent diagnostic criteria and well-controlled studies will be vital to this effort. These elusive data will be of critical importance to navigate our way successfully out of the pandemic.

Acknowledgments

C.P. and C.A.Y. are both members of Independent SAGE: www.independentsage.org.

References and Notes

1M. Roser et al., Our World in Data (2021); https://bit.ly/3kepLgw.GO TO REFERENCE GOOGLE SCHOLAR2H. E. Davis et al., E. Clin. Med.38, 101019 (2021).GO TO REFERENCE GOOGLE SCHOLAR3M. Sivan, S. Taylor, BMJ371, m4938 (2020).GO TO REFERENCE CROSSREF PUBMED GOOGLE SCHOLAR4S. M. Moghadas et al., Proc. Natl. Acad. Sci. U.S.A.117, 17513 (2020).GO TO REFERENCE CROSSREF PUBMED GOOGLE SCHOLAR5J. Wise, BMJ370, m3678 (2020).GO TO REFERENCE CROSSREF PUBMED GOOGLE SCHOLAR6D. Dowdy, G. D’Souza, COVID-19 Testing: Understanding the “Percent Positive” (2020); https://bit.ly/3CeN8wl.GO TO REFERENCE GOOGLE SCHOLAR7C. E. Gómez et al., Vaccines (Basel)9, 243 (2021).CROSSREF PUBMED GOOGLE SCHOLAR8A. B. Docherty et al., BMJ369, 1985 (2020).GO TO REFERENCE CROSSREF PUBMED GOOGLE SCHOLAR9Office for National Statistics, Deaths registered weekly in England and Wales by age and sex: covid-19 (2021); https://bit.ly/3Ci2obS.

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Curation is Uniquely Distinguished by the Historical Exploratory Ties that Bind

Posted in Interviews with Scientific Leaders, Scientist: Career considerations, Translational Science, tagged Andrew Wiles, Archimedes, bias minimization, Content Curation, critical insights, Curation, Curation methodology, distinct from creation, Euclid, global access, Hilbert, Hilbert space, integrated knowledge, Karl Landsteiner, knowledge constructs, Louis Pasteur, medical and biological science, Newton, Nobel Prize, Pythagorean Theorem, Thomas Hunt Morgan on January 1, 2014| Leave a Comment »

Curation is Uniquely Distinguished by the Historical Exploratory Ties that Bind

Author and Curator: Larry H Bernstein, MD, FCAP

The description and definition of curation has been introduced in a Forward to Series A: e-Books on Cardiovascular Diseases, Volume Two, by Dr. Aviva Lev-Ari, PhD, RN, the Founder of Leaders in Pharmaceutical Business Intelligence’s Scientific Journal http://pharmaceuticalintelligence.com, acting as Curator, Co-Curator, and e-Publishing Article Architecture Designer and, chiefly, Editor-in-Chief of a Five e-Series in BioMed,

http://pharmaceuticalintelligence.com/biomed-e-books/

Forward to Volume Two

Volume Two: Cardiovascular Original Research: Cases in Methodology Design for Content Co-Curation

Curation is explained by it being contrasted with the Art of Scientific Creation, both are expored below by examples.

Part 1: The Scientific Creation

I shall try to identify the important features and criteria that contribute to scientific curation of medical, biological, and pharmaceutical research, including structural and functional content from the sciences of anatomy, physiology, physics and chemistry.

The principles that I seek to realized is a foundation in the body of knowledge that precedes the discovery or innovation. Is the discovery essential, but unnoticed because of unlinkings to prior established concepts. This is extremely difficult to cull out, but it has had a recurrent history. It might be easiest to refer to examples in physics, such as, the unique Nobel Prize discovery of pseudo-crystals that has had an impact on materials science. But actually, in the history of mathematics, astronomy, and physics, and later in anatomy and physiology, we have an “audit trail” in writings from the Hellenistic period, interrupted by the dark ages and the Bubonic Plague, and a reawakening in the period preceding and through the enlightenment and reformation. This carried significant risks for great thinkers in a society that changes slowly, and with repeated interruptions throughout all periods by wars. One might say that this has no relevance to curation, but repeatedly, libraries and museums preserved discovery that could be re-examined later. Thus, we can’t discard the brilliance of Hipparchos, whose influence on Ptolemy is known, and who discovered the centrality of the Sun to our universe, even though the extent to which he accepted societal belief in astrology is at best limited. The work of Copernicus later was under great duress, but gave precedence to Galileo and Newton. The Hellenistic period also gave us Euclid and Archimedes, which was critical for the development of mathematics and measurement, and El Gibr’ gave us algebra. In his time, Archimedes found no-one who he could share his ideas with other than Conon, who died too early, but he was later read by Omar Kayyam, Leonardo da Vinci, Galileo and Newton. The Greek diagrams used by Archimedes of Syracuse were a major contribution to cognition and inference. The Archimedes Palimpses, which were given to us as by the priest-scribe, Ioannes Myronas in 1229, is historically a major contribution revealing Archimedes work in the Method. There is the center of gravity of a triangle, and the treatise on Balancing Planes, from which he deduces that if you place two objects on a balance on which the distances are movable from the fulcrum, the distance of the lighter object is five times the distance of the heavier object. The rule is that weights balance when they are reciprocal to their distance. Then there is Fermat’s Last Theorem, unsolved problem for centuries since the seventeenth century.The theorem state that while the square of a whole number can can be broken down into two other squares of whole numbers the same cannot be done for cubes or any higher power. The theorem took seven years to write, with a ynother year to edit.The principle was incorporated into the Pythagorean Theorem, and in 1955 two japanese mathematicians made a far reaching conjecture that paved the way to the solution by Andrew Wiles at Princeton in 1995.

Notably, the great mathematician, Gauss, who published Disquisition on Mathematics in 1801, on number theory at age 24, refused to engage in the solution, but his work in complex analysis, based on earlier work by Euler involving imaginary numbers was crucial to the 20th century understanding.Perhaps another apt example is Einstein’s general theory of relativity, the prediction of gravitational radiation bringing a new attention to the tiny ripples in space-time that has opened our eyes to modern cosmology. Finally, we find that a small piece of our universe is viewed as a chunk of Hilbert space, developing as a nest of interacting probability waves. The waves of Hilbert space are actually the waves Schroedinger derived before we had the tools to observe their behavior.The mathematics of entanglement identifies the high-probability areas of a joint-Hilbert space developed from the interaction having consistent histories. This has led to the description of Schroedinger’s principle, the things that we consider to be real are stable persistent patterns. This gives rise to debate about many worlds.

We leave the seemingly esoteric world of problems in mathematics and theoretic physics and return to the world of biochemistry, molecular biology, genomics, proteomics and allied medical sciences.

The scientific underpinnings of biology and medicine transitioned from a largely observational and descriptive phase in the 19th century with the scientifc leadership of Rudolph Virchow, Louis Pasteur, Robert Koch, John Hunter, Edward Jennings, Walter Reed, Karl Landsteiner, and Thomas Hunt Morgan. Pasteur, Koch, Landsteiner and Morgan were outstanding experimentalists. The latter two were to receive Nobel Prizes that began in 2001. The idea of a more fundamental basis for biological sciences was concerned with studying the chemical structures and processes of biological phenomena that involve the basic units of life, and it developed out of the related fields of biochemistry, genetics, and biophysics. The primary focus became the study of proteins and nucleic acids—i.e., the macromolecules that are essential to life processes. A great impetus was provided by enabling the three-dimensional structure of these macromolecules through such techniques as X-ray diffraction and electron microscopy. In seeking to understand the molecular basis of genetic processes; molecular biologists map the location of genes on specific chromosomes, associate these genes with particular characters of an organism, and use recombinant DNA technology to isolate, sequence, and modify specific genes.

The above is tied to a dominance of Western scientific discovery, as seen in the recipients of the Nobel Prize, but it is only a two dimensional view. Here another type of graphical display would be more informative, and it has been developed. I might consider a separation by type for physics, chemistry and medicine, leaving out the others, and then, in combination. I would bet that there are interactions.

For instance – 2001 – Roentgen, Physics; Pierre and Marie Curie, Physics; E.O. Lawrence, Chemistry, Berkeley Radiation Lab; Max Planck, following on Boltzmann and on Josiah Willard Gibbs (pre-Nobel) work. Then you have radiology and radioisotope chemistry and photosynthesis, Martin Kamen. Of course, modern physiology and metabolism traces back to the work on oxygen, carcon dioxide, and heat, adiabatic systems, and leads to the calorimeter, the Warburg apparatus, which credits Pasteur’s work 60 years earlier. The fruit fly genetics was an impetus for cracking the genetic code, but the impetus for that was both from Gregor Mendel and Charles Darwin, and then the mathematical work of Pearson and of Fischer. The work on the chemical bond by Linus Pauling really opened up a foundation for understanding organic and inorganic reactions based on atomic orbital theory that was essential for pursuit of the double helix. This was so important that it unlocked the structure of polymeric proteins through the disulfide bond, and also metalloprotein complexes (heme, …). Wouldn’t it be incredible to map the Nobel work to seminal work done in the 100 years before the Prize with different colored arrows to show stromg and weaker associations? This is in a strong sense, a method of CURATION (as opposed to creation), that is very important for a fundamental grasp of the growth of and ties in the development of the knowledgebase.

Wouldn’t it be incredible to map the Nobel work to seminal work done in the 100 years before the Prize with different colored arrows to show stromg and weaker associations? This is in a strong sense, a method of CURATION (as opposed to creation), that is very important for a fundamental grasp of the growth of and ties in the development of the knowledge-base.

Such a discussion in depth is the curation that is intended for http://pharmaceuticalintelligence.com/biomed-e-books/series-e-titles-in the strategic-plan-for-2014-1015/2014-milestones-in-physiology-discoveries-in-medicine

Part 2: Scientifc Results – The Art of Curation

Dr. Lev-Ari continued her work, beyond Volume Two, above, on Curation as a Methodology for Critique of the Scientific Frontier and the most effective method for synthesis of scientific milestones in the following selective list of articles:

e-Recognition via Friction-free Collaboration over the Internet: “Open Access to Curation of Scientific Research by Aviva Lev-Ari, PhD, RN

Digital Publishing Promotes Science and Popularizes it by Access to Scientific Discourse by Aviva Lev-Ari, PhD, RN

Synthetic Biology: On Advanced Genome Interpretation for Gene Variants and Pathways: What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging

The Heart: Vasculature Protection – A Concept-based Pharmacological Therapy including THYMOSIN

Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1

The Fatal Self Distraction of the Academic Publishing Industry: The Solution of the Open Access Online Scientific Journals

For a complete list of her Curations, go to

http://pharmaceuticalintelligence.com/?s=Aviva+Lev-Ari%2C+PhD%2C+RN

REFERENCES

1. George Sarton. A History of Science: Hellenistic Science and Culture in the last three centuries B.C. 1959. Harvard University Press. Cambridge, MA, USA.
2. Reviel Netz & William Noel. The Archimedes Codex: How a medieval prayer book is revealing the true genius of antiquity’s greatest scientist. 2007. Da Capo Press.
Perseus Books Group, Philadelphia, PA, USA.
3. Amir D Aczel. Fermat’s last theorem: Unlocking the secret of an ancient methematical problem. Four Walls Eight Windows. 1996. New York, NY, USA.
4. Colin Bruce. Schroedinger’s Rabbits: the many worlds of quantum. 2004. Joseph Henry Press. Washington, DC, USA.
5. Marcia Bartusiak. Einstein’s Unfinished Symphony: listening to the sounds of spac^2 E-time. The Berkley Publishing Group, New York, NY, USA.