The document summarizes discrepancies in COVID-19 case data reported by Public Health England (PHE). PHE's notifications of infectious diseases (NOIDs) data reported only 87 cases for one week compared to 145,129 cases from another PHE source. Three additional data sources - a symptom tracker, NHS triage calls, and lateral flow/antibody testing - show a September peak in cases that contradicts continually rising PCR positive cases. The document argues PHE should only diagnose symptomatic cases and re-evaluate PCR testing quality.
Nombre de décès estimés du fait du vaccin aux USASociété Tripalio
Etude statistique tentant d'approcher le nombre de décès dus au vaccin contre le COVID aux USA. Cette étude porte sur les chiffres officiels jusqu'au 28 août 2021.
Lessons from COVID-19: How Are Data Science and AI Changing Future Biomedical...Jake Chen
: COVID-19 has profoundly impacted all our lives. Not all such impacts in science are negative. For example, how we adapt to online learning, remote mentorship, and online teamwork may become new “norms” of future scientific collaborations, breaking down institutional boundaries to communication. The COVID-19 pandemic has united the scientific community more than ever, through more than 3600 clinical trials, 60,000 peer-reviewed publications, 80,000 SARS-CoV-2 genome sequences, 100,000 COVID-19 open software tools, and a global community of scientists, with which all of us are working hard to find epidemiological patterns, diagnosis, therapeutics, and vaccines in a “War Against COVID-19”. In this talk, I will define and characterize data-driven medicine primarily through my personal journey in the past ten months, having witnessed the rapid “weaponizing of data science tools” in our community’s fight against COVID-19 (including ours, at http://covid19.ubrite.org/). I will review up-to-date COVID-19 literature, especially those related to how biomedical informatics, data science, and artificial intelligence have been applied in accelerating COVID-19 breakthrough discoveries, from basic research to clinical practice. I will end by sharing my thoughts on how the future of medicine in cancer and other translational areas can benefit from the proactive incorporation of new “data science engines.”
Nombre de décès estimés du fait du vaccin aux USASociété Tripalio
Etude statistique tentant d'approcher le nombre de décès dus au vaccin contre le COVID aux USA. Cette étude porte sur les chiffres officiels jusqu'au 28 août 2021.
Lessons from COVID-19: How Are Data Science and AI Changing Future Biomedical...Jake Chen
: COVID-19 has profoundly impacted all our lives. Not all such impacts in science are negative. For example, how we adapt to online learning, remote mentorship, and online teamwork may become new “norms” of future scientific collaborations, breaking down institutional boundaries to communication. The COVID-19 pandemic has united the scientific community more than ever, through more than 3600 clinical trials, 60,000 peer-reviewed publications, 80,000 SARS-CoV-2 genome sequences, 100,000 COVID-19 open software tools, and a global community of scientists, with which all of us are working hard to find epidemiological patterns, diagnosis, therapeutics, and vaccines in a “War Against COVID-19”. In this talk, I will define and characterize data-driven medicine primarily through my personal journey in the past ten months, having witnessed the rapid “weaponizing of data science tools” in our community’s fight against COVID-19 (including ours, at http://covid19.ubrite.org/). I will review up-to-date COVID-19 literature, especially those related to how biomedical informatics, data science, and artificial intelligence have been applied in accelerating COVID-19 breakthrough discoveries, from basic research to clinical practice. I will end by sharing my thoughts on how the future of medicine in cancer and other translational areas can benefit from the proactive incorporation of new “data science engines.”
Selon une étude, publiée en décembre 2020, la population de la ville de Manaus (Brésil) aurait atteint l’immunité collective. Laurent AVENTIN, PhD – Consultant en santé publique, fait le point pour Le Courrier des Stratèges…
The usability of STAMP in drug development Arete-Zoe, LLC
Arete-Zoe in cooperation with Stuttgart University
Study authors: Veronika Valdova, Ronald L Sheckler, Asim Abdulkhaleq and Stefan Wagner (Jonathan M Fishbein)
Presentation of synopsis: Veronika Valdova
Presented at STAMP team meeting, PSCI, ACRES on February 26, 2016
PowerPoint Presentation from May 2011 Personal Validation and Entity Resolution Conference. Presenters: T. Lamagni, N. Potz, D. Powell, N. Hinton, A. Grant, E. Sheridan, R. Pebody. Presentation Title: Application of probabilistic linkage methods to join infectious disease surveillance records to death registrations
The Gibraltar COVID-19 Cohort: Determining the True Incidence and Severity Ra...asclepiuspdfs
COVID-19 is a new infectious disease with an unclear incidence and an unknown rate of progression to severe disease. The Gibraltar COVID-19 Cohort utilises two distinct cohorts - a clinical cohort and a random population based cohort -, to provide an accurate assessment of case severity rate. Design: Retrospective analysis of a SARS-CoV2 RT-PCR point prevalence study and a RT-PCR confirmed positive clinical case cohort to calculate case severity rates. Settings and Participants: Over a three day period nasopharyngeal swabs were sampled from a randomly selected 1.2% of the population of Gibraltar and then analysed via RT-PCR to determine the background incidence of COVID-19 infection. The results were then analysed and compared to the clinical case cohort. The rate of progression to severe COVID-19 disease in those with COVID-19 infection was then calculated.
Sanjay Mehta, MD
Associate Professor of Medicine
Division of Infectious Diseases & Global Public Health
Department of Medicine
University of California, San Diego
The value of real-world evidence for clinicians and clinical researchers in t...Arete-Zoe, LLC
In the midst of a rapidly spreading global pandemic, real-world evidence can offer invaluable insight into the most promising treatments, risk factors, and not only predict but suggest how to improve outcomes. Despite overwhelming news coverage, significant knowledge gaps regarding COVID-19 persist. The current uncertainties regarding incidence and the case fatality rate can only be addressed by widespread testing. But the paucity of testing, and diversity of approaches implemented in different countries, particularly among the general asymptomatic public, perpetuates a lack of understanding about spread and infectivity. The essential indicators that would describe the pandemic more accurately can be obtained using real-world data (RWD). To that purpose, we designed a data collection tool to collect data from hospitals that treat COVID-19 patients. The captured data will enhance our understanding of the COVID-19 pandemic, identify risk factors relevant for triage, relate to other similar seasonal infections and gain insight into the safety and efficacy of experimental and off-label therapies. Knowledge derived from a focused data collection effort will enable clinicians to adjust rapidly clinical protocols and discontinue interventions that turn out to be ineffective or harmful. By deploying our elegantly designed survey to capture routine clinical indicators, we avoid placing an additional burden on practitioners. Systematically generating real-world evidence can decrease the time to insight compared to randomized clinical trials, improving the odds for patients in rapidly changing conditions.
Selon une étude, publiée en décembre 2020, la population de la ville de Manaus (Brésil) aurait atteint l’immunité collective. Laurent AVENTIN, PhD – Consultant en santé publique, fait le point pour Le Courrier des Stratèges…
The usability of STAMP in drug development Arete-Zoe, LLC
Arete-Zoe in cooperation with Stuttgart University
Study authors: Veronika Valdova, Ronald L Sheckler, Asim Abdulkhaleq and Stefan Wagner (Jonathan M Fishbein)
Presentation of synopsis: Veronika Valdova
Presented at STAMP team meeting, PSCI, ACRES on February 26, 2016
PowerPoint Presentation from May 2011 Personal Validation and Entity Resolution Conference. Presenters: T. Lamagni, N. Potz, D. Powell, N. Hinton, A. Grant, E. Sheridan, R. Pebody. Presentation Title: Application of probabilistic linkage methods to join infectious disease surveillance records to death registrations
The Gibraltar COVID-19 Cohort: Determining the True Incidence and Severity Ra...asclepiuspdfs
COVID-19 is a new infectious disease with an unclear incidence and an unknown rate of progression to severe disease. The Gibraltar COVID-19 Cohort utilises two distinct cohorts - a clinical cohort and a random population based cohort -, to provide an accurate assessment of case severity rate. Design: Retrospective analysis of a SARS-CoV2 RT-PCR point prevalence study and a RT-PCR confirmed positive clinical case cohort to calculate case severity rates. Settings and Participants: Over a three day period nasopharyngeal swabs were sampled from a randomly selected 1.2% of the population of Gibraltar and then analysed via RT-PCR to determine the background incidence of COVID-19 infection. The results were then analysed and compared to the clinical case cohort. The rate of progression to severe COVID-19 disease in those with COVID-19 infection was then calculated.
Sanjay Mehta, MD
Associate Professor of Medicine
Division of Infectious Diseases & Global Public Health
Department of Medicine
University of California, San Diego
The value of real-world evidence for clinicians and clinical researchers in t...Arete-Zoe, LLC
In the midst of a rapidly spreading global pandemic, real-world evidence can offer invaluable insight into the most promising treatments, risk factors, and not only predict but suggest how to improve outcomes. Despite overwhelming news coverage, significant knowledge gaps regarding COVID-19 persist. The current uncertainties regarding incidence and the case fatality rate can only be addressed by widespread testing. But the paucity of testing, and diversity of approaches implemented in different countries, particularly among the general asymptomatic public, perpetuates a lack of understanding about spread and infectivity. The essential indicators that would describe the pandemic more accurately can be obtained using real-world data (RWD). To that purpose, we designed a data collection tool to collect data from hospitals that treat COVID-19 patients. The captured data will enhance our understanding of the COVID-19 pandemic, identify risk factors relevant for triage, relate to other similar seasonal infections and gain insight into the safety and efficacy of experimental and off-label therapies. Knowledge derived from a focused data collection effort will enable clinicians to adjust rapidly clinical protocols and discontinue interventions that turn out to be ineffective or harmful. By deploying our elegantly designed survey to capture routine clinical indicators, we avoid placing an additional burden on practitioners. Systematically generating real-world evidence can decrease the time to insight compared to randomized clinical trials, improving the odds for patients in rapidly changing conditions.
Chapter 7 Discussion- Hundreds of hospitals- clinics- and health depar.pdfaonetelecompune
Chapter 7 Discussion. Hundreds of hospitals, clinics, and health departments automatically
report certain symptoms and diagnoses to the government each day. This practice of
biosurveillance helps officials track the spread of flu, detect outbreaks, and watch for odd
symptoms that might signal a brand new disease or bioterrorism. Although information is
reported daily, doctors rarely know what their colleagues nearby are diagnosing. Instead they
often call the health department to ask if anyone has heard of any outbreak of certain cases.
Work is being done to create a mechanism to track diseases before they become outbreaks (CNS
News 2011). Researchers are working on technology that will link local biosurveillance to
electronic health records, and even mobile applications. Providing data on the amount of disease
or infection that is spreading locally can improve diagnosis and treatment methods. Federal
health officials are working to create an easy-to-use web tool that will allow doctors and
consumers to search for local surveillance information. Websites and mobile applications such as
HealthMap, CDC Influenza, and Flu Near You are tools used to track cases in specific areas.
Explore the Web sites (links in the Module) for the CDC, the California Department of Health
Division of Communicable Disease Control, CalREDIE, and HealthMap. HealthMap has a video
in the About section explaining how they gather data and how it can be used . As you explore
these sites look for information on current disease outbreaks. Through the disease reporting in
various databases you can see that information is becoming more widely available to healthcare
providers and the public. Coronavirus (COVID-19) world-wide is being monitored through the
World Health Organization. Links to an external site.US cases are tracked in local and state
databases and nationally by the CDCLinks to an external site. and Johns Hopkins Corona Virus
Resource CenterLinks to an external site. (global and US tracking) We are entering the time of
year, there is always a high incidence of influenza and the CDC reports weekly tracking of
positive testing for influenza. Influenza Surveillance Report.Links to an external site. The 2022-
2023 flu season is just ending and tracking for the 2023-2024 begins. The California Department
of Public Health recently reported that sexually transmitted diseases reached a new high in
California. Link to the article.Links to an external site. Specified diseases and conditions are
mandated by state laws and regulations to be reported by healthcare providers and laboratories to
the local health officer - reportable diseases in California. Discussion Instructions: In the
discussion thread describe information you found on current outbreaks that are occurring
nationally and/or in California. How does technology and the availability of secondary data
sources help healthcare providers in treating patients? In your post, provide at least one reason
why technology is.
As of the end of February, US COVID-19 cases have increased by 1.69 million (roughly 6%), indicating a decline in the rate of new cases across the U.S.
Powepoint On Epidemiological INDICES OF TB
Suitable For Community Medicine Students - KUHS
KERALA MEDICAL BOARD
Prepared By A Student from
Mount Zion Medical College , Chayalode Adoor
How a U.S. COVID-19 Data Registry Fuels Global ResearchHealth Catalyst
In addition to driving COVID-19 understanding within the United States, a national disease registry is informing research beyond U.S. borders. Clinicians with the Singapore Ministry of Healthcare Office for Healthcare Transformation (MOHT) have used Health Catalyst Touchstone® COVID-19 data to develop a machine learning tool that helps predict the likelihood of COVID-19 mortality. With this national data set that leverages deep aggregated EHR data, the MOHT accessed the research-grade data it needed to build a machine-learning algorithm that predicts risk of death from COVID-19. The registry-informed prediction model was accurate enough to stand up to comparisons in the published literature and promises to help inform vaccine research and, ultimately, allocation of vaccines within populations.
• Much is still unknown regarding the markers of disease and recovery process for SARS-CoV-2, including if and what immunity arises and which tests or markers can be useful in assessing immunity status
• A multi-phased plan is required to reopen the economy post-COVID-19, with significantly daily testing capacity (millions) required at all stages
o Challenges with scientific validation, regulatory, manufacturing, and ongoing logistics must be overcome to successfully ramp up testing capacities in the US
o Hundreds of molecular and serology tests are now available, but many have limited accuracy (high false positive/negative rates) due to the rapid development and lack of validation of these tests
• In this edition of Demystifying COVID-19 Testing, we highlight what is required now and in the future to move to a “new normal” and why it is challenging to get this testing up and running at volumes needed in the US
COVID-19 (coronavirus disease 2019) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), a strain of coronavirus. The first cases were seen in Wuhan, China in December 2019 before spreading globally. The current outbreak was recognized as a pandemic on 11 March 2020.
The non-specific imaging findings are most commonly of atypical or organizing pneumonia, often with a bilateral, peripheral, and basal predominant distribution. No effective treatment or vaccine exists currently (March 2020).
Epidemiology of Tuberculosis (TB) in Albania 1998-2009iosrphr_editor
Abstract : In Albania, many people erroneously think that tuberculosis (TB) is a disease of the past-an illness
that no longer constitutes a public health threat. Surveillance is an integral part of tuberculosis (TB) control.
Albania has a highTB notification rate and there are doubts about underreporting. The evolution of the
incidence of tuberculosis is presented, together with more detailed figures over the period 1998-2009. These
figures were obtained by the monthly forms (called 14/Sh) compared with the individual notification data.
Objective: To examine the distribution and sources of increased tuberculosis (TB) morbidity and reporting
system deficiencies in the Albania from 1998 through 2009. Metodology: The study is descriptive one conductet
during the period 1998-2009. The statistical analysis is based on data reported from regional level (regional
epidemiological departments) to the central level (Public Health Institute). Results: The main findings were:
discordance between the collected data (individual form) and reported data (monthly form); tuberculosis
incidence rate shows little oscillations which ranges from 6.67 to 9.2 cases/100.000 population; 50% of the
regions show a lack of information on the confirmation of diagnosis and laboratory examination type used for
confirmation. Conclusion: TB disease in high-risk populations where it is difficult to detect, diagnose, and treat;
limitations of current control measures and the need for new tests and treatments, including an effective
vaccine; improving information system, regulation of individual form and personnel training.
Similar to The PHE data that goes against the narrative (20)
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfJim Jacob Roy
Cardiac conduction defects can occur due to various causes.
Atrioventricular conduction blocks ( AV blocks ) are classified into 3 types.
This document describes the acute management of AV block.
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
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- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
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Basavarajeeyam is an important text for ayurvedic physician belonging to andhra pradehs. It is a popular compendium in various parts of our country as well as in andhra pradesh. The content of the text was presented in sanskrit and telugu language (Bilingual). One of the most famous book in ayurvedic pharmaceutics and therapeutics. This book contains 25 chapters called as prakaranas. Many rasaoushadis were explained, pioneer of dhatu druti, nadi pareeksha, mutra pareeksha etc. Belongs to the period of 15-16 century. New diseases like upadamsha, phiranga rogas are explained.
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
The PHE data that goes against the narrative
1. The PHE data that goes
against the narrative -
Hunting down
symptomatic COVID-19
Aleks Nowak and
Dr Clare Craig,
with assistance from
Joel Smalley and
Dr Jonathan Engler
DECEMBER 2020
Public Health England’s (PHE) notifications
of infectious diseases (NOIDs) data had only
87 COVID cases listed for the week
beginning 9th November compared with
145,129 cases reported on the government
dashboard using another PHE data source.
This is a gargantuan discrepancy and
requires further investigation.
COVID-19 became a notifiable disease in
March this year. Since then there has been
a statutory requirement that any
Registered Medical Practitioner having
“reasonable grounds for suspecting” that
their patient has COVID-19, has to notify
their local council or Health Protection
Team. The legal requirement is to notify
prior to any confirmatory analysis (e.g. PCR
testing). PHE collects and aggregates this
data, publishing it in the notifiable disease
weekly reports.
The crucially significant aspect of the
NOIDs data is that it is a measure of actual
disease, which by definition requires
symptoms. The bulk of data offered by the
government dashboard in contrast reflects
positive PCR test results with no reference
to symptoms. A disease requires
symptomatic diagnosis which may be
confirmed by testing for causative agents.
The disease here being COVID-19 and the
causative agent being the virus
SARS-COV-2. A positive causative agent test
alone does not determine disease.
I totalled the COVID-19 notifiable disease
reports for COVID-19 since the start of the
year; 17099 up to 15 November 2020 (across
England and Wales). Dumbfounded and
unable to form a thought, after forty
minutes pacing the room, I reached out to
Abir Ballan and Nick Hudson at
PanData.org and they connected me with
Dr Clare Craig to make sense of the
notifiable disease dataset.
2. How can this vast numerical discrepancy
be explained?
Doctors know they have a legal
requirement to report certain specified
diseases and have to do so for a large
number of notifiable diseases. For some
diseases, e.g. tuberculosis, the patient will
have a number of interactions with doctors
on the frontline, doctors making the
diagnosis in the laboratory and TB nurses,
each of whom may do the required
reporting to the public health authorities. In
this way a safety net is built in that is likely
to ensure that all or nearly all cases are
notified.
Some possible explanations for the now
number of notified COVID-19 cases might
be:
● Perhaps doctors treating COVID-19
patients have been run ragged and
it is not reasonable to expect them
to find the time for such
administrative tasks?
● Could it be that the doctors caring
for patients with COVID-19 thought
that someone else would do the
reporting?
● Could it be that as PHE were
responsible for the testing they felt
there was no need to notify them?
All three may be the case but, even if we
assume the NOIDs data represents only a
proportion of actual cases of COVID-19
disease, as opposed to cases of a positive
detection of SARS-COV-2, there are still
some noteworthy features of this data.
There were two peaks of notified COVID in
England. The first peak occurred in May and
the second peak began at the beginning of
September, reached a maximum at the
beginning of October and has returned to
the summer baseline since 17 October
(Figure 1).
The number of NOIDs cases are shown against
the number of positive PCR test results below,
and in order to better observe the relationship
between the trends observed we have included a
further graph in which the 2 measures are
rescaled.
Figure 1 Notified COVID cases (orange) vs
PCR positive COVID cases (grey). Top graph
on same scale second graph scaled to
show trends.
PANDA ARTICLES | pandata.org | The PHE data that goes against the narrative
3. Viewing the same data as a percentage of
cases reported demonstrates that what
doctors were notifying as symptomatic
COVID via NOIDs became an insignificant
proportion of the total PCR positive COVID
cases in mid-October (Figure 2).
Figure 2 Percentage of PCR positive COVID
cases that were notified to PHE via NOIDs
The significance of a September rise in
notified cases that returned to normal by
October is that other data shows a similar
pattern. The Zoe App symptom tracker has
a large number of nationwide participants
who enter their symptoms and test data to
track COVID symptomatology. This data
also showed a September rise and
mid-September peak before returning to a
previous baseline (figure 3).
Data from NHS triage shows the numbers
of people phoning 111 or using NHS online
which the system categorise as “COVID like”
(figure 4). These two data sources also
show a mid-September spike before
returning to a baseline above the summer
baseline.
Figure 3 Contains two charts, the first plots
ZoeApp symptom tracker data showing a
mid-September peak in symptoms in the
community which then returns to baseline
while the second chart shows the positive
test results continue to climb while
symptoms decline. Graph from
@timspector.
PANDA ARTICLES | pandata.org | The PHE data that goes against the narrative
4.
Figure 4 Solid coloured bars show daily
numbers of patients triaged by NHS 111 and
categorised as COVID like (by age) with a
peak on 15th September. The red line shows
the weekly ‘cases’ defined by a single
positive PCR test result. Scales are different
but demonstrate trends. Graph by
@realjoelsmalley.
There are therefore three datasets all
showing a second wave that begins in
September, peaks two weeks later and
returns to baseline by the end of
September:
1. PHE Notifiable Infectious Disease
2. Community symptom tracking
3. NHS triage classification of patients
All three datasets concur but contradict the
PCR positive test results.
There are two other diagnostic tests for
COVID:
1. Lateral flow tests which test for viral
proteins that form part of the viral
particles themselves
2. Antibody testing which confirm
infection two to five weeks
afterwards
Results of lateral flow testing in Liverpool
and Merthyr Tydfil show a consistent
positive rate of <0.8%. This is higher than
the expected false positive rate calculated
with clear cut positive and negative cases
but it is often the case that the false
positive rate is higher when testing with
real world ambiguity. It is striking that the
positive rate for this test is the same over
time and in different places. Lateral flow
tests will not diagnose every case. In fact,
20% will be missed which is the same false
negative rate as seen with most PCR
testing. This is insufficient to account for
the discrepancy between ONS PCR testing
and lateral flow testing of the population at
random. The ONS predicted 2.3% of
Liverpool had COVID on 11th November but
lateral flow testing found only a third of
that - 0.7%. Even if 20% of cases had been
missed by lateral flow tests, that is not
enough to bridge the gap.
Antibody testing of the population has
failed to show a rise in levels despite plenty
of time since the rise in cases.
PANDA ARTICLES | pandata.org | The PHE data that goes against the narrative
5. Figures from Public Health England
Weekly national Influenza and
COVID19 surveillance report
Again two sources of data, lateral flow
testing and antibody testing concur and
contradict results from PCR testing.
Could it be that reports of Notifiable
Infectious Diseases - being filtered by the
need for symptoms to gain the attention of
GPs - are actually a more representative
measure, at least in terms of trends, of “real”
COVID-19 than PCR testing?
It cannot have gone unnoticed by PHE that
this notifiable disease data is very divergent
from published case data. The Government
must urgently review their processes:
1. Only diagnose disease in
symptomatic patients
2. Hospital diagnosis should be
based on alternative bedside
testing for rapid and reliable
results (E.g. Lateral flow tests)
3. PCR testing must be halted
until the quality of the results
has been properly audited
PANDA ARTICLES | pandata.org | The PHE data that goes against the narrative
6. ABOUT THE AUTHORS
Aleks Nowak is a Blockchain Technology
Entrepreneur. Twitter: @an648
Dr Clare Craig has been a pathologist since
2001 for the NHS in the UK and more recently
as the day to day pathology lead for the cancer
arm of the 100,000 Genomes Project and
working for an AI startup in cancer diagnostics.
Twitter: @ClareCraigPath
Joel Smalley is a self-taught empiricist with an
MBA from University of Toronto. Data science,
econometrics, quantitative analysis. Early
career trading equity and credit derivatives
then quant, specialising in time series and
stochastic analysis. Twitter: @RealJoeSmalley
Dr Jonathan Engler is qualified in medicine
and law, but has spent most of his career in
the pharma industry. He founded a company
using tech to coordinate clinical trials, and
after selling it, currently runs a small biotech
doing reasonably clever things with cancer
stem-cells. Twitter: @jengleruk
REFERENCES
1. https://www.gov.uk/government/pu
blications/notifiable-diseases-weekl
y-reports-for-2020
2. https://coronavirus.data.gov.uk/deta
ils/cases
3. https://assets.publishing.service.gov
.uk/government/uploads/system/up
loads/attachment_data/file/942969/
Weekly_Flu_and_COVID-19_report_
w50_FINAL.PDF
Photo by Scott Graham on Unsplash
PANDA ARTICLES | pandata.org | The PHE data that goes against the narrative