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Record W3217285115 · doi:10.4103/2468-8827.330644

Noncommunicable diseases in the age of pandemics

2021· article· en· W3217285115 on OpenAlexaffabout
Arun Chockalingam, Sandhiya Kalyanasundaram

Bibliographic record

VenueInternational Journal of Noncommunicable Diseases · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)GeographyMedicineDiseaseInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

At the beginning of the Corona Virus – SARS-COV-2 (COVID-19) pandemic in 2020, the International Journal of Noncommunicable Diseases brought out a Special issue[1] in which it examined the effect of COVID-19 on individual NCDs and their risk factors. The Special Issue explored and examined the implications of COVID-19 on various NCDs from multiple perspectives. It has now been more than 18 months since the World Health Organization declared COVID-19 a pandemic. During this period, nearly 240 million cases and 5 million deaths attributed to COVID-19 have been recorded globally.[2] In addition to being particularly vulnerable to the virus, people with noncommunicable diseases have also suffered due to lack of access to hospital beds for much needed surgeries and procedures. The impact of COVID-19 on the lives of human beings in every part of the world has been devastating and multi-dimensional. It is a testament to human resilience and ingenuity that the pandemic also motivated governments, private sector, researchers and public health practitioners around the world to find ways and means to mitigate the ill-effects of this tiny virus, to cope with it through public health and preventive measures, and to contain its spread through innovative vaccines. We witnessed the speed at which vaccines have been developed in the race against COVID-19, combined with an unprecedented acceleration to regulatory approval of vaccines and international collaborations to find solutions. Despite all these efforts, the challenge to overcome the pandemic remains, as the virus has undergone multiple mutations, triggering what is referred to as 'waves' with each mutation (ranging from alpha to delta, until now) causing more and more mortality and morbidity. The term “wave” comes from the 1889–1892 influenza outbreak that occurred in multiple phases over several years.[3] Consequences of COVID-19 have been felt in all aspects of human lives ranging from direct impact of the disease on the body, government lockdowns to contain the spread and their subsequent results– economic hardship, human fear and suspicion of fellow human beings, mental depression, helplessness and much more. With an objective to examine the impact of COVID-19, share the innovative technologies being developed to study, combat and overcome it, and make public policy recommendations for governments to implement, Canada India Healthcare Summit (CIHS) 2021 was hosted in Toronto, Canada, on May 20–21, 2021. A brief report of this Summit is provided in the article that follows the Editorial.[4] The CIHS addressed the latest COVID-19 related scientific and technical developments, focusing on four (4) topics: (a) digital technology-artificial intelligence (AI) in particular, (b) biotechnology ranging from food technology to vaccine development, (c) Correlation between NCD and COVID-19, in particular cardiovascular diseases, mental health and post-COVID physical pain (myalgia), and (d) mathematical modeling for prediction using “big data” for policy development, and vaccine inequities. Each of these topics was well debated through participation of scientists from India and Canada over 6-month prior to the Summit in multiple virtual working group meetings and public discussions through open webinars. Four white papers were developed out of these discussions and presented at the Summit to elicit broader consultation and are summarized in this issue. Furthermore, during the Summit, scientific experts and policy makers from Canada, India and the United States examined current evidence and made recommendations for the way forward in the above four aspects. This Special issue is a collection of White papers, original articles, reviews, and perspectives. We consider this as a “Sequel” to the 2020 special issue of IJNCD on COVID-19 and NCDs.[1] A brief background and rationale for considering the four topics is provided below. Digital Health We have seen the adoption of digital technology in healthcare for a major part of the past two decades, accelerating rapidly in the past few years. Electronic medical records (EMRs) were one of the earliest applications developed to digitize paper-based records and processes and help doctors in their decision-making. More recently, considerable research has been conducted in the area of wearable technologies, to measure, monitor, and manage patient's health using the Internet of Things. During the COVID-19 pandemic, the constantly increasing pressure on already limited resources in hospitals and clinics to manage the overwhelming number of patients, has led to adoption and greater dependence on telehealth to provide virtual patient care services. We also see an emergence of healthcare access points such as retail clinics, urgent care centers, digital kiosks, and virtual care providers. The digital system is reliable and accurate and has also improved the operational efficiency, workflow, and ease for patients and doctors. The social isolation imposed by COVID-19 has led to more widespread implementation of virtual diagnosis and treatment. COVID-19 has also led us to focus on digital transformation in the science of medicine. We see the use of digital technologies being used from drug discovery to clinical trials and digital therapeutics. Digital technology is transforming the new therapies and their delivery systems. To maximize the advantage of these new technologies, we need integrated digital healthcare systems where platforms can share the information to support better and quicker decision-making. The information-sharing will help public health and other healthcare professionals respond quickly to emergencies and arrest future problems such as Ebola or COVID-19 or others before they go out of control. These integrated digital health care systems will provide affordable access to better therapeutics and personalized health care for patients, resulting in better capabilities, higher agility and efficiency in decision-making and more satisfactory healthcare experiences for both patients and healthcare providers. These systems will generate a large amount of data that, with the help of AI, identify trends and in help in better decision-making. The next decade will bring in more disruptive health care technologies to reduce costs, empower patients and improve patient experience, telescope time for research and development, forecast and arrest emergence of epidemics using big data and AI. Biotechnology Unlike with digital technology, the healthcare sector has been an early adopter of biotechnology. “Biotechnology” is a composite word made up of biology and technology. The word was first used by Karl Ereky. The study of biotechnology is more than a century old and has been used to develop products in various applications with the help of living organisms. The tools and applications in biotechnology have spanned multiple sectors, such as agricultural, industrial, environmental and healthcare. Biotechnology in healthcare involves research and development on living cells with the objective of developing drugs and other medical solutions. Some of the major biotechnology-based medical advancements include CRISPR, Tissue nanotransfection, Recombinant DNA, Genetic testing, HPV vaccine and Stem cell research. Today, biotechnology is an essential element in fields such as genomics, immunology, diagnostic tests, and various pharmaceutical solutions. The urgency of developing solutions to overcome COVID-19 and eliminate the physical, social, and economic hardships faced by humanity has resulted in innovative biotechnology-based initiatives some of which were covered in the Summit and described in this issue. It can also be credited with greater acceptance of what had previously been controversial areas of research and development. NCD and COVID-19 The IJNCD Special issue 2020, edited by Dr. Jai Prakash Narain[1] introduces the relation between COVID-19 and every one of the chronic noncommunicable diseases and their risk factors. The NCDs by themselves are the biggest cause of death and disability[5] and in the presence of COVID-19 it multiplied in many folds. Data from the past 18 months confirm this and it is expected that additional data gathered in the coming year will yield valuable information and insight into mutual impact on NCD and COVID-19 as well as efforts to mitigate that impact. The access to care of NCD sufferers is another key metric which has been greatly compromised due to COVID-19. Research and development alone cannot provide a solution for this. However, it can ensure the success of a well thought-out social and public health infrastructure. Mathematical Modeling and Big Data Big Data as terminology is quite recent, <30 years old. But no other terminology has captured the imagination of scientists and researchers as much. Application of data for analysis and applications has, however, been around for millennia. The Romans are said to have used data to plan their troop movements. What has changed recently is (1) a logarithmic increase in the amount of data created, gathered, stored and analyzed (2) sustained technology developments both at the academic and industry level to enable processing of big data. Early examples of big data have been in areas of predictive analytics, user behavior analytics and other data analytics methods that exploit the volume of data to generate value from data for observation and decision making. Big data and the ability to analyze it is now seen as panacea to many issues, such as spotting business trends, fighting crime and, pertinent to us, fighting and preventing diseases. Big data have enhanced areas of study such as FinTech, urban planning, business informatics, meteorology, environmental research, genomics, and complex simulations. While the amount of data generated during the COVID-19 was an unfortunate outcome of the duration and global spread of the pandemic, it also has provided researchers and mathematical modeling experts to use it to identify target geographical areas and demographic groups to focus on. Mathematical modeling has been an integral element of government initiatives to fight the spread of COVID-19 and to keep the general public informed and reassured. Data generated from COVID-19 incidences and mortalities also reinforced scientific opinion on the success of vaccines and enabled governments to take firm stance on alternative treatment claims. Vaccine Equity While life-saving vaccines have been produced in a remarkably short period, fast tracked regulatory approval process, and introduced to the market, the benefit unfortunately has been limited to high-, upper-, and middle-income countries only. This leaves a wide inequity between the rich and poor countries.[6] Indeed, in many of the poorer countries the vaccination rate is 1% or less and this is attributed by stakeholders to the lack of intent by the producers of the vaccines as well as by the developed countries. In addition, there are inequities present within population even within the developed countries, due to either faith-based or non-science-based beliefs. Vaccine inequity poses a major ethical dilemma globally, while also delaying the eventual containment of the virus. Science alone cannot address this issue, but it can help in educating those who choose not to get vaccinated, as well as advising planners on the public health reasoning for achieving global vaccine equity. It is hoped that continued research and public health focus on the above topics as they apply to COVID-19 will not only ensure that we get out of the pandemic soon globally, but also that we will be much better prepared for any pandemic that may befall humanity in the future. In concluding, we, the authors, sincerely thank Prof. J. S. Thakur, President and the members of the World NCD Federation for encouraging us to publish the findings of CIHS 2021 through IJNCD. We convey our special thanks to Dr. V. I. Lakshmanan for his vision in conceiving and chairing the Summit and to the four co-organizers: Canada India Foundation, University Health Network– Toronto Rehab Institute, Federation of Indian Chambers of Commerce and Industry and the Consul General of India in Toronto. Any amount of “thank you” is not adequate for the yeomen work done by our efficient editorial assistants and promising healthcare professionals Ms. Arrti Bhasin and Ms. Nikita Thakkar. They both have been meticulous at every step of the way right from pre-Summit to the execution of the Summit and post-Summit preparation of this Special issue. Finally, we thank Mr. Chocko Valliappa of Sona College of technology and Mr. Muthu Murugappan of Valensa International for their continued commitment and support for our initiative. The success of CIHS 2021 is largely because of every member of different committees [Table 1].Table 1: Canada India Healthcare Summit - CommitteesIt has been a privilege to have the opportunity to put together this issue. We hope that readers will benefit from the information and insights provided in the papers that constitute this issue. Feedback from the readers will be greatly appreciated.

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

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

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

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

Opus teacher head0.042
GPT teacher head0.340
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

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

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Citations0
Published2021
Admission routes2
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