1. Data files for ``Making Chaos Out Of Covid-19 Testing" - Figshare
1 dec 2023 · It was created to model the huge data set generated for the Covid-19 pandemic by testing. The chaos generation mechanism is due to Shilnikov's ...
Mathematical models for infectious diseases in epidemiology are not known to be chaotic. This is the first time that chaos is found in such a model. It was created to model the huge data set generated for the Covid-19 pandemic by testing. The chaos generation mechanism is due to Shilnikov's saddle-focus homoclinic orbit. The data set contains all Matlab mfiles used to generate the simulation results of the manuscript ``Making Chaos Out Of Covid-19 Testing" by B. Deng and CY. Yang. Just run `Run\_Plot\_*' on Matlab to produce all figures of the paper.
2. Chaos theory applied to the outbreak of COVID-19: an ancillary approach ...
Data of the COVID-19 epidemics in China, Japan, South Korea and Italy were used to build up deterministic models without strong assumptions.
While predicting the course of an epidemic is difficult, predicting the course of a pandemic from an emerging virus is even more so. The validity of most predictive models relies on numerous parameters, involving biological and social ...
3. The Chaotic Behavior of the Spread of Infection During the COVID-19 ...
The results show that the behavior of the COVID-19 pandemic was chaotic in 55% of the investigated countries.
In December 2019, China announced the breakout of a new virus identified as coronavirus SARS-CoV-2 (COVID-19), which soon grew exponentially and resulted in a global pandemic. Despite strict actions to mitigate the spread of the virus in various ...
4. [PDF] Understanding chaos in COVID-19 and its relationship to stringency ...
8 jun 2022 · We supplemented the findings of Jones and Strigul (2020) and described the chaotic behavior of COVID-19 using state space plots which depicted ...
5. Chaos and Control of COVID-19 Dynamical System
Many dynamical systems have been proposed to understand the spreading behaviour of the disease. This paper investigates the chaos in the outbreak of COVID-19 ...
Chaos, which is found in many dynamical systems, due to the presence of chaos, systems behave erratically. Due to its erratic behaviour, the chaotic behaviour of the system needs to be controlled. Severe acute respiratory syndrome Coronavirus 2 (Covid-19), which has spread all over the world as a pandemic. Many dynamical systems have been proposed to understand the spreading behaviour of the disease. This paper investigates the chaos in the outbreak of COVID-19 via an epidemic model. Chaos is observed in the proposed SIR model. The controller is designed based on the fractional-order Routh Hurwitz criteria for fractional-order derivatives. The chaotic behaviour of the model is controlled by feedback control techniques, and the stability of the system is discussed.
6. Covid-19 : Using chaos theory to predict the course of the epidemic
20 mei 2020 · Covid-19 : Using chaos theory to predict the course of the epidemic. How can we predict the course of an epidemic when data are in short supply?
How can we predict the course of an epidemic when data are in short supply? To answer that question, a team of scientists has developed an approach based on chaos theory. The results bear out field data, and the approach is due to be rolled out in Africa and also used for other diseases
7. Covid Chaos | 9789811264573 | Robert J Sherertz | Boeken - Bol
... documents making recommendations for reducing infections at the national level, and have global experience managing international infectious diseases.The ...
Covid Chaos (Paperback). COVID Chaos is a book about the 2019 SARS-CoV-2 Pandemic that was written real time, spanning the time from March 31, 2020...
8. Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data
Chaos Theory and Applications | Volume: 6 Issue: 1.
Chaos Theory and Applications | Volume: 6 Issue: 1
9. The scientific chaos phase of the great pandemic: A longitudinal analysis ...
Early stages of catastrophes like COVID-19 are often led by chaos and panic. ... Data Availability: All relevant data are within the paper and its Supporting ...
Background Early stages of catastrophes like COVID-19 are often led by chaos and panic. To characterize the initial chaos phase of clinical research in such situations, we analyzed the first surge of more than 1000 clinical trials about the new disease at baseline and after two years follow-up. Our 3 main objectives were: (1) Assessment of spatial and temporal evolution of clinical research of COVID-19 across the globe, (2) Assessment of transparency and quality—trial registration, (3) Assessment of research waste and redundancies. Methods By entering the keyword “COVID-19” we screened the International Clinical Trials Registry Platform of the WHO and downloaded the search output when our goal of 1000 trials was reached on the 1st of April 2020. Additionally, we verified the integrity of the downloaded data from the meta registry by comparing the data with each individual registration record on their source register. Also, we conducted a follow-up after two years to track their progress. Results (1) The spatial evolution followed the geographical spread of the disease as expected, however, the temporal development suggested that panic was the main driver for clinical research activities. (2) Trial registrations and registers showed a huge lack of transparency by allowing retrospective registrations and not keeping their registration records up to date. Quality of trial registration seems to have improved over the last decade, yet crucial information still was missing. (3)...
10. Chaos, Percolation and the Coronavirus Spread: a two-step ...
8 jul 2020 · Without the quarantine, the casualties would have been more than 50,000, hundred days after the start of the pandemic. The data from the 50 US ...
We discuss a two-step model for the rise and decay of a new coronavirus (Severe Acute Respiratory Syndrome-CoV-2) first reported in December 2019, COVID-19. The first stage is well described by the same equation for turbulent flows, population growth and chaotic maps: a small number of infected d grows exponentially to a saturation value d∞. The typical growth λ time (aggressive spreading of the virus) is given by ![Graphic][1], where λ is the Lyapunov exponent.!After a time tcrit determined by social distancing and/or other measures, the spread decreases exponentially as for nuclear decays and non-chaotic maps. Some countries, like China, S. Korea and Italy are in this second stage while others including the USA are near the end of the growth stage. The model predicts 15,000 (±2,250) casualties for the Lombardy region (Italy) at the end of the spreading around May 10,2020. Without the quarantine, the casualties would have been more than 50,000, hundred days after the start of the pandemic. The data from the 50 US states are of very poor quality because of an extremely late and confused response to the pandemic, resulting unfortunately in a large number of casualties, more than 70,000 on May 6, 2020. S. Korea, notwithstanding the high population density (511/km2) and the closeness to China, responded best to the pandemic with 255 deceased as of May 6,2020. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement no exte...
11. At the edge of chaos: a prospective multiple case study in Australian ...
COVID-19 in Victoria during 2020. Data Collection Timeline. Data management. All digital data were stored on a secure server only accessible by JA, RL ...
Objectives The rapid onset and progressive course of the COVID-19 pandemic challenged primary care practices to generate rapid solutions to unique circumstances, creating a natural experiment of effectiveness, resilience, financial stability and governance across primary care models. We aimed to characterise how practices in Melbourne, Australia modified clinical and organisational routines in response to the pandemic in 2020–2021 and identify factors that influenced these changes. Design Prospective, qualitative, participatory case study design using constant comparative data analysis, conducted between April 2020 and February 2021. Participant general practitioner (GP) investigators were involved in study design, recruitment of other participants, data collection and analysis. Data analysis included investigator diaries, structured practice observation, documents and interviews. Setting The cases were six Melbourne practices of varying size and organisational model. Participants GP investigators approached potential participants. Practice healthcare workers were interviewed by social scientists on three occasions, and provided feedback on presentations of preliminary findings. Results We conducted 58 interviews with 26 practice healthcare workers including practice owners, practice managers, GPs, receptionists and nurses; and six interviews with GP investigators. Data saturation was achieved within each practice and across the sample. The pandemic generated changes to t...
12. Covert coronavirus, chaos prize and the cost of contact-tracing - Nature
25 mrt 2020 · A team of researchers in China and the United States developed a model using clinical data from 26,000 laboratory-confirmed cases reported to ...
The latest science news, in brief. The latest science news, in brief.
13. Coronavirus, statistical chaos and the news: preliminary reflections from ...
Data and statistics have been a staple of modern society since at least the latter half of the 20th century, but have never taken such a central place in ...
A Joint Symposium of Bournemouth University, Royal Statistical Society and ABSW
14. Anticipated Mass KIID/KID Re-Generation in Mid-2025
14 aug 2024 · Unwinding of COVID Chaos: Anticipated Mass KIID/KID Re-Generation in Mid-2025 ... data period, was notably affected by this volatility.
On September 25, 2024, the Securities and Exchange Commission (SEC) announced settled charges against 23 entities and individuals for failing to timely report their holdings and transactions in public company stocks. This enforcement action, focused on Schedules 13D, 13G, and Forms 3, 4, and 5, underscores the SEC's commitment to enforcing shareholder disclosure rules and maintaining transparency in financial markets. Among the entities penalised are some of the largest and most recognisable names in the corporate world, including Alphabet and Goldman Sachs. The total fines levied amount to more than $3.8 million.
15. IRU waarschuwt voor chaos door Covid maatregelen - BIGtruck
,,De voorziening van levensmiddelen, medicijnen en de toelevering van bedrijven in de hele EU lopen gevaar door de stagnaties en filevorming aan de grenzen''.
IRU waarschuwt voor chaos door Covid maatregelen
16. Order from chaos - Scripps Research Magazine
As scientists and the public struggle with COVID-20 information overload, a Scripps Research team creates an online haven where data is organized, findable and ...
As scientists and the public struggle with COVID-20 information overload, a Scripps Research team creates an online haven where data is organized, findable and usable. The volume and speed of COVID-19 discovery around the world is nothing short of astounding. Genetic sequences of coronavirus samples are posted daily to research websites, while thousands of new […]
17. Illness stories of hospitalised COVID-19 patients
Chaos was more prevalent among the hospitalisation stories and restitution more among the recovery stories. The quest story type occurred in 6% of the data. The ...
Objective: This study aimed to explore the lived experiences of former hospitalised COVID-19 patients and how they narrate the experiences of their hospitalisation and post-hospitalisation (recovery) period, six and twelve months after hospital dismission. By attaining a better understanding of these experiences, future healthcare services that treat COVID-19 patients may be improved. Method: The sample (N=143) was extracted from the patient population of three Dutch hospitals. As part of a larger cohort study, two open-ended questions were added to inquire about patients’ experiences. For the narrative analysis, Arthur Frank’s story typologies (chaos, restitution and quest) were used to construct a coding scheme containing substory types (e.g. chaos hospitalisation, restitution achieved, quest gratitude). Results: The hospitalisation and recovery experiences of former COVID-19 patients contain all three of Frank’s story types. The chaos (47%) and restitution story (47%) types are dominant, accounting for 94% of the identified codes. Chaos was more prevalent among the hospitalisation stories and restitution more among the recovery stories. The quest story type occurred in 6% of the data. The substory types of chaos and restitution seem related to events and experiences during the illness trajectory of COVID-19. Alternatively, the quest subtypes appear as a reflection of the illness experience as a whole. Conclusion: This study suggests that COVID-19 narratives of hospitalise...
18. Taking Covid-19 data away from CDC is a recipe for chaos (Opinion) - CNN
16 jul 2020 · Dr. Kent Sepkowitz writes that the Trump administrations move to have the HHS collect Covid-19 data now instead of the CDC is the sort of ...
Dr. Kent Sepkowitz writes that the Trump administrations move to have the HHS collect Covid-19 data now instead of the CDC is the sort of tough-guy domination of the data that is increasingly appealing to the president as the US struggles with the realities of a disastrously mismanaged, raging pandemic. But the White House may have buyer’s remorse much sooner than later.
