A new model for the spread of COVID-19 and the improvement of safety.
TLDR
In this paper, the authors developed a more effective method for diagnosing and predicting the COVID-19 spread and to evaluate the effectiveness of control measures to reduce and stop the virus spread.About:
This article is published in Safety Science.The article was published on 2020-12-01 and is currently open access. It has received 42 citations till now. The article focuses on the topics: Population.read more
Citations
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Modeling the spread of COVID-19 on construction workers: An agent-based approach.
TL;DR: This study found that the workforce from a construction project may be reduced by 30% to 90% due to the spread of COVID-19, which is a key component of countries’ economies and may help to the financial response to the pandemic.
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Challenges of SERS technology as a non-nucleic acid or -antigen detection method for SARS-CoV-2 virus and its variants.
TL;DR: In this paper, surface-enhanced Raman spectroscopy (SERS) has been proposed as an alternative and supplementary diagnostic method for SARS-CoV-2 virus and compared its pros and cons to the standard methods and what other aspects it could offer that the other methods are not capable of.
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Mathematical Tools for Understanding Infectious Disease Dynamics. Princeton Series in Theoretical and Computational Biology. By Odo Diekmann, Hans Heesterbeek and Tom Britton. xiv + 502 pp. Princeton, NJ: Princeton University Press. 2014. $90.00 (cloth and e‐book).
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Physics-informed neural networks and functional interpolation for data-driven parameters discovery of epidemiological compartmental models
Enrico Schiassi,Mario De Florio,Andrea D’Ambrosio,Andrea D’Ambrosio,Daniele Mortari,Roberto Furfaro +5 more
TL;DR: This work focuses on the capability of X-TFC in solving inverse problems to estimate the parameters governing the epidemiological compartmental models via a deterministic approach and shows the low computational times, the high accuracy, and effectiveness of the X- TFC method in performing data-driven parameters’ discovery systems modeled via parametric ODEs using unperturbed and perturbed data.
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The Signature of the Coronavirus Lockdown in Air Pollution in Greece
TL;DR: In this paper, the change in atmospheric pollution from a public lockdown in Greece introduced to curb the spread of the COVID-19 is examined based on ground-based and satellite observations.
References
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Journal ArticleDOI
Population biology of infectious diseases: Part II
Robert M. May,Roy M. Anderson +1 more
TL;DR: Consideration is given to the relation between the ecology and evolution of the transmission processes and the overall dynamics, and to the mechanisms that can produce cyclic patterns, or multiple stable states, in the levels of infection in the host population.
Book
Mathematical Models in Population Biology and Epidemiology
TL;DR: This paper presents a series of models for continuous single-species and multi-species population models, and a model forStructured Population Models, which combines continuous and discrete models for populations with spatial distribution.
BookDOI
Population biology of infectious diseases.
Roy M. Anderson,Robert M. May +1 more
TL;DR: When you read more every page of this population biology of infectious diseases, what you will obtain is something great.
Book
Statistical Models: Theory and Practice
TL;DR: This paper presents a meta-modelling framework for estimating the bootstrap values of multiple regression models based on data from Observational studies and experiments and a comparison of these models with real-world data.
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The Epidemiologic Transition: A Theory of the Epidemiology of Population Change
TL;DR: The case for a multidisciplinary approach to population theory has been aptly stated by Kurt Mayer: "Any meaningful interpretation of the cause and effects of population changes must extend beyond formal statistical measurement of the components of change, i.e., fertility, mortality and migration, and draw on the theoretical framework of several other disciplines for assistance" as mentioned in this paper.