A call for epidemic modeling to examine historical and structural drivers of racial disparities in infectious disease

Mathematical analysis and modelling is central to infectious disease epidemiology. This paper, inspired by the natural ripple-spreading phenomenon, proposes a novel ripple-spreading network model for the study of infectious disease transmission. The new epidemic model naturally has good potential for capturing many spatial and temporal features observed in the outbreak of plagues. In particular, using a stochastic ripple-spreading process simulates the effect of random contacts and movements of individuals on the probability of infection well, which is usually a challenging issue in epidemic modeling. Some ripple-spreading related parameters such as threshold and amplifying factor of nodes are ideal to describe the importance of individuals’ physical fitness and immunity. The new model is rich in parameters to incorporate many real factors such as public health service and policies, and it is highly flexible to modifications. A genetic algorithm is used to tune the parameters of the model by referring to historic data of an epidemic. The well-tuned model can then be used for analyzing and forecasting purposes. The effectiveness of the proposed method is illustrated by simulation results.

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Facilitating Understanding, Modeling and Simulation of Infectious Disease Epidemics in the Age of COVID-19

Frontiers in Public Health ◽

10.3389/fpubh.2021.593417 ◽

2021 ◽

Vol 9 ◽

Author(s):

David M. Rubin ◽

Shamin Achari ◽

Craig S. Carlson ◽

Robyn F. R. Letts ◽

Adam Pantanowitz ◽

...

Keyword(s):

Infectious Disease ◽

Differential Equations ◽

System Dynamics ◽

Epidemic Modeling ◽

Disease Epidemiology ◽

Infectious Disease Epidemiology ◽

Complex Models ◽

Flow Diagrams ◽

Stock Flow ◽

Disease Epidemics

Interest in the mathematical modeling of infectious diseases has increased due to the COVID-19 pandemic. However, many medical students do not have the required background in coding or mathematics to engage optimally in this approach. System dynamics is a methodology for implementing mathematical models as easy-to-understand stock-flow diagrams. Remarkably, creating stock-flow diagrams is the same process as creating the equivalent differential equations. Yet, its visual nature makes the process simple and intuitive. We demonstrate the simplicity of system dynamics by applying it to epidemic models including a model of COVID-19 mutation. We then discuss the ease with which far more complex models can be produced by implementing a model comprising eight differential equations of a Chikungunya epidemic from the literature. Finally, we discuss the learning environment in which the teaching of the epidemic modeling occurs. We advocate the widespread use of system dynamics to empower those who are engaged in infectious disease epidemiology, regardless of their mathematical background.

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Tissue section lifting for electron microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100081292 ◽

1978 ◽

Vol 36 (2) ◽

pp. 86-87

Author(s):

Adrian F. van Dellen

Keyword(s):

Infectious Disease ◽

Electron Microscopy ◽

Tissue Culture ◽

Organ System ◽

Surrounding Tissue ◽

Paraffin Sections ◽

Surface Areas ◽

Specific Determination ◽

High Degree ◽

Accuracy And Repeatability

The morphologic pathologist may require information on the ultrastructure of a non-specific lesion seen under the light microscope before he can make a specific determination. Such lesions, when caused by infectious disease agents, may be sparsely distributed in any organ system. Tissue culture systems, too, may only have widely dispersed foci suitable for ultrastructural study. In these situations, when only a few, small foci in large tissue areas are useful for electron microscopy, it is advantageous to employ a methodology which rapidly selects a single tissue focus that is expected to yield beneficial ultrastructural data from amongst the surrounding tissue. This is in essence what "LIFTING" accomplishes. We have developed LIFTING to a high degree of accuracy and repeatability utilizing the Microlift (Fig 1), and have successfully applied it to tissue culture monolayers, histologic paraffin sections, and tissue blocks with large surface areas that had been initially fixed for either light or electron microscopy.

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