• Corpus ID: 212747878

Options on infectious diseases

  title={Options on infectious diseases},
  author={Andrew S. Lesniewski and Nicholas Lesniewski},
  journal={arXiv: Computational Finance},
We present a parsimonious stochastic model for valuation of options on the fraction of infected individuals during an epidemic. The underlying stochastic dynamical system is a stochastic differential version of the SIR model of mathematical epidemiology. 
Epidemic control via stochastic optimal control
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Application of 3D bioprinting in the prevention and the therapy for human diseases
3D bioprinting in infectious disease research and drug development could be a significant platform technology for the rapid and automated production of tissue/organ models and medicines in the near future.


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A simple stochastic epidemic model is defined and exact and asymptotic (relying on a large community) properties are presented and several generalizations towards realism are presented.
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It is proved that this classical susceptible-infected-susceptible epidemic model is formulated as a stochastic differential equation (SDE) for the number of infectious individuals and that this SDE has a unique global positive solution.
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It will be shown that the phenomenon of extinction or fade-out of infection largely decides whether the deterministic approximation has any relevance or not to the quasiperiodicity of recurrent epidemics, and implies that the two-year cycle sometimes claimed as an inherent feature of measles will be replaced by a longer average interval between epidemics for smaller communities.
Monte Carlo Methods in Financial Engineering
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The present communication discussion will be limited to the case in which all members of the community are initially equally susceptible to the disease, and it will be further assumed that complete immunity is conferred by a single infection.
Monte Carlo Methods
1 The general nature of Monte Carlo methods.- 2 Short resume of statistical terms.- 3 Random, pseudorandom, and quasirandom numbers.- 4 Direct simulation.- 5 General principles of the Monte Carlo
Mathematical Models in Epidemiology, Springer (2019)
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Stochastic epidemic models: A survey, Mathematical Biosciences
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Numerical Solution of Partial Differential Equations, Cambridge University
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Numerical Solution of Partial Differential Equations