Improvement of Traditional Model of Infectious Diseases

DOI

10.2991/mmebc-16.2016.260How to use a DOI?

Keywords

epidemic model,multi-objective optimization,Runge-Kutta method

Abstract

This paper is to speculate the drug demand of each region and assist to plan a reasonable number through analyzing variations of weekly infected people, which is based on epidemic model and multi-objective optimization theory. Unlike traditional SIR model,I consider the patients under incubation period and antibody carriers after cure in my model. To begin with, I apply five classifications to sample individuals (i.e. the susceptible, borderline cases, confirmed cases, death cases and the cured cases), by which I establish a first order differential system to represent the disease propagation. By applying Runge-Kutta method to establish system, I obtain a fitted curve , through which the future propagation is more predictable.And then,To establish a comprehensive and efficient evaluation model,that is based on previous one while considering other key factors ,including drug manufacturing rate and delivery efficiency, I introduce a comprehensive evaluation coefficient of region coverage intensity .

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lingzhi Fu
PY  - 2016/06
DA  - 2016/06
TI  - Improvement of Traditional Model of Infectious Diseases
BT  - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
PB  - Atlantis Press
SP  - 1277
EP  - 1280
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmebc-16.2016.260
DO  - 10.2991/mmebc-16.2016.260
ID  - Fu2016/06
ER  -