Prediction method for disease dynamic states on basis of network structure

A technology of network structure and dynamic prediction, applied in the fields of medical data mining, special data processing applications, instruments, etc., can solve problems such as not being taken in time, unreasonable allocation of limited resources, etc., to achieve the effect of improving accuracy

Inactive Publication Date: 2017-05-31
GUANGDONG UNIV OF PETROCHEMICAL TECH
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Problems solved by technology

For public medical events, underestimating the impact of the epidemic may lead to failure to take effe

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  • Prediction method for disease dynamic states on basis of network structure
  • Prediction method for disease dynamic states on basis of network structure
  • Prediction method for disease dynamic states on basis of network structure

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Embodiment

[0108] The present invention adopts an intelligent mobile device installed with a contact tracking application. This application can track cases infected with Ebola virus. As long as you directly contact an Ebola virus patient, the time and place of this contact will be determined through the mobile device held by a volunteer. Can be submitted to the Centers for Disease Control and recorded in the database. Volunteers in the Ebola epidemic area wear the mobile device, and the data collected by it is transmitted to the World Health Organization (WHO), who makes emergency decisions on the epidemic based on the information obtained.

[0109] Such as figure 1 Shown, fragments of the dynamic contact network. This clip shows 50 cases and their interrelationships (infected and infected) in three typical countries and seven regions of the Ebola outbreak since 2014. The three countries considered are: Guinea, Nigeria and Liberia; the seven regions considered are: Guekedou, Macenta, K...

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Abstract

The invention discloses a prediction method for disease dynamic states on the basis of a network structure. The prediction method comprises the following steps: firstly, analyzing a great quantity of spatio-temporal data collected by mobile equipment carried by a volunteer in an epidemic situation region to evaluate influence of the network structure on the disease dynamic states; adopting three features including a clustering coefficient, degree distribution and degree correlation to describe the network structure; then, on the basis of an evaluation result, designing a structure identification model to identify a dynamically changed network structure; and finally, according to a relationship model of disease dynamic property and the network structure, predicting the dynamic change of a disease. According to the method, disease prediction accuracy can be effectively improved, and the method has an important significance for infectious disease control and prevention.

Description

technical field [0001] The invention relates to a network structure-based disease dynamic prediction method, which belongs to the technical field of information processing-based infectious disease control and prediction. Background technique [0002] During the outbreak of infectious diseases, accurate prediction of disease dynamics is a very important aspect of infectious disease control and prediction. Through accurate prediction, medical resources can be allocated reasonably and effectively, so as to make public medical events Reasonable and fast response. For public medical events, underestimating the impact of the epidemic may lead to failure to take effective measures in time, while overestimating will lead to unreasonable allocation of limited resources. Therefore, it is of great practical significance to accurately predict the dynamic changes and impact of diseases. [0003] During the epidemic period, the reproduction number R of infectious cases can be used as a ...

Claims

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Application Information

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IPC IPC(8): G06F19/00
CPCG16H50/70
Inventor 陈媛芳舒磊言理
Owner GUANGDONG UNIV OF PETROCHEMICAL TECH
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