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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Mar 11, 2020
Date Accepted: Mar 23, 2020

The final, peer-reviewed published version of this preprint can be found here:

Optimization of Precontrol Methods and Analysis of a Dynamic Model for Brucellosis: Model Development and Validation

Huang Y, Li M

Optimization of Precontrol Methods and Analysis of a Dynamic Model for Brucellosis: Model Development and Validation

JMIR Med Inform 2020;8(5):e18664

DOI: 10.2196/18664

PMID: 32459180

PMCID: 7287712

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Application of Optimal Control and Analysis of Dynamic Model in Brucellosis

  • Yihao Huang; 
  • Mingtao Li

ABSTRACT

Background:

Brucella is a kind of bacteria parasitic in cells. The infection scope of Brucella is quite wide. The main source of infection is mammals, such as cattle, sheep, goats, pigs, and dogs. The transmission of Brucella is that it passes through the digestive tract, the respiratory tract, and the skin and mucous membranes. Currently, human beings do not transmit brucellosis with each other. By eating Brucella-contaminated food, contacting animals or animal secretions and excreta infected with Brucella, humans are infected with Brucella [8]. Although Brucellosis is not found in humans, its diagnosis and cure are very difficult; thus, it brings impacts to humans. Once infected with Brucella, the infected person will go through the acute phase and the chronic phase. The infected person is first in the acute phase. At this time, the infected person will have symptoms of other systemic diseases. In this stage, Brucellosis is relatively easy to be cured; however, the infected person often cannot be effectively diagnosed as brucellosis. After the infected person enters the chronic stage, Brucellosis will be very difficult to cure [9]. Brucella has a strong ability to adapt to the environment, which makes it able to tolerate dryness and cold and survive in meat or dairy products for up to two months. However, Brucella is not heat-resistant and will immediately die in boiling water. However, if a common disinfectant is used to destroy the bacteria, it will take several hours. Therefore, Brucella has been spread all over the world, and China is one of the most-widely spread countries. Even with the rapid development of medical science, Brucellosis is still a huge problem for Chinese people. At present, the number of patients suffering from Brucellosis in China is as high as 100,000 per year. In addition, due to the improvement of the living standards of Chinese people, the demand for meat products has gradually increased, and meat transactions have greatly promoted the spread of Brucellosis. Therefore, the research on the transmission of Brucella, as well as the diagnosis and treatment of Brucellosis, has become the issue that the researchers are concerning. Mathematical models have become a very important tool for the study of infectious diseases. Mathematical models can reflect the spread of infectious diseases, and can also be used to study the effect of different inhibition methods on the suppression of infectious diseases. The effect of control measures to obtain effective suppression programs can provide theoretical support for the suppression of infectious diseases [10]. Therefore, it is the major objective of this study to build a suitable mathematical model for Brucellosis infection.

Objective:

To study the optimized pre-control method of Brucellosis model by the dynamic threshold-based microcomputer model, and to provide critical theoretical support for the prevention and control of Brucellosis.

Methods:

By studying the transmission characteristics of Brucella and building a Brucella transmission model, a pre-control method for key populations (Brucella susceptible populations) is designed according to these characteristics, thereby exploring the utilization of protective tools by key groups before and after pre-control.

Results:

The improvement in “whether wearing gloves” is the most obvious, which increases from 51.01% before the pre-control to 66.22% after the pre-control, with an increase of 15.21%. The difference is statistically significant (P<0.001). However, for “whether wearing hats”, the conditions of key populations are not improved significantly, which increases from 57.3% before the pre-control to 58.6% after the pre-control, with an increase of 1.3%. The difference is not statistically significant (P>0.05).

Conclusions:

The research results of Brucellosis have provided theoretical support for the suppression of Brucella and the protective measures for key populations.


 Citation

Please cite as:

Huang Y, Li M

Optimization of Precontrol Methods and Analysis of a Dynamic Model for Brucellosis: Model Development and Validation

JMIR Med Inform 2020;8(5):e18664

DOI: 10.2196/18664

PMID: 32459180

PMCID: 7287712

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