Optimization of Precontrol Methods and Analysis of a Dynamic Model for Brucellosis: Model Development and Validation
Authors: Mingtao Li
Yihao Huang
Journal: JMIR Medical Informatics (2020)
Discipline: CLINICAL MEDICINE
Keywords: brucellosis; dynamic model; precontrol methods; protective measures.
Affiliations: School of Computer and Information Technology, Shanxi University, Taiyuan, China., Complex Systems Research Center, Shanxi University, Taiyuan, China., College of Mathematics, Shanxi University of Technology, Taiyuan, China.

Abstract:  Background: Brucella is a gram-negative, nonmotile bacterium without a capsule. The infection scope of Brucella is wide. The major source of infection is mammals such as cattle, sheep, goats, pigs, and dogs. Currently, human beings do not transmit Brucella to each other. When humans eat Brucella-contaminated food or contact animals or animal secretions and excretions infected with Brucella, they may develop brucellosis. Although brucellosis does not originate in humans, its diagnosis and cure are very difficult; thus, it has a huge impact on humans. Even with the rapid development of medical science, brucellosis is still a major problem for Chinese people. Currently, the number of patients with brucellosis in China is 100,000 per year. In addition, due to the ongoing improvement in the living standards of Chinese people, the demand for meat products has gradually increased, and increased meat transactions have greatly promoted the spread of brucellosis. Therefore, many researchers are concerned with investigating the transmission of Brucella as well as the diagnosis and treatment of brucellosis. Mathematical models have become an important tool for the study of infectious diseases. Mathematical models can reflect the spread of infectious diseases and be used to study the effect of different inhibition methods on infectious diseases. The effect of control measures to obtain effective suppression can provide theoretical support for the suppression of infectious diseases. Therefore, it is the objective of this study to build a suitable mathematical model for brucellosis infection. Objective: We aimed to study the optimized precontrol methods of brucellosis using a 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, the precontrol methods were designed and presented to the key populations (Brucella-susceptible populations). We investigated the utilization of protective tools by the key populations before and after precontrol methods. Results: An improvement in the amount of glove-wearing was evident and significant (P&lt;.001), increasing from 51.01% before the precontrol methods to 66.22% after the precontrol methods, an increase of 15.21%. However, the amount of hat-wearing did not improve significantly (P=.95). Hat-wearing among the key populations increased from 57.3% before the precontrol methods to 58.6% after the precontrol methods, an increase of 1.3%. Conclusions: By demonstrating the optimized precontrol methods for a brucellosis model built on a dynamic threshold-based microcomputer model, this study provides theoretical support for the suppression of Brucella and the improved usage of protective measures by key populations. 

Retracted: No

PubPeer comments:
 An image in Figure 8A appears to overlap with an image in Figure 8B. I believe the field of view may be slightly rotated. This issue is sometimes seen in papers that have been outsourced. All of the authors appear affiliated with a provincial hospital, except for the last author. *** ![file] , 
 Thank you for reminding. Especially, great thanks for this email. We checked all the original pictures again and make sure that all the pictures and data we used in our manuscript are true and correct. However, we did make a mistake when we did Figure 8 although it didnu2019t have any impact on our results. In the process of preparing the Figure, the sixth figure (named 6) in the migration file of the si-LINC01121+NC group in our original file mistakenly replaced the sixth figure (named 6) in the invasion file of the si-LINC01121+miR-150-5p inhibitor group. Therefore, Figure 8B contains the representative images of cell migration in the si-LINC01121+NC group. However, the conclusions made are not influenced by the mistake of Fig. 8B, because the statistical analysis was performed based on the original images of cell invasion in the invasion file of the si-LINC01121+miR-150-5p inhibitor group. We have started contacting the periodical office for corrigendum. Thanks again for your efforts. , 
 #2 Thank you for responding. For my education, could you explain the responsibility of the various authors? It seems most of the authors are breast surgeons, who wouldnu2019t be expected to have access to the facilities or training to perform these experiments, yet the corresponding author is apparently a neurologist, who seemingly wouldnu2019t normally have involvement with breast cancer research. , 
 #3 Thank you for your question. In fact, the first author is also a PhD MD candidate at Xiangya Hospital of Central South University at that time. He has undergone a series of training during his master and PhD career. Furthermore, there are two co-corresponding authors in this article. The two institutions are in the neighbourhood and we have really close collaboration. Every author have known each other well. That s no problem for crossing paths in academic career. ,