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OUEMBA TASSÉ AJ, TSANOU B, LUBUMA J, WOUKENG JEANLOUIS, SIGNING FRANCIS. EBOLA VIRUS DISEASE DYNAMICS WITH SOME PREVENTIVE MEASURES: A CASE STUDY OF THE 2018–2020 KIVU OUTBREAK. J BIOL SYST 2022. [DOI: 10.1142/s0218339022500048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
To fight against Ebola virus disease, several measures have been adopted. Among them, isolation, safe burial and vaccination occupy a prominent place. In this paper, we present a model which takes into account these three control strategies as well as the indirect transmission through a polluted environment. The asymptotic behavior of our model is achieved. Namely, we determine a threshold value [Formula: see text] of the control reproduction number [Formula: see text], below which the disease is eliminated in the long run. Whenever the value of [Formula: see text] ranges from [Formula: see text] and 1, we prove the existence of a backward bifurcation phenomenon, which corresponds to the case, where a locally asymptotically stable positive equilibrium co-exists with the disease-free equilibrium, which is also locally asymptotically stable. The existence of this bifurcation complicates the control of Ebola, since the requirement of [Formula: see text] below one, although necessary, is no longer sufficient for the elimination of Ebola, more efforts need to be deployed. When the value of [Formula: see text] is greater than one, we prove the existence of a unique endemic equilibrium, locally asymptotically stable. That is the disease may persist and become endemic. Numerically, we fit our model to the reported data for the 2018–2020 Kivu Ebola outbreak which occurred in Democratic Republic of Congo. Through the sensitivity analysis of the control reproduction number, we prove that the transmission rates of infected alive who are outside hospital are the most influential parameters. Numerically, we explore the usefulness of isolation, safe burial combined with vaccination and investigate the importance to combine the latter control strategies to the educational campaigns or/and case finding.
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Affiliation(s)
- A. J. OUEMBA TASSÉ
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
| | - B. TSANOU
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
- Department of Science, Mathematics and Applied Mathematics, University of Pretoria, Private Bag X20, Pretoria 0028, South Africa
- IRD Sorbonne University, UMMISCO, F-93143, Bondy, France
| | - J. LUBUMA
- School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa
| | - JEAN LOUIS WOUKENG
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
| | - FRANCIS SIGNING
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
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Zhang J, Gan JR, Wu Y, Liu JB, Zhang S, Shao B. Research on the Resilience Evaluation and Spatial Correlation of China’s Sports Regional Development Under the New Concept. Front Psychol 2022; 12:763501. [PMID: 35185672 PMCID: PMC8855688 DOI: 10.3389/fpsyg.2021.763501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 11/26/2021] [Indexed: 11/13/2022] Open
Abstract
In order to fully implement the new development concept, bring into full play the potential of sports development, and maintain the resilience of China’s sports development. This paper studies the resilience evaluation and spatial correlation of Chinese sports development under the new development concept. First, we constructed Resilience Evaluation Indexes System for Sports Development in China based on the analysis of the resilience features of sports development and the DPSIR model, which is from the five aspects of “driving force – pressure – state – influence – response.” Second, used Coefficient of Variation and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) Method to measure the resilience level of sports development in 31 provinces in China from 2013 to 2017. Then, we introduced the obstacle degree model to identify the obstacle factors that hinder the resilience of Chinese sports development in different periods. Finally, we used the global and local Moran indexes to analyze the spatial correlation of China sports regional development. The results showed that: (1) overall, the development level of sports resilience in 31 provinces in China showed an upward trend from 2013 to 2017, while some provinces showed obvious fluctuations. (2) The obstacles to the development of sports resilience in China mainly include sports scientific research equipment, the number of national fitness monitoring stations, the number of national fitness centers, the full-time equivalent of (R&D) personnel, and the number of sports scientific research projects. The response subsystem is the main obstacle factor that affects the improvement of the resilience level of sports development in China. (3) There is a positive spatial autocorrelation between the resilience level of sports development and regional spatial distribution, and the correlation shows a weakening trend, and the internal difference is significant. Finally, we concluded that we must take the new development philosophy as the guiding principle. First, we should stick to innovation-driven development to fully upgrade the resilience of China’s sports development. Second, we should adhere to the principle of coordinated development to promote the overall and balanced development of sports. Lastly, we should promote shared development so as to deliver benefits for all in an equal way.
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Affiliation(s)
- Jing Zhang
- School of Physical Education and Training, Shanghai University of Sport, Shanghai, China
- Faculty of Physical Education, Shanghai International Studies University, Shanghai, China
| | - Jing-Ru Gan
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, China
| | - Ying Wu
- School of Physical Education and Training, Shanghai University of Sport, Shanghai, China
| | - Jia-Bao Liu
- School of Mathematics and Physics, Anhui Jianzhu University, Hefei, China
| | - Su Zhang
- Department of Physical Education, Anhui University of Finance and Economics, Bengbu, China
| | - Bin Shao
- School of Physical Education and Training, Shanghai University of Sport, Shanghai, China
- *Correspondence: Bin Shao,
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Cai XW, Bao YQ, Hu MF, Liu JB, Zhu JM. Simulation and Prediction of Fungal Community Evolution Based on RBF Neural Network. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2021; 2021:7918192. [PMID: 34659448 PMCID: PMC8519688 DOI: 10.1155/2021/7918192] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 09/20/2021] [Indexed: 11/18/2022]
Abstract
Simulation and prediction of the scale change of fungal community. First, using the experimental data of a variety of fungal decomposition activities, a mathematical model of the decomposition rate and the relationship between the bacterial species was established, thereby revealing the internal mechanism of fungal decomposition activity in a complex environment. Second, based on the linear regression method and the principle of biodiversity, a model of fungal decomposition rate was constructed, and it was concluded that the interaction between mycelial elongation and moisture resistance could increase the fungal decomposition rate. Third, the differential equations are used to quantify the competitive relationship between different bacterial species, divide the boundaries of superior and inferior species, and simulate the long-term and short-term evolution trends of the community under the same initial environment. And an empirical analysis is made by taking the sudden change of the atmosphere affecting the evolution of the colony as an example. Finally, starting from summer, combining soil temperature, humidity, and fungal species data in five different environments such as arid and semiarid, a three-dimensional model and RBF neural network are introduced to predict community evolution. The study concluded that under given conditions, different strains are in short-term competition, and in the long-term, mutually beneficial symbiosis. Biodiversity is important for the biological regulation of nature.
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Affiliation(s)
- Xiao-Wei Cai
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China
| | - Ya-Qian Bao
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China
| | - Ming-Feng Hu
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China
| | - Jia-Bao Liu
- School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China
| | - Jia-Ming Zhu
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China
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Wu YQ, Lu HX, Liao XL, Liu JB, Zhu JM. Foreign Direct Investment, Regional Innovation, and Green Economic Efficiency: An Empirical Test Based on the Investigation of Intermediary Effect and Threshold Effect. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2021; 2021:7348599. [PMID: 34630551 PMCID: PMC8497125 DOI: 10.1155/2021/7348599] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 09/14/2021] [Indexed: 11/18/2022]
Abstract
Based on the theoretical mechanism analysis of FDI, regional innovation, and green economic efficiency, this article uses China's provincial panel data to calculate the provincial green economic efficiency level based on the three-stage DEA method and uses the system GMM model, intermediary effect model, and threshold model to empirically test the specific effects and transmission paths of FDI on the efficiency of the green economy. Research shows that FDI is one of the important factors that promote the improvement of green economic efficiency. Subregional tests have found that FDI has a significant regional heterogeneity in promoting the efficiency of the green economy. The mediation effect test found that the mediation effect of regional innovation is significant, and FDI can significantly promote the growth of green economic efficiency through regional innovation. The threshold effect analysis found that there are significant and effective double thresholds for regional economic levels, and the impact of FDI on green economic efficiency is heterogeneous within different threshold intervals. The research conclusions provide new inspiration for China to allocate FDI more rationally and efficiently under the new development pattern.
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Affiliation(s)
- You-Qun Wu
- School of Economics, Anhui University of Finance and Economics, Bengbu 233030, Anhui, China
| | - Huai-Xin Lu
- School of Economics, Anhui University of Finance and Economics, Bengbu 233030, Anhui, China
| | - Xin-Lin Liao
- School of Economics, Anhui University of Finance and Economics, Bengbu 233030, Anhui, China
| | - Jia-Bao Liu
- School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China
| | - Jia-Ming Zhu
- Institute of Quantitative Economics, Anhui University of Finance and Economics, Bengbu 233030, China
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Probert WJM, Lakkur S, Fonnesbeck CJ, Shea K, Runge MC, Tildesley MJ, Ferrari MJ. Context matters: using reinforcement learning to develop human-readable, state-dependent outbreak response policies. Philos Trans R Soc Lond B Biol Sci 2019; 374:20180277. [PMID: 31104604 PMCID: PMC6558555 DOI: 10.1098/rstb.2018.0277] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/26/2019] [Indexed: 02/06/2023] Open
Abstract
The number of all possible epidemics of a given infectious disease that could occur on a given landscape is large for systems of real-world complexity. Furthermore, there is no guarantee that the control actions that are optimal, on average, over all possible epidemics are also best for each possible epidemic. Reinforcement learning (RL) and Monte Carlo control have been used to develop machine-readable context-dependent solutions for complex problems with many possible realizations ranging from video-games to the game of Go. RL could be a valuable tool to generate context-dependent policies for outbreak response, though translating the resulting policies into simple rules that can be read and interpreted by human decision-makers remains a challenge. Here we illustrate the application of RL to the development of context-dependent outbreak response policies to minimize outbreaks of foot-and-mouth disease. We show that control based on the resulting context-dependent policies, which adapt interventions to the specific outbreak, result in smaller outbreaks than static policies. We further illustrate two approaches for translating the complex machine-readable policies into simple heuristics that can be evaluated by human decision-makers. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
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Affiliation(s)
- W. J. M. Probert
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, UK
| | - S. Lakkur
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37203, USA
| | - C. J. Fonnesbeck
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37203, USA
| | - K. Shea
- Department of Biology, Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, PA 16802, USA
| | - M. C. Runge
- US Geological Survey, Patuxent Wildlife Research Center, Laurel, MD 20708, USA
| | - M. J. Tildesley
- Department of Life Sciences and Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK
| | - M. J. Ferrari
- Department of Biology, Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, PA 16802, USA
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Berge T, Ouemba Tassé AJ, Tenkam HM, Lubuma J. Mathematical modeling of contact tracing as a control strategy of Ebola virus disease. INT J BIOMATH 2018. [DOI: 10.1142/s1793524518500936] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
More than 20 outbreaks of Ebola virus disease have occurred in Africa since 1976, and yet no adequate treatment is available. Hence, prevention, control measures and supportive treatment remain the only means to avoid the disease. Among these measures, contact tracing occupies a prominent place. In this paper, we propose a simple mathematical model that incorporates imperfect contact tracing, quarantine and hospitalization (or isolation). The control reproduction number [Formula: see text] of each sub-model and for the full model are computed. Theoretically, we prove that when [Formula: see text] is less than one, the corresponding model has a unique globally asymptotically stable disease-free equilibrium. Conversely, when [Formula: see text] is greater than one, the disease-free equilibrium becomes unstable and a unique globally asymptotically stable endemic equilibrium arises. Furthermore, we numerically support the analytical results and assess the efficiency of different control strategies. Our main observation is that, to eradicate EVD, the combination of high contact tracing (up to 90%) and effective isolation is better than all other control measures, namely: (1) perfect contact tracing, (2) effective isolation or full hospitalization, (3) combination of medium contact tracing and medium isolation.
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Affiliation(s)
- T. Berge
- Department of Science, Mathematics and Applied Mathematics, University of Pretoria, Private Bag X20, Pretoria 0028, South Africa
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
| | - A. J. Ouemba Tassé
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
| | - H. M. Tenkam
- Department of Mathematics and Applied Mathematics, North-West University, Private Bag X1290, Potchefstroom 2520, South Africa
| | - J. Lubuma
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
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