Dynamics of a seasonal brucellosis disease model with nonlocal transmission and spatial diffusion

Yang, Junyuan; Xu, Rui; Sun, Hongquan

doi:10.1016/j.cnsns.2020.105551

Cited by 18 publications

(8 citation statements)

References 32 publications

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“…Meanwhile, it should also be noted that spatial effects play an important role in brucellosis transmission, which may form pattern formation with rich structures [71] , [72] , [73] . For such reason, one may need to combine the method of transmission dynamics based on partial differential equations (mainly reaction–diffusion equations) [74] and geographic information system (GIS) to associate the outbreak and development trend of brucellosis with the specific geographical location, and build a brucellosis prediction and early warning system. Additionally, big data analysis is also required to reveal the features of brucellosis transmission in both space and time [75] , [76] .…”

Section: Discussionmentioning

confidence: 99%

Transmission dynamics of brucellosis: Mathematical modelling and applications in China

Sun

Zhang

et al. 2020

Computational and Structural Biotechnology Journal

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Brucellosis, the most common zoonotic disease worldwide, represents a great threat to animal husbandry with the potential to cause enormous economic losses. Meanwhile, brucellosis is one of the major public-health problems in China, and the number of human brucellosis cases has increased dramatically in recent years. In order to show the main features of brucellosis transmission in China, we give a systematic review on the transmission dynamics of brucellosis including a series of mathematical models and their applications in China. For different situations, dynamical models of brucellosis transmission in single population and multiple populations are devised based on ordinary differential equations. Furthermore, we revealed the spatial-temporal characteristics and effective control measures of brucellosis transmission. The results may provide new perspectives for the prevention and control of other types of zoonoses.

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Section: Discussionmentioning

confidence: 99%

Transmission dynamics of brucellosis: Mathematical modelling and applications in China

Sun

Zhang

et al. 2020

Computational and Structural Biotechnology Journal

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“…Several mathematical models of brucellosis have been developed by researchers. Their authors have used various mathematical approaches: ordinary differential equations with waning of immunity [9][10][11][12][13][14][15][16], culling [17][18][19], treatment and vaccination [18,20], seasonality [21], and partial differential equations with age of infection [22] and seasonality [23]. Ainseba et al [24] proposed an unstructured model to study the transmission of brucellosis.…”

Section: Mathematical Modelmentioning

confidence: 99%

A Model for Brucellosis Disease Incorporating Age of Infection and Waning Immunity

et al. 2022

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This paper proposes a model for brucellosis transmission. The model takes into account the age of infection and waning immunity, that is, the progressive loss of immunity after recovery. Three routes of transmissions are considered: vertical transmission, and both direct and indirect routes of horizontal transmission. According to the well-posedness results, we provide explicit formulas for the equilibria. Next, we derive the basic reproduction number R0 and prove some stability results depending on the basic reproductive number. Finally, we perform numerical simulations using model parameters estimated from biological data to confirm our theoretical results. The results of these simulations suggest that for certain values of parameters, there will be periodic outbreaks of epidemics, and the disease will not be eradicated from the population. Our results also highlight the fact that the birth rate of cattle significantly influences the dynamics of the disease. The proposed model can be of a good use in studying the effects of vaccination on the cattle population.

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“…Many infectious diseases, such as influenza, brucellosis, hand-foot-mouth disease, and tuberculosis, have the characteristics of seasonal transmission. [10][11][12] Tuberculosis has a seasonal pattern peaking in the spring and summer seasons in many countries. 13 The monthly new TB cases of Jiangsu Province from 2009 to 2018 14 are shown in Figure 1, which illustrates strong annual oscillations.…”

Section: Introductionmentioning

confidence: 99%

Seasonal transmission dynamics and optimal control strategies for tuberculosis in Jiangsu Province, China

Xue

Ren

Sun

et al. 2022

Math Methods in App Sciences

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Tuberculosis was ranked No. 3 among 29 types of infectious diseases in January 2022 of Jiangsu Province, in the southeast of China, and it has strong seasonality whose incidence rate has been high in springs and low in winters. This comprehensive study extends the spreading dynamics to the control strategies of TB in Jiangsu Province with time-varying transmission rate, which is the first one in this type. The periodic transmission rate is incorporated to the classic SEIR model with susceptible, latent, infectious, and recovered compartments. The analysis shows that when the basic reproduction number R 0 is less than one, the epidemic will eventually disappear but, if R 0 is larger than one, the disease may persist with a periodic solution. The R 0 value of Jiangsu TB is calculated as 1.297.In addition, the model predicts that the epidemic will not disappear over time and there will be a major outbreak after certain years. To eradicate TB, this work introduces three control strategies on susceptible, latent, and infectious populations. It turns out that the optimal control solutions can reduce the incidence rate in 2035 by 90% from 2015, the goal of World Health Organization. Simultaneously, we find that the optimal controls have the same seasonality as the transmission rate. This indicates that Jiangsu Province needs to invest more control efforts in springs than in winters. In addition, the cost of control strategies is analyzed in terms of the unit cost, total cost, and incremental cost-effectiveness. Summarizing all results, we recommend targeting the latent patients, or both latent and infectious individuals, with the transmission rate-synchronized control strength as the most effective control strategy, to mitigate or even eradicate TB disease in Jiangsu Province.

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Dynamics of a seasonal brucellosis disease model with nonlocal transmission and spatial diffusion

Cited by 18 publications

References 32 publications

Transmission dynamics of brucellosis: Mathematical modelling and applications in China

Transmission dynamics of brucellosis: Mathematical modelling and applications in China

A Model for Brucellosis Disease Incorporating Age of Infection and Waning Immunity

Seasonal transmission dynamics and optimal control strategies for tuberculosis in Jiangsu Province, China

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