Transmission dynamics of a multi-group brucellosis model with mixed cross infection in public farm

Global stability for a sheep brucellosis model with immigration

“…Based on the facts of brucellosis infection in the sheep farms, we classify the sheep population into four compartments: the susceptible compartment SðtÞ, the exposed compartment EðtÞ (In this compartment for sheep, which is asymptomatic infectious), the infectious compartment IðtÞ and the vaccinated compartment VðtÞ at time t. Let WðtÞ denote the quantity of sheep brucella in the environment at time t, it is only a assumption because it is very difficult to determine the quantity in environment and the quantity that is enough to infect an individual [17]. Thus, according to the paper [13], we also define the average number of brucella that is enough for a host to be infected as an infectious unit, so the unit of WðtÞ is the infectious unit.…”

“…In order to explore the transmission rules and find effective control strategies for sheep brucellosis, several mathematical dynamic models have also been developed to study the transmission of brucellosis [13,37,2,17]. For example, Hou et al [13] proposed a dynamic model which included transmission within sheep and the transmission from sheep to humans for brucellosis in Inner Mongolia of China.…”

“…Alnseba et al [2] studied an susceptible, infected and the contaminated environment dynamical model for brucellosis epidemic in ovine with direct and indirect transmission. Li et al [17] investigated a multi-group dynamical model with bidirectional mixed cross infection between cattle and sheep in public farms of China. Based on previous works and the facts of brucellosis infection in the sheep farms, in this paper we propose a deterministic dynamical model to investigate sheep brucellosis systematically in the sheep farms of China.…”

Dynamics and Stability Analysis of a Brucellosis Model with Two Discrete Delays

“…Models can provide solutions to phenomena which are difficult to measure practically. Recently, a number of mathematical models have been proposed to study the spread and control of brucellosis (see, for example, [3,[6][7][8][9][10][11][12][13][14][15] and references therein). A limitation of these previous studies, however, is the noninclusion of the time taken before an infectious animal is detected and culled, despite the fact that in many countries where the disease is endemic lack of financial and human resources often results in delay of detection and culling of infectious animals.…”

Modelling Seasonal Brucellosis Epidemics in Bayingolin Mongol Autonomous Prefecture of Xinjiang, China, 2010–2014

“…Brucellosis is a contagion-allergy zoonosis, it is caused by Gram-negative bacteria of the genus Brucella which includes Brucella abortus , Brucella melitensis , Brucella suis , Brucella neotomae , Brucella ovis , and Brucella canis [1, 2]. British military doctor Bruce was the first to confirm the pathogen of the disease in 1886; hence the disease was named “brucellosis” in order to honor him [3, 4].…”