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  • 标题:Modeling and analysis of taeniasis and cysticercosis transmission dynamics in humans, pigs and cattle
  • 本地全文:下载
  • 作者:Joshua A. Mwasunda ; Jacob I. Irunde ; Damian Kajunguri
  • 期刊名称:Advances in Difference Equations
  • 印刷版ISSN:1687-1839
  • 电子版ISSN:1687-1847
  • 出版年度:2021
  • 卷号:2021
  • 期号:1
  • 页码:1
  • DOI:10.1186/s13662-021-03341-9
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Taeniasis and cysticercosis pose a significant challenge to food safety and public health. Cysticercosis reduces the market value for pigs and cattle by making pork and beef unsafe for consumption. In this paper, a mathematical model for the transmission dynamics of taeniasis and cysticercosis in humans, pigs and cattle is formulated and analyzed. The analysis shows that both the disease free equilibrium (DFE) and the endemic equilibrium (EE) exist. To study the dynamics of the diseases, we derived the basic reproduction number $R_{0}$ by next generation matrix method. When $R_{0} 1$ the EE is globally asymptotically stable. The normalized forward sensitivity index was used to determine sensitive parameters to the diseases. Humans’ recruitment rate, probability of humans’ infection with taeniasis and the defecation rate of taenia eggs by humans with taeniasis are the most positive sensitive parameters to diseases’ transmission whereas the human natural death rate is the most negative sensitive parameter. However, it is biologically unethical and not practical to increase human natural mortality rate for disease control. In this case, other parameters with negative sensitivity indices such as death rate of taenia eggs and proportions of unconsumed infected beef and pork can be considered for disease control. Generally, to control the diseases, more efforts should be made directed to reducing the number of humans who have taeniasis and defecate in the open environment. Also meat inspection and indoor keeping of cattle and pigs should be emphasized.
  • 关键词:Taeniasis ; Cysticercosis ; Reproduction number ; Equilibria ; Stability analysis ; Sensitivity analysis
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