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Dynamics of echinococcosis transmission among multiple species and a case study in Xinjiang, China

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  • Zhu, Guanghu
  • Chen, Sixing
  • Shi, Benyun
  • Qiu, Hongjun
  • Xia, Shang

Abstract

Human echinococcosis is an emerging but neglected zoonotic disease caused by parasites of genus Echinococcus. Its morbidity and mortality keep increasing in recent years, partially due to poor understanding of transmission dynamics and lack of effective control strategies of the disease. This paper aims to provide a modeling framework for analyzing echinococcosis transmission among multiple species and investigating spread dynamics of echinococcosis infection in Xinjiang Uygur Autonomous Region (XUAR), China. Based on the notions of compartmental and deterministic principles, a new echinococcosis transmission model is proposed, which incorporates the intrinsic interactions among intermediate hosts (IHs), definitive hosts (DHs), humans and echinococcus eggs (EEs). It is theoretically proved that the basic reproduction number R0 is the epidemic threshold, which determines the global stability of the disease-free and endemic equilibria. The model is validated with real data by applying retrospectively to the 2008–2012 seasonal echinococcosis infection in XUAR. It is found that the basic reproduction number in XUAR could be R0=1.69. If without control strategies, human incidence would keep increasing in the following years, reaching stable level at about 55,000 cases at the end of this century. Finally, the effects of transmission parameters are clarified by numerical simulations. It is observed that the interaction patterns among these species play a key role in echinococcosis transmission. The present study provides useful information to improve the understanding of echinococcosis transmission and further help control the disease.

Suggested Citation

  • Zhu, Guanghu & Chen, Sixing & Shi, Benyun & Qiu, Hongjun & Xia, Shang, 2019. "Dynamics of echinococcosis transmission among multiple species and a case study in Xinjiang, China," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 103-109.
    • Handle: RePEc:eee:chsofr:v:127:y:2019:i:c:p:103-109
    DOI: 10.1016/j.chaos.2019.06.032
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    References listed on IDEAS

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    1. Meng, Xinzhu & Li, Fei & Gao, Shujing, 2018. "Global analysis and numerical simulations of a novel stochastic eco-epidemiological model with time delay," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 701-726.
    2. Franz J Conraths & Carolina Probst & Alessia Possenti & Belgees Boufana & Rosella Saulle & Giuseppe La Torre & Luca Busani & Adriano Casulli, 2017. "Potential risk factors associated with human alveolar echinococcosis: Systematic review and meta-analysis," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 11(7), pages 1-15, July.
    3. Haokun Qi & Lidan Liu & Xinzhu Meng, 2017. "Dynamics of a Nonautonomous Stochastic SIS Epidemic Model with Double Epidemic Hypothesis," Complexity, Hindawi, vol. 2017, pages 1-14, November.
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    Cited by:

    1. Chen, Weixin & Xu, Xinzhong & Zhang, Qimin, 2024. "Hopf bifurcation and fixed-time stability of a reaction–diffusion echinococcosis model with mixed delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 223(C), pages 1-19.
    2. Qing-Long Gong & Gui-Yang Ge & Qi Wang & Tian Tian & Fei Liu & Nai-Chao Diao & Lan-Bi Nie & Ying Zong & Jian-Ming Li & Kun Shi & Xue Leng & Rui Du, 2021. "Meta-analysis of the prevalence of Echinococcus in dogs in China from 2010 to 2019," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 15(4), pages 1-17, April.

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