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A dynamic model and some strategies on how to prevent and control hepatitis c in mainland China. | LitMetric

A dynamic model and some strategies on how to prevent and control hepatitis c in mainland China.

BMC Infect Dis

School of Information and Mathematics, Yangtze University, Jingzhou 434023, China, Nanhuan Road, Jingzhou, 434023, China.

Published: August 2019

Background: Hepatitis C virus (HCV) is a leading cause of chronic liver disease. As yet there is no approved vaccine protects against contracting hepatitis C. HCV seriously affects many people's health in the world.

Methods: In this article, an epidemiological model is proposed and discussed to understand the transmission and prevalence of hepatitis C in mainland China. This research concentrates on hepatitis C data from Chinese Center for Disease Control and Prevention (China's CDC). The optimal parameters of the model are obtained by calculating the minimum chi-square value. Sensitivity analyses of the basic reproduction number and the endemic equilibrium are conducted to evaluate the effectiveness of control measures.

Results: Vertical infection is not the most important factor that causes hepatitis C epidemic, but contact transmission is. The proportion of acute patients who are transformed into chronic patients is about 82.62%. The possibility of the hospitalized patients who are restored to health is about 76.24%. There are about 92.32% of acute infected are not treated. The reproduction number of hepatitis C in mainland China is estimated as approximately 1.6592.

Conclusion: We find that small changes of transmission infection rate of acutely infected population, transmission infection rate of exposed population, transition rate for the acutely infected, and rate of progression to acute stage from the exposed can achieve the purpose of controlling HCV through sensitivity analysis. Finally, based on the results of sensitivity analysis, we find out several preventions and control strategies to control the Hepatitis C.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697970PMC
http://dx.doi.org/10.1186/s12879-019-4311-xDOI Listing

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