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A Markov based model to estimate the number of syphilis cases among floating population

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摘要 Syphilis is a sexually transmitted disease that spreads widely around the world,infecting tens of millions of people every year.In China,syphilis not only causes more than 1 million infections every year,but also has its own characteristics in spreading pattern:this disease always spreads with the migration of floating population.There have been many related investigations and studies on the transmission of syphilis with the floating population in China,but the study of quantitative modeling in this field is very limited.In this paper,based on the Markov process model and datasets collected in Zhejiang Province,China,we construct a new model to analyze the transmission and immigration process of syphilis.The results show that immigrant patients are one of the sources of infection of syphilis in Zhejiang province,and the infection rate is remarkable which should not be ignored.By using the PRCC method to analyze the relationship between parameters and infected cases,we also find two main effective measures that can control the spread of syphilis and reduce the infection rate:the self-attention of infected persons,and the use of sexual protection measures.With the increasing frequent exchanges of people among different countries and regions,studying the transmission of diseases with the floating populations has become more and more important.The method we use in this paper gives a new insight studying this issue,providing a quantitative research method using the data of diagnosed cases.All the methods and models in this paper can be extendly used in the studies of other diseases where immigrant patients should be considered.
出处 《Infectious Disease Modelling》 2022年第1期243-251,共9页 传染病建模(英文)
基金 supported by the financial support from GDAS0 Project of Science and Technology Development(2021GDASYL-20210103089) China Postdoctoral Science Foundation(2021M690747) National Natural Science Foundation of China(11701445) Science and Technology Program of Guangzhou(202007040007) GDAS0 Project of Science and Technology Development(2019GDASYL-0502007) Guangdong Provincial Rural Revitalization Strategy Special Fund Project(2019KJ138) Guangdong Basic and Applied Basic Research Foundation(2019A1515110503).
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