Leprocy Leprosy Bibliometrics And Empirical Research On Epidemiology

Objectives: carding the process of leprosy prevention and control by conducting leprosy Bibliometrics.to fit the leprosy prevalence of Gansu province from 1950 to 2016 in time series analysis model and regression analysis,respectively.Choosing more precise model to predict the leprosy prevalence of Gansu province from 2017 to 2020,providing early warning of leprosy with scientific evidence.Methods: 1.Leprosy Bibliometrics analysis: the main chinese databases were searched to select studies on leprosy,and two reviewers selected studies in Endnote X6,independently.Excel2003 was used to statistic analysis.2.Empirical research of leprosy prevalence in Gansu province:based on the leprosy prevalence of Gansu province from 1950 to 2016,R software and SPSS 20.0software were used to establish ARIMA model and quadratic regression,respectively.Comparing the precision of two models and choosing the error lesser one,and predicting the leprosy prevalence of Gansu province from 2017 to 2020 in this error lesser model.Results: 1.Leprosy Bibliometrics analysis: 4414 studies were included,and the first leprosy study recorded in databases was published in 1954.statistical result showed that the leprosy researches' quantity variation trend was so obvious.According to quantity variation trend,there were four stages,also many difference in every period.leprosy treatment and microscopic research were mainly been researched in previous period,however,time series analysis were mainly been researched in later stage.In addition,professional journals were the main base of leprosy research and published the majority studies.2.Empirical research of leprosy prevalence in Gansu province: based standard fitting process and the leprosy prevalence of Gansu province from1950 to 2016,ARIMA(0,2,1)model and regression equation were much better than other models.And in these two models,ARIMA(0,2,1)model was better,with higher determination coefficient(R2)0.825,and quadratic regression has lesser determination coefficient(R2)0.782.So,after comparing two models' precision,ARIMA(0,2,1)was optimization model.the leprosy prevalence of Gansu province from 2017 to 2020 will be:0.045/100,000,0.043/100,000,0.036/100,000 and 0.035/100,000 using ARIMA(0,2,1)model.Conclusion: Bibliometrics analysis showed that,the leprosy researches experienced grows out ofnothing,gradually increased to peak and decreases gradually.And now,based on history information,many researchers intent to summarize the laws of leprosy prevalence and optimize the strategy of prevention and control constantly.However,many studies just describe the time series simply.No effective and mature method can be used to do early warning of leprosy.And in empirical research section,compared with quadratic regression,ARIMA(0,2,1)was the optimization model to fit the leprosy prevalence data of Gansu province.And this model can be used as early warning method for epidemic situation of leprosy.