Statistical Analysis Of The Incidence And Contamination Rate Of Salmonella In China

As the category of pathogenic bacteria which is the most dangerous and featured with the highest incidence rate in the pathogenic group of foodborne disease pathogens,Salmonella is able to lead to a large number of food poisoning incidents every year.Moreover,there are some commonalities or patterns for these incidents based on their respectiv e epidemiological characteristics.However,the relevant statistical studies on it by crossing time or geography at home and abroad are rare.In this regard,the following research was carried out in the paper with the objectives of breaking the statistical limitations of small sample data,getting to know the status of Salmonella contamination in food and grasping the disease pattern of foodborne Salmonella in China’s mainland:It built up the Hierarchical Bayesian model based on Bayesian estimation method and by relying on the data obtained from Literature mining,which was conductive to offering the reliable statistics on Salmonella contamination rate in commercially-available food products in China.The results showed that the average contamination rate of Salmonella in food sold was 5.91% in the mainland market of China,fluctuating from 2.02% to 8.29%,from 2004 to2018(95% confidence interval: 4.69%-7.27%).Among all types of food sold in the market,raw meat and meat products were the ones with the highest contamination rate of 8.45%.Sichuan province,Shanghai city and Heilongjiang province were the regions where the situation of food contamination by Salmonella was severe,with contamination rates of12.05%,11.53%,and 10.68%,respectively.The main pathogenic types were S.Enterica subgroup Ⅰ and Salmonella group infecting both animal and human,and the main species of Salmonella in food contamination were S.enteritidis,S.derby,and S.typhimurium,with contamination rates of 22.10%,15.23%,and 12.54%,respectively.It was possible to estimate the incidence rate of Salmonella in China from 2004-2018 and the incidence rate of Salmonella in each province based on hierarchical Bayesian model and adopting imputation formula of incidence rate,additionally,it could also predict the trend of incidence rate by adopting a gray prediction model.It was revealed by the results that most of the food poisoning incidents caused by Salmonella generally occurred in spring and summer while there were less cases in winter;food poisoning frequently occurred in catering businesses and rural banquets;in these places,meat and meat products were the main food types;from 2004 to 2018,the estimated value of average visit rate for diarrhea patients in China was 37.05% and the estimated value of detection rate of Salmonella in anal swab specimens of diarrhea patients was 13.96%.Moreover,the estimated value of Salmonella infection diarrhea was 86.87%.After metabolic GM(1,1)model was used to predict the annual incidence rate of Salmonella in 2019 and 2020 with the results being 18284.75/100000 and 18431.93/100000 respectively.The correlation coefficients and regression analysis were adopted to research on the relationship between the rate of Salmonella contamination and the incidence led by Salmonella.It was revealed by the results that there was a linear relationship between the rate of Salmonella contamination in food and the morbidity rate.The regression equation established by using the province data was y=76965.83x+2778.96;the regression equation established by using the year data was y=10120.61x+17150.41.All in all,it is conductive to carrying out reliable statistics on the rate of Salmonella contamination in commercially available foods in China,prediction of the trend of morbidity in this aspect and determination of a linear relationship between contamination rate and morbidity rate by adopting hierarchical Bayesian model which is established in the paper.In terms of the relevant work in the research,it can be extended to other foodborne pathogenic bacteria contamination rate and morbidity studies;except that,it can also be used by the health and market supervision departments to formulate the strategies for food safety management and carry out the effective technical means for supervision.