Study On The Correlation Between Foodborne Diseases And Meteorological Factors And Prediction Of Time Series Model In Jinan

BackgroundThe global annual incidence rate and mortality of foodborne diseases have been on the rise due to food pollution.In China,one in every 6.5 people suffers from foodborne diseases.This situation is deeply worrying,and more stringent measures must be taken to curb and prevent the spread of such diseases.This disease is very common worldwide and poses a huge threat to human health and social stability.In recent years,due to the impact of environmental degradation and global warming,more and more studies have shown that climate change can lead to diseases and other adverse effects on human health.Therefore,exploring the epidemic trends of foodborne diseases and major pathogenic bacteria,the impact of meteorological factors on the incidence of foodborne diseases,and building models for short-term prediction,can provide scientific theoretical basis and technical support for the administrative departments to formulate corresponding policies and measures.ObjectivesTo understand the epidemic trend and pathogenic characteristics of foodborne diseases in Jinan City,to explore the correlation between meteorological factors and the incidence of foodborne diseases,to build a time series prediction model,and predict its incidence trend,so as to adapt to the epidemiological characteristics of foodborne diseases in Jinan City and provide targeted measures for the prevention and control of foodborne diseases.Methods1.Excel 2013 software was used to collect the incidence data and meteorological data of the same period in Jinan,and descriptive epidemiological analysis was conducted on the incidence data and meteorological factors of the same period.2.The correlation between the incidence of foodborne diseases and meteorological data during the same period in Jinan City was analyzed using Spearman rank correlation analysis.Combining the results of correlation analysis,the included meteorological indicators were introduced into the GAM model through natural cubic spline functions to explore the impact of various meteorological factors on the risk of foodborne diseases.3.Using R software,a seasonal ARIMA time series prediction model for the incidence data of foodborne diseases in Jinan from 2014 to 2020 was constructed.Using the actual incidence data in 2021,the fitting effect was verified and the prediction effect of the model was evaluated.Results1.From 2013 to 2021,5417 cases of foodborne diseases were reported in two sentinel hospitals in Jinan,mainly among children aged 0 to 5 years(48.6%);The high incident period of foodborne diseases(75.0%)was from May to October;Digestive system syndrome was the main clinical symptom;Meat and meat products(13.9%)were the largest number of suspected exposed foods,and the packaging of exposed foods was mainly home-made foods(45.8%);The total detection rate of pathogens was 38.4%,among which diarrhoeal Escherichia coli(24.2%)was the main pathogen,and the detection rate of norovirus was 17.8%.There was a statistically significant difference in the detection rate of pathogens before and after the founding of the Healthy Cityproject,and before and after the COVID-19 epidemic(P<0.001).2.The incidence of foodborne diseases in Jinan was positively correlated with daily average temperature,relative humidity,and daily average wind speed,while negatively correlated with daily average atmospheric pressure.The exposure-response curve showed that the number of foodborne diseases increased slowly as the average temperature increased.When the daily average temperature was below the threshold of 24.63 ℃,the number of cases of foodborne diseases increased by 0.04%(95%confidence interval:0.02-0.06)for each 1 ℃ increase in the daily average temperature.When the daily average temperature was above the threshold of 24.63 ℃,the number of cases of foodborne diseases increased by 0.18%(95%confidence interval:0.07-0.28)for each 1℃ increase in the daily average temperature.When the daily average wind speed was higher than the threshold value of 2.26m/s,the incidence of foodborne diseases would decrease by 0.36%(95%confidence interval:-0.67--0.05)for each lm/s increase in the daily average wind speed.The results of relative humidity around the threshold of 34.72%was not statistically significant.3.The residual diagnosis sequence of ARIMA(2,0,1)(0,1,1)12model showed significant white noise characteristics.We compared the actual incidence data of Jinan in 2021 with the predicted value of the model,and found that the overall difference between the actual incidence cases and the predicted value was not significant,and the prediction accuracy was high.Conclusion1.Children and young adults aged 0-5 in Jinan City are susceptible to foodborne diseases,especially in summer and autumn.The infection rate of these viruses is higher,with the highest rates of Escherichia coli and Norovirus.In order to prevent the occurrence of foodborne diseases,relevant departments should take appropriate prevention and control measures.2.Through a comprehensive analysis of the incidence of foodborne diseases and historical records of climate change during the past nine years,it was found that meteorological factors were related to the occurrence of foodborne diseases.This conclusion provides a scientific basis for us to better formulate effective environmental and health policies.3.Using seasonal ARIMA models can accurately predict the development trend of foodborne diseases in Jinan.This approach can help us better address the short-term challenges of foodborne diseases in Jinan.