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Objective To investigate the relationship between clinical parameters related to acute bacterial dysentery and other infectious diarrhea in adults.Methods From April to October 2018,70 patients with clinical diagnosis of acute bacterial dysentery,180 patients with clinical diagnosis of infectious diarrhea and 399 patients with diarrhea to be examined were investigated retrospectively.The collected data included gender,age,time from onset to treatment,maximum body temperature,main symptoms,epidemiological history,blood routine,C-reactive protein and stool routine.Analysis of these clinical factors related to acute bacterial dysentery and other infectious diarrhea.Results A total of 70 patients with acute bacterial dysentery,180 patients with other infectious diarrhea and 399 patients with diarrhea of unknown origin were investigated.The positive rate of epidemiology in the three groups was statistically significant (P ＜0.05);the age of onset of bacterial dysentery was younger than that in patients with diarrhea of unknown orion (P＜O.05).Compared with the other two groups of patients,the onset to visit time was earlier,the number of vomiting was higher,the incidence of fever and tenesmus was higher,and the levels of white blood cells,neutrophils and C-reactive protein were significantly increased (P ＜ 0.05).Conclusions Patients with acute bacterial dysentery,other infectious diarrhea,and diarrhea of unknown origin have some differences in epidemiological history,age at onset,clinical manifestations,and laboratory tests.
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Objective@#To investigate the relationship between clinical parameters related to acute bacterial dysentery and other infectious diarrhea in adults.@*Methods@#From April to October 2018, 70 patients with clinical diagnosis of acute bacterial dysentery, 180 patients with clinical diagnosis of infectious diarrhea and 399 patients with diarrhea to be examined were investigated retrospectively. The collected data included gender, age, time from onset to treatment, maximum body temperature, main symptoms, epidemiological history, blood routine, C-reactive protein and stool routine. Analysis of these clinical factors related to acute bacterial dysentery and other infectious diarrhea.@*Results@#A total of 70 patients with acute bacterial dysentery, 180 patients with other infectious diarrhea and 399 patients with diarrhea of unknown origin were investigated. The positive rate of epidemiology in the three groups was statistically significant (P<0.05); the age of onset of bacterial dysentery was younger than that in patients with diarrhea of unknown origin (P<0.05). Compared with the other two groups of patients, the onset to visit time was earlier, the number of vomiting was higher, the incidence of fever and tenesmus was higher, and the levels of white blood cells, neutrophils and C-reactive protein were significantly increased (P<0.05).@*Conclusions@#Patients with acute bacterial dysentery, other infectious diarrhea, and diarrhea of unknown origin have some differences in epidemiological history, age at onset, clinical manifestations, and laboratory tests.
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Objective: To analyze the spatial epidemiological characteristics of bacillary dysentery and its correlation with meteorological elements in Chongqing, and to construct its incidence prediction model, thus providing scientific basis for the prevention and control of bacterial dysentery. Methods: The data of bacterial dysentery cases and meteorological factors from 2009 to 2016 in Chongqing was collected in this study. Descriptive methods were employed to investigate the epidemiological distribution of bacillary dysentery. Spatiotemporal scanning statistics was used to analyze spatiotemporal characteristics of bacillary dysentery. DCCA coefficient method was used to quantify the correlation between the incidence of bacillary dysentery and meteorological elements. Both Boruta algorithm and particle swarm optimization algorithm (PSO) combined with support vector machine for regression model (SVR) were used to establish the prediction model for the incidence of bacterial dysentery. Results: ①The mean annual reported incidence of bacillary dysentery in Chongqing from 2009 to 2016 was 29.394/100 000. Children <5 years old had the highest incidence (295.892/100 000) among all age categories and scattered children had the highest proportion (50.335%) among all occupation categories. The seasonal incidence peak was from May to October. Bacterial dysentery showed a significant spatial-temporal aggregation that the most likely clusters for disease was found mainly in the main urban areas and main gathering time was from June to October. ②The most important meteorological elements associated with the incidence of bacterial dysentery were monthly mean atmospheric pressure (ρDCCA=-0.918), monthly mean maximum temperature (ρDCCA=0.875) and monthly mean temperature (ρDCCA=0.870). ③The mean squared error (MSE), mean absolute percentage error (MAPE) and square correlation coefficient (R2) of PSO_SVR model constructed based on meteorological elements were 0.055, 0.101 and 0.909, respectively. Conclusion: The main urban areas of Chongqing and the northeast of Chongqing should be regarded as the key areas for the prevention and control of bacillary dysentery. At the same time, according to the characteristics of bacillary dysentery, relevant health departments should take targeted measures to control the spread and prevalence of bacillary dysentery among children <5 years old, scattered children and farmers. The PSO_SVR model constructed based on meteorological elements has good predictive performance and can provide scientific theoretical support for the prevention and control of bacterial dysentery.
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Objective@#To analyze the relationship between the incidence of bacterial dysentery and related meteorological, environmental and socio-economic factors in parts of southwest China, under the geodetector.@*Methods@#Incidence data on bacillary dysentery from 2005 to 2014 was collected from the China infectious disease reporting system and meteorological, terrain environment and socio-economic related data were used for statistical analysis with geodetector also used, in Sichuan province, Yunnan province and the Tibet autonomous region (southwest China).@*Results@#Through geodetector model, results showed that the elevation maximum value of power of determinant (PD) (PD=0.308), ethnicity (PD=0.260), followed by summer mean temperature, topography, elevation standard deviation, slope, population density were noticed. The maximum value of PD of summer average relative humidity, summer average precipitation, and regional GDP were all less than 0.200. In the ecological detector model, value of PD appeared significantly different from multiple factors such as summer average precipitation, regional GDP, average altitude, elevation standard deviation, slope, terrain and ethnicity (P<0.05). In the interactive detector model, after the spatial interaction, factors as: value on PD of summer average relative humidity, population density and regional GDP were larger than the value on the sum of PD of two factors with nonlinear superposition enhancing trend. Results from the risk zone detection showed that areas of moderate average summer temperature, low average precipitation, moderate average summer relative humidity, high average altitude, large elevation standard deviation, high slope, mountain topography, Tibeto-Burmese of ethnicity, low population density, low regional GDP were all related to the high incidence rates of bacterial dysentery.@*Conclusions@#Meteorological conditions and topography environments were related to the bacterial dysentery in southwest China, socio-economic behaviors depends on the level of economic development and sanitary conditions etc. were all directing influencing the transmission and incidence of bacterial dysentery. For developing a better intervention programs on bacillary dysentery, socio-economic means should be used for the control of bacillary dysentery, in the region.
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Objective To explore the application of autoregressive integrated moving average (ARIMA) model, and ARIMA combined nonlinear autoregressive (ARIMA-NAR) model in predicting bacterial dysentery (BE) incidence. Methods Data of BE monthly incidences from Jan. 2004 to Feb. 2015 in Jiangsu Province were used as fitting samples, the 15-month data from Mar. 2015 to May 2016 were used in the prediction phase. ARIMA model and ARIMA-NAR model were established and the effects of two models were compared according to mean absolute error (MAE), mean square error (MSE), and mean absolute percentage error (MAPE), in which lower values suggested higher prediction accuracy. Results In the fitting phase, the MAE, MSE and MAPE of the ARIMA model were 0. 177 5, 0. 081 4 and 0. 184 7, respectively, while those of the ARIMA-NAR model were 0. 094 1, 0. 029 5 and 0. 104 6, respectively. In the prediction phase, the MAE, MSE and MAPE of the ARIMA model were significantly higher than those of the ARIMA-NAR model. Conclusion ARIMA-NAR combined model is superior to ARIMA model in predicting the time series of BE incidence in Jiangsu Province, suggesting that ARIMA-NAR model can be used to predict the incidence of BD.
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BACKGROUND: In March 1999, six children who attended a nursery school became ill with acute gastroenteritis by Shigella sonnei. The majority of the children became sick one day after sharing a snack which was served from one of the children's home. By the time the outbreak of dysentery was recognized, the rest of family members of the children became also sick. The nursery school was located in a crowded residential area. EPIDEMIOLOGIC INVESTIGATION: After active and passive surveillance was established on patients with diarrhea, 438 patients were registered. Among them, 252 patients were considered to have simple diarrhea, but the rest (186 patients) suffered from more than three consecutive diarrheas. Shigella sonnei was isolated from 75 patients. The first attack rate was estimated at 50.0%, the second, 25.6%-34.3% and the third, 13.5%. The epidemic lasted for two months spreading further from person to person in the highly populous area. The active surveillance was implemented after the occurrence of the secondary attack of dysentery among the residents, who had no obvious direct contact with people associated with the nursery school. CONCLUSION: This investigation demonstrates the need for prompt implementation of active surveillance when Shigella infection is recognized in a highly populous city.