Incidence Of Bacillary Dysentery Research Articles

Inverted U-shaped association between bacillary dysentery and temperature: A new finding using a novel two-stage strategy in multi-region studies.

Bacillary dysentery (BD) has brought a significant public health concern in China. Temperature is one of the main factors affecting BD incidence. Due to the largely different temperature ranges between regions, the classic multi-region time series studies could only explore the relative temperature-BD association and showed that BD incidence is positively associated with relative temperature (i.e., temperature percentile), which does not conform to the laboratory knowledge that both high and low temperature interfere with the survival of bacteria. The association on relative temperature scale also limits the intuition of epidemiological meanings. A novel two-stage strategy was proposed to investigate the association between monthly temperature and BD incidence on the original temperature scale in 31 provinces, China. In the first stage, truncated polynomial splines, as the substitute of the common natural splines or B-splines in generalized additive models, were used to characterize the temperature-BD association on the original temperature scale in each province. In the second stage, a multivariate meta-analysis compatible with missing values was used to pool the associations. The classic strategy based on relative temperature was used as a reference. The average temperature-BD association presented a U-inverted shape, but not a monotonically increasing shape obtained using the classic strategy. This inverted U-shaped association conforms more to the laboratory knowledge and the original-scale association also provided an intuitive perspective and an easily explanatory result. Another advantage is that the novel strategy can extrapolate the province-specific association outside the observed temperature ranges by utilizing information from other provinces, which is meaningful considering the frequent incidences of extreme temperatures. The association between temperature and BD incidence presented a U-inverted shape. The proposed strategy can efficiently characterize the association between exposure and outcome on original scale in a multi-region study with largely different exposure ranges.

Comparison and Analysis of Incidence Rate of Bacillary Dysentery in Selected Countries

Bacillary dysentery is a waterborne and foodborne disease, which results in substantial morbidity all over the world. However, the changes in morbidity over time and the cause of bacillary dysentery varies in countries with different level of development. The study aims to compare the characteristics and changes of bacillary dysentery incidence and proper interventions in selected countries. From 2010 to 2019, the morbidity and mortality of it in underdeveloped countries are higher, indicating that the disease burden of bacillary dysentery in a specific country is associated with the level of development. The species of Shigella also show a difference. The outbreaks of bacillary dysentery in under-developed and developing countries are mainly caused by S.flexneri, while S.sonnei account for most infections in developed countries. The risk factors in underdeveloped countries are uneven health conditions and funding, inadequate health education, and poor hygiene and sanitation. As for developing countries, the risk factors are related to regional economic conditions, meteorological conditions, health conditions, and living habits. However, for developed countries, the emerging drug resistance of the pathogenic Shigella and the transmission between the men sex with men (MSM). Individual, household and government should be carried out with cooperation in countries with varying levels of development to reduce the burden of bacillary dysentery. The pathogen of bacillary dysentery has advanced quickly in recent years, bringing much disease burden globally. All nations must address the socioeconomic causes of bacillary dysentery. Scientific interventions need to be carried out according to the actual situations and specific risk factors to meet the demand of reducing Shigella morbidity and mortality.

Effects of temperature on incidence of bacillary dysentery in a temperate continental arid climate city in northwest China.

The effect of ambient temperature on health continues to draw more and more attention with the global warming. Bacillary dysentery (BD) is a major global environmental health issue and affected by temperature and other environmental variables. In the current study, we evaluated the effect of temperature on the incidence of BD from January 1st, 2008 to December 31st, 2011 in Jiayuguan, a temperate continental arid climate city in the Hexi Corridor of northwest China. A distributed lag non-linear model (DLNM) was performed to evaluate the lag effect of temperature on BD up to 30 days. Results showed the risk of BD increased with temperature significantly, especially after 8°C. The maximum risk of BD was observed at extreme high temperature (29°C). The effect of temperature on BD risk was significantly divided into short-term effect at lag 5 days and long-term effect at lag 30 days. Age ≤ 15 years were most affected by high temperature. The maximum cumulative risk for lag 30 days (25.8, 95% CIs: 11.8-50.1) was observed at 29°C. Age ≤ 15 years and females showed short-term effect at lag 5 days and long-term effect at lag 30 days, while age > 15 years and males showed acute short-term effect at lag 0 and light long-term effect at lag 16 days.

Effects of daily mean temperature and other meteorological variables on bacillary dysentery in Beijing-Tianjin-Hebei region, China.

BackgroundAlthough previous studies have shown that meteorological factors such as temperature are related to the incidence of bacillary dysentery (BD), researches about the non-linear and interaction effect among meteorological variables remain limited. The objective of this study was to analyze the effects of temperature and other meteorological variables on BD in Beijing-Tianjin-Hebei region, which is a high-risk area for BD distribution.MethodsOur study was based on the daily-scale data of BD cases and meteorological variables from 2014 to 2019, using generalized additive model (GAM) to explore the relationship between meteorological variables and BD cases and distributed lag non-linear model (DLNM) to analyze the lag and cumulative effects. The interaction effects and stratified analysis were developed by the GAM.ResultsA total of 147,001 cases were reported from 2014 to 2019. The relationship between temperature and BD was approximately liner above 0 °C, but the turning point of total temperature effect was 10 °C. Results of DLNM indicated that the effect of high temperature was significant on lag 5d and lag 6d, and the lag effect showed that each 5 °C rise caused a 3% [Relative risk (RR) = 1.03, 95% Confidence interval (CI): 1.02–1.05] increase in BD cases. The cumulative BD cases delayed by 7 days increased by 31% for each 5 °C rise in temperature above 10 °C (RR = 1.31, 95% CI: 1.30–1.33). The interaction effects and stratified analysis manifested that the incidence of BD was highest in hot and humid climates.ConclusionsThis study suggests that temperature can significantly affect the incidence of BD, and its effect can be enhanced by humidity and precipitation, which means that the hot and humid environment positively increases the incidence of BD.Supplementary informationThe online version contains supplementary material available at https://doi.org/10.1265/ehpm.21-00005.

The exposure-response association between humidex and bacillary dysentery: A two-stage time series analysis of 316 cities in mainland China

BackgroundMany studies have reported the interactive effects between relative humidity and temperature on infectious diseases. However, evidence regarding the combined effects of relative humidity and temperature on bacillary dysentery (BD) is limited, especially for large-scale studies. To address this research need, humidex was utilized as a comprehensive index of relative humidity and temperature. We aimed to estimate the effect of humidex on BD across mainland China, evaluate its heterogeneity, and identify potential effect modifiers. MethodsDaily meteorological and BD surveillance data from 2014 to 2016 were obtained for 316 prefecture-level cities in mainland China. Humidex was calculated on the basis of relative humidity and temperature. A multicity, two-stage time series analysis was then performed. In the first stage, a common distributed lag non-linear model (DLNM) was established to obtain city-specific estimates. In the second stage, a multivariate meta-analysis was conducted to pool these estimates, assess the significance of heterogeneity, and explore potential effect modifiers. ResultsThe pooled cumulative estimates showed that humidex could promote the transmission of BD. The exposure-response relationship was nearly linear, with a maximum cumulative relative risk (RR) of 1.45 [95% confidence interval (CI): 1.29–1.63] at a humidex value of 40.94. High humidex had an acute adverse effect on BD. The humidex-BD relationship could be modified by latitude, urbanization rate, the natural growth rate of population, and the number of primary school students per thousand persons. ConclusionsHigh humidex could increase the risk of BD incidence. Thus, it is suitable to incorporate humidex as a predictor into the early warning system of BD and to inform the general public in advance to be cautious when humidex is high. This is especially true for regions with higher latitude, higher urbanization rates, lower natural growth rates of population, and lower numbers of primary school students per thousand persons.

Spatial heterogeneity of bacillary dysentery and the impact of temperature in the Beijing-Tianjin-Hebei region of China.

Previous studies indicate that the incidence of bacillary dysentery is closely related to meteorological factors. However, the impact of temperature and the spatial heterogeneity of the disease in regions of unbalanced socioeconomic development remains unclear. Therefore, this research collected data for 29,639 daily bacillary dysentery cases in children under 5 years of age, as well as the meteorological variables from China's Beijing-Tianjin-Hebei region, to analyze the spatial pattern of bacillary dysentery and reveal its nonlinear association with temperature. The SatScan method was employed first, to detect the spatial heterogeneity of the disease risk, and then the distributed lag nonlinear model (DLNM) was used to analyze the relationships between the daily minimum, mean, and maximum temperatures and bacillary dysentery in the stratified heterogeneous regions. The results indicated that bacillary dysentery incidence presented statistically significant spatial heterogeneity. The area of highest risk was found to be Beijing and its neighboring regions, which have high population densities. There was also a positive association between bacillary dysentery and temperature. Hotter temperatures were accompanied by higher relative risks. In the most likely spatial cluster region, the excess risk (ER) values for a 1°C rise in minimum, mean, and maximum temperatures above the median were 4.65%, 11.30%, and 19.21%, respectively. The effect of temperature on bacillary dysentery peaked at a lag of 3 to 4 days. The findings of this study will aid risk assessments and early warning systems for bacillary dysentery.

Associations between floods and bacillary dysentery cases in main urban areas of Chongqing, China, 2005\u20132016: a retrospective study

BackgroundUnderstanding the association between floods and bacillary dysentery (BD) incidence is necessary for us to assess the health risk of extreme weather events. This study aims at exploring the association between floods and daily bacillary dysentery cases in main urban areas of Chongqing between 2005 and 2016 as well as evaluating the attributable risk from floods.MethodsThe association between floods and daily bacillary dysentery cases was evaluated by using distributed lag non-linear model, controlling for meteorological factors, long-term trend, seasonality, and day of week. The fraction and number of bacillary dysentery cases attributable to floods was calculated. Subgroup analyses were conducted to explore the association across age, gender, and occupation.ResultsAfter controlling the impact of temperature, precipitation, relative humidity, long-term trend, and seasonality, a significant lag effect of floods on bacillary dysentery cases was found at 0-day, 3-day, and 4-day lag, and the cumulative relative risk (CRR) over a 7-lag day period was 1.393 (95%CI 1.216–1.596). Male had higher risk than female. People under 5 years old and people aged 15–64 years old had significantly higher risk. Students, workers, and children had significantly higher risk. During the study period, based on 7-lag days, the attributable fraction of bacillary dysentery cases due to floods was 1.10% and the attributable number was 497 persons.ConclusionsThis study confirms that floods can increase the risk of bacillary dysentery incidence in main urban areas of Chongqing within an accurate time scale, the risk of bacillary dysentery caused by floods is still serious. The key population includes male, people under 5 years old, students, workers, and children. Considering the lag effect of floods on bacillary dysentery, the government and public health emergency departments should advance to the emergency health response in order to minimize the potential risk of floods on public.

Features of the Incidence of Shigellosis in the Karachay-Cherkess Republic in 2005–2019

Introduction: In the Karachay-Cherkess Republic (KCR), dysentery and salmonellosis rank high in the etiological structure of intestinal infections and arose interest in studying the incidence of shigellosis in the republic. Our objective was to analyze the incidence of bacillary dysentery, to study Shigella landscape in the territory of the KCR in 2005–2019, and to compare the findings with similar variables in other regions of the Russian Federation. Materials and methods: We analyzed data of the Center for Hygiene and Epidemiology in the Karachay-Cherkess Republic on the incidence of shigellosis and Shigella isolates obtained from human stool samples in the KCR in 2005–2019 and compared them with available results of similar studies conducted in other parts of the country. Results: When analyzing the curves of the incidence of dysentery in the KCR and the Russian Federation, we found that they were asynchronous. In the KCR, the curve rose twice (in 2005–2006 and 2011–2014), while in the Russian Federation, the incidence rates demonstrated a gradual decrease. Over the whole observation period, only in 2018–2019 the incidence of shigellosis in Karachay-Cherkessia was 1.3–1.8 times lower than in the country as a whole. We also established that, in contrast to the Russian Federation, Shigella sonnei represented by the biochemical variant IIg prevailed in the structure of shigellosis in the republic. The analysis of the relationship between the number of detected samples of dairy products of poor microbial quality and the incidence rate of Sonne dysentery showed that those two variables did not always correlate. Molecular genotyping of Shigella sonnei strains by pulsed-field gel electrophoresis (PFGE) allowed us to assume the imported nature of the pathogen. The import could have occurred during the Hajj to Mecca and Medina of KCR residents in 2012. Conclusion: Shigella sonnei strains differing in the presence of tetracycline and chloramphenicol (levomycetin) resistance determinants are circulating in Karachay-Cherkessia. No bacteria resistant to ciprofloxacin were isolated in the republic in 2005–2019.

Real-time forecasting and early warning of bacillary dysentery activity in four meteorological and geographic divisions in China

BackgroundAccurate and timely forecasts of bacillary dysentery (BD) incidence can be used to inform public health decision-making and response preparedness. However, our ability to detect BD dynamics and outbreaks remains limited in China. ObjectivesThis study aims to explore the impacts of meteorological factors on BD transmission in four representative regions in China and to forecast weekly number of BD cases and outbreaks. MethodsWeekly BD and meteorological data from 2014 to 2016 were collected for Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China). A boosted regression tree (BRT) model was conducted to assess the impacts of meteorological factors on BD transmission. Then a real-time forecast and early warning model based on BRT was developed to track the dynamics of BD and detect the outbreaks. The forecasting methodology was compared with generalized additive model (GAM) and seasonal autoregressive integrated moving average model (SARIMA) that have been used to model the BD case data previously. ResultsAmbient temperature was the most important meteorological factor contributing to the transmission of BD (80.81%–92.60%). A positive effect of temperature was observed when weekly mean temperature exceeded 4 °C, −3 °C, 9 °C and 16 °C in Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China), respectively. BD incidence (Beijing and Shenyang) in temperate cities was more sensitive to high temperature than that in subtropical cities (Chongqing and Shenzhen). The dynamics and outbreaks of BD can be accurately forecasted and detected by the BRT model. Compared to GAM and SARIMA, BRT model showed more accurate forecasting for 1-, 2-, 3-weeks ahead forecasts in Beijing, Shenyang and Shenzhen. ConclusionsTemperature plays the most important role in weather-attributable BD transmission. The BRT model achieved a better performance in comparison with GAM and SARIMA in most study cities, which could be used as a more accurate tool for forecasting and outbreak alert of BD in China.

Spatiotemporal variations in the incidence of bacillary dysentery and long-term effects associated with meteorological and socioeconomic factors in China from 2013 to 2017

Bacillary dysentery is a global public health problem that exhibits manifest spatiotemporal heterogeneity. However, long-term variations and regional determinant factors remain unclear. In this study, the Bayesian space-time hierarchy model was used to identify the long-term spatiotemporal heterogeneity of the incidence of bacillary dysentery and quantify the associations of meteorological factors with the incidence of bacillary dysentery in northern and southern China from 2013 to 2017. GeoDetector was used to quantify the determinant powers of socioeconomic factors in the two regions. The results showed that the incidence of bacillary dysentery peaked in summer (June to August), indicating temporal seasonality. Geographically, the hot spots (high-risk areas) were distributed in northwestern China (Xinjiang, Gansu, and Ningxia) and northern China (including Beijing, Tianjin, and Hebei), whereas the cold spots (low-risk areas) were concentrated in southeastern China (Jiangsu, Zhejiang, Fujian, and Guangdong). Moreover, significant regional differences were found among the meteorological and socioeconomic factors. Average temperature was the dominant meteorological factor in both northern and southern China. In northern and southern China, a 1 °C increase in the average temperature led to an increase of 1.01% and 4.26% in bacillary dysentery risk, respectively. The dominant socioeconomic factors in northern and southern China were per capita gross domestic product and the number of health technicians, with q statistic values of 0.81 and 0.49, respectively. These findings suggest that hot, moist, and overcrowded environments or poor health conditions increase the risk of bacillary dysentery. This study provides suggestions and serves as a basis for surveillance efforts. Further, the suggestions may aid in the control of bacillary dysentery and in the implementation of disease prevention policies.

The application of spatial empirical Bayesian smoothing method in spatial analysis of bacillary dysentery: A case study in Yudu County, Jiangxi Province

Bacillary dysentery (BD) has become one of the major public health threats to the sustainable development of human beings. The primary objective of this paper is to validate the effectiveness of applying spatial empirical Bayesian smoothing (SEBS) method in spatial analysis of BD in Yudu County, Jiangxi Province. By using SEBS method in calculating BD incidence, we compared the raw incidence data and smoothed incidence data. Spatial distribution map and global autocorrelation analysis were adopted to explore the effect of SEBS method in BD analysis. The result showed that SEBS method provided a stable incidence estimate in epidemic research. The proposed method could be used as an effective tool for studying the spatial distribution of BD, especially in town level study.

Epidemiological characteristics of bacillary dysentery from 2009 to 2016 and its incidence prediction model based on meteorological factors

BackgroundThis study aimed to analyse the epidemiological characteristics of bacillary dysentery (BD) caused by Shigella in Chongqing, China, and to establish incidence prediction models based on the correlation between meteorological factors and BD, thus providing a scientific basis for the prevention and control of BD.MethodsIn this study, descriptive methods were employed to investigate the epidemiological distribution of BD. The Boruta algorithm was used to estimate the correlation between meteorological factors and BD incidence. The genetic algorithm (GA) combined with support vector regression (SVR) was used to establish the prediction models for BD incidence.ResultsIn total, 68,855 cases of BD were included. The incidence declined from 36.312/100,000 to 23.613/100,000, with an obvious seasonal peak from May to October. Males were more predisposed to the infection than females (the ratio was 1.118:1). Children < 5 years old comprised the highest incidence (295.892/100,000) among all age categories, and pre-education children comprised the highest proportion (34,658 cases, 50.335%) among all occupational categories. Eight important meteorological factors, including the highest temperature, average temperature, average air pressure, precipitation and sunshine, were correlated with the monthly incidence of BD. The obtained mean absolute percent error (MAPE), mean squared error (MSE) and squared correlation coefficient (R2) of GA_SVR_MONTH values were 0.087, 0.101 and 0.922, respectively.ConclusionFrom 2009 to 2016, BD incidence in Chongqing was still high, especially in the main urban areas and among the male and pre-education children populations. Eight meteorological factors, including temperature, air pressure, precipitation and sunshine, were the most important correlative feature sets of BD incidence. Moreover, BD incidence prediction models based on meteorological factors had better prediction accuracies. The findings in this study could provide a panorama of BD in Chongqing and offer a useful approach for predicting the incidence of infectious disease. Furthermore, this information could be used to improve current interventions and public health planning.

Effects of ambient temperature on bacillary dysentery: A multi-city analysis in Anhui Province, China

BackgroundRising ambient temperature is expected to increase incidence of bacillary dysentery (BD), but few studies have compared the temperature-BD effects of different age groups and cities in China, especially in a multi-city setting. ObjectivesWe used city-specific data including BD cases and meteorological variables to determine the relationship between BD incidence and temperature at provincial level. MethodsWeekly BD disease surveillance data and meteorological variables were collected in all 16 prefecture-level cities in Anhui Province of China. Firstly, city-specific weekly mean temperature-BD incidence associations were estimated with Distributed Lag Nonlinear Model (DLNM). Secondly, city-specific estimates were pooled at province-level through multivariate meta-analysis. Also, we conducted subgroup analyses for ages (children <5 years old and population of other ages) and urbanization of cities (high and low level), respectively. ResultsIn Anhui, BD morbidity risk increased with increasing weekly mean temperature. Relative risks (RR) at the 90th percentile (27.5 °C) versus the 50th percentile (17 °C) of weekly mean temperature were 1.42 (95% confidence interval (CI): 1.16, 1.75) and 2.02 (95% CI: 1.76, 2.32) for children <5 and population of other ages, respectively. The relative risk of high temperature on other ages group was higher than that of children under five years old (p = 0.006). Children under 5 in high urbanized cities appeared to be more vulnerable to the effects of ambient high temperature (RR: 1.56, 95% CI: 1.20, 1.92) than in low urbanized cities (RR: 1.01, 95% CI: 0.70, 1.46), the difference between two intervals was statistically significant (p = 0.044). ConclusionsThis study suggests that high temperatures may be an important trigger of BD incidence, and especially lead to a substantial burden of BD for high urbanized cities in Anhui Province of China.

Spatiotemporal Characteristics of Bacillary Dysentery from 2005 to 2017 in Zhejiang Province, China

Background: This study aimed to analyze the epidemiological and spatiotemporal characteristics of bacillary dysentery in Zhejiang Province and to provide the basis for its monitoring, prevention and control. Methods: This study included cases registered in China Information System for Diseases Control and Prevention from 1 January 2005 to 31 December 2017 in Zhejiang. Descriptive methods were employed to investigate the long trend of this disease: gender distribution, high-risk population, seasonality, and circular distribution was explored to detect the peak period; incidence maps were made to show the incidence trend of disease at county level; spatial autocorrelation was explored and the regions with autocorrelation were detected; and spatiotemporal scan was conducted to map out the high-risk regions of disease and how long they lasted. Statistical significance was assumed at p value of <0.05. Results: A total of 105,577 cases of bacillary dysentery were included, the incidence declining sharply from 45.84/100,000 to 3.44/100,000 with an obvious seasonal peak from July to October. Males were more predisposed to the infection than females. Pre-education children had the highest proportion among all occupation categories. Incidence in all age groups were negatively correlated with the year (p < 0.001), and the incidences were negatively correlated with the age groups in 2005–2008 (p = 0.022, 0.025, 0.044, and 0.047, respectively). Local autocorrelation showed that counties in Hangzhou were high-risk regions of bacillary dysentery. The spatiotemporal scan indicated that all clusters occurred before 2011, and the most likely cluster for disease was found in Hangzhou, Jiaxing and Huzhou. Conclusions: The incidence of bacillary dysentery in Zhejiang from 2005 to 2017 featured spatiotemporal clustering, and remained high in some areas and among the young population. Findings in this study serve as a panorama of bacillary dysentery in Zhejiang and provide useful information for better interventions and public health planning.

Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015

Objective: To analyze the distribution characteristics of bacillary dysentery in Beijing during 2004-2015 and evaluate the influence of meteorological factors on the temporal and spatial distribution of bacillary dysentery. Methods: The incidence data of bacterial dysentery and meteorological data in Beijing from 2004 to 2015 were collected. Descriptive epidemiological analysis was conducted to study the distribution characteristics of bacterial dysentery. Linear correlation analysis and multiple linear regression analysis were carried out to investigate the relationship between the incidence of bacillary dysentery and average precipitation, average air temperature, sunshine hours, average wind speed, average air pressure, gale and rain days. Results: A total of 280 704 cases of bacterial dysentery, including 36 deaths, were reported from 2004 to 2015 in Beijing, the average annual incidence was 130.15/100 000. The annual incidence peak was mainly between May and October, the cases occurred during this period accounted for 80.75% of the total, and the incidence was highest in age group 0 year. The population distribution showed that most cases were children outside child care settings and students, and the sex ratio of the cases was 1.22∶1. The reported incidence of bacillary dysentery was positively associated with average precipitation, average air temperature and rain days with the correlation coefficients of 0.931, 0.878 and 0.888, but it was negatively associated with the average pressure, the correlation coefficient was -0.820. Multiple linear regression equation for fitting analysis of bacillary dysentery and meteorological factors was Y=3.792+0.162X(1). Conclusion: The reported incidence of bacillary dysentery in Beijing was much higher than national level. The annual incidence peak was during July to August, and the average precipitation was an important meteorological factor influencing the incidence of bacillary dysentery.

The relationship between meteorological factors and the risk of bacillary dysentery in Hunan Province, China

Meteorological factors are known to influence the morbidity of bacillary dysentery in humans in a number of different regions. To investigate the effect of meteorological factors on the incidence of this disease in the Hunan Province of China, Xiangxi, the region with the highest annual average incidence of bacillary dysentery in the Hunan province from 2005 to 2010 (44.07 cases per 100 000 people) was selected as the area of study, based on spatial descriptive analysis. Spearman correlation analysis showed that average temperature (without lag), relative humidity (with a 1‐month lag), rainfall (with a 2‐month lag), hours of sunshine (without lag), and air pressure (with a 2‐month lag) were all significantly correlated with the number of dysentery cases in Xiangxi. Multivariate analysis showed that average temperature, relative humidity, rainfall, and hours of sunshine appeared to increase the incidence of dysentery cases in Xiangxi (0.05–2.72%). Multivariate Poisson regression showed no correlation between air pressure and bacillary dysentery incidence. Average temperature was found to be the most important of the meteorological factors considered (it was found that a 1 degC rise in temperature corresponds to a 2.72% increase in the number of cases of bacillary dysentery).

Temporal-spatial analysis of bacillary dysentery in the Three Gorges Area of China, 2005-2016

Objective: To analyze the spatial and temporal distributions of bacillary dysentery in Chongqing, Yichang and Enshi (the Three Gorges Area) from 2005 to 2016, and provide evidence for the disease prevention and control. Methods: The incidence data of bacillary dysentery in the Three Gorges Area during this period were collected from National Notifiable Infectious Disease Reporting System. The spatial-temporal scan statistic was conducted with software SaTScan 9.4 and bacillary dysentery clusters were visualized with software ArcGIS 10.3. Results: A total of 126 196 cases were reported in the Three Gorges Area during 2005-2016, with an average incidence rate of 29.67/100 000. The overall incidence was in a downward trend, with an average annual decline rate of 4.74%. Cases occurred all the year round but with an obvious seasonal increase between May and October. Among the reported cases, 44.71% (56 421/126 196) were children under 5-year-old, the cases in children outside child care settings accounted for 41.93% (52 918/126 196) of the total. The incidence rates in districts of Yuzhong, Dadukou, Jiangbei, Shapingba, Jiulongpo, Nanan, Yubei, Chengkou of Chongqing and districts of Xiling and Wujiagang of Yichang city of Hubei province were high, ranging from 60.20/100 000 to 114.81/100 000. Spatial-temporal scan statistic for the spatial and temporal distributions of bacillary dysentery during this period revealed that the temporal distribution was during May-October, and there were 12 class Ⅰ clusters, 35 class Ⅱ clusters, and 9 clusters without statistical significance in counties with high incidence. All the class Ⅰ clusters were in urban area of Chongqing (Yuzhong, Dadukou, Jiangbei, Shapingba, Jiulongpo, Nanan, Beibei, Yubei, Banan) and surrounding counties, and the class Ⅱ clusters transformed from concentrated distribution to scattered distribution. Conclusions: Temporal and spatial cluster of bacillary dysentery incidence existed in the three gorges area during 2005-2016. It is necessary to strengthen the bacillary dysentery prevention and control in urban areas of Chongqing and Yichang.

Influence of humidex on incidence of bacillary dysentery in Hefei: a time-series study

Objective: To investigate the effect of humidex combined with mean temperature and relative humidity on the incidence of bacillary dysentery in Hefei. Methods: Daily counts of bacillary dysentery cases and weather data in Hefei were collected from January 1, 2006 to December 31, 2013. Then, the humidex was calculated from temperature and relative humidity. A Poisson generalized linear regression combined with distributed lag non-linear model was applied to analyze the relationship between humidex and the incidence of bacillary dysentery, after adjusting for long-term and seasonal trends, day of week and other weather confounders. Stratified analyses by gender, age and address were also conducted. Results: The risk of bacillary dysentery increased with the rise of humidex. The adverse effect of high humidex (90 percentile of humidex) appeared in 2-days lag and it was the largest at 4-days lag (RR=1.063, 95%CI: 1.037-1.090). Subgroup analyses indicated that all groups were affected by high humidex at lag 2-5 days. Conclusion: High humidex could significantly increase the risk of bacillary dysentery, and the lagged effects were observed.

Spatial-temporal detection of risk factors for bacillary dysentery in Beijing, Tianjin and Hebei, China

BackgroundBacillary dysentery is the third leading notifiable disease and remains a major public health concern in China. The Beijing–Tianjin–Hebei urban region is the biggest urban agglomeration in northern China, and it is one of the areas in the country that is most heavily infected with bacillary dysentery. The objective of the study was to analyze the spatial-temporal pattern and to determine any contributory risk factors on the bacillary dysentery.MethodsBacillary dysentery case data from 1 January 2012 to 31 December 2012 in Beijing–Tianjin– Hebei were employed. GeoDetector method was used to determine the impact of potential risk factors, and to identify regions and seasons at high risk of the disease.ResultsThere were 36,472 cases of bacillary dysentery in 2012 in the study region. The incidence of bacillary dysentery varies widely amongst different age groups; the higher incidence of bacillary dysentery mainly occurs in the population under the age of five. Bacillary dysentery presents apparent seasonal variance, with the highest incidence occurring from June to September. In terms of the potential meteorological risk factors, mean temperature, relative humidity, precipitation, mean wind speed and sunshine hours explain the time variant of bacillary dysentery at 83%, 31%, 25%, 17% and 13%, respectively. The interactive effect between temperature and humidity has an explanatory power of 87%, indicating that a hot and humid environment is more likely to lead to the occurrence of bacillary dysentery. Socio-economic factors affect the spatial distribution of bacillary dysentery. The top four factors are age group, per capita GDP, population density and rural population proportion, and their determinant powers are 61%, 27%, 25% and 21%, respectively. The interactive effect between age group and the other factors accounts for more than 60% of bacillary dysentery transmission.ConclusionsBacillary dysentery poses a higher risk in the population of children. It is affected by meteorological and socio-economic factors, and it is necessary to pay more attention to the meteorological period and situation, particularly in period with high temperature and humidity, as well as places in urban areas with high population density, and a low proportion of rural population.

Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).

ObjectivesInfluence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model.MethodsA time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970–2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE).ResultsFirstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004–0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009–0.037) displayed the highest prediction accuracy.ConclusionsThe ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.