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Background: In China, bacillary dysentery (BD) is the third most frequently reported infectious disease, with the greatest annual incidence rate of 38.03 cases per 10,000 person-years. It is well acknowledged that temperature is associated with BD and the previous studies of temperature-BD association in different provinces of China present a considerable heterogeneity, which may lead to an inaccurate estimation for a region-specific association and incorrect attributable burdens. Meanwhile, the common methods for multi-city studies, such as stratified strategy and meta-analysis, have their own limitations in handling the heterogeneity. Therefore, it is necessary to adopt an appropriate method considering the spatial autocorrelation to accurately characterize the spatial distribution of temperature-BD association and obtain its attributable burden in 31 provinces of China. Methods: A novel three-stage strategy was adopted. In the first stage, we used the generalized additive model (GAM) model to independently estimate the province-specific association between monthly average temperature (MAT) and BD. In the second stage, the Leroux-prior-based conditional autoregression (LCAR) was used to spatially smooth the association and characterize its spatial distribution. In the third stage, we calculate the attribute BD cases based on a more accurate estimation of association. Results: The smoothed association curves generally show a higher relative risk with a higher MAT, but some of them have an inverted "V" shape. Meanwhile, the spatial distribution of association indicates that western provinces have a higher relative risk of MAT than eastern provinces with 0.695 and 0.645 on average, respectively. The maximum and minimum total attributable number of cases are 224,257 in Beijing and 88,906 in Hainan, respectively. The average values of each province in the eastern, western, and central areas are approximately 40,991, 42,025, and 26,947, respectively. Conclusion: Based on the LCAR-based three-stage strategy, we can obtain a more accurate spatial distribution of temperature-BD association and attributable BD cases. Furthermore, the results can help relevant institutions to prevent and control the epidemic of BD efficiently.

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This study aimed to ascertain the delayed effects of various exposure temperatures on infectious diarrhea. We performed a Bayesian random-effects network meta-analysis to calculate relative risks (RR) with 95 % confidence intervals (95 % CI). The heterogeneity was analyzed by subgroup analysis. There were 25 cross-sectional studies totaling 6858735 patients included in this analysis, with 12 articles each investigating the effects of both hyperthermia and hypothermia. Results revealed that both high temperature (RRsingle = 1.22, 95%CI:1.04-1.44, RRcum = 2.96, 95%CI:1.60-5.48, P < 0.05) and low temperature (RRsingle = 1.17, 95%CI:1.02-1.37, RRcum = 2.19, 95%CI:1.33-3.64, P < 0.05) significantly increased the risk of infectious diarrhea, while high temperature caused greater. As-sociations with strengthening in bacillary dysentery were found for high temperatures (RRcum = 2.03, 95%CI:1.41-3.01, P < 0.05; RRsingle = 1.17, 95%CI:0.90-1.62, P > 0.05), while the statistical significance of low temperatures in lowering bacterial dysentery had vanished. This investigation examined that high temperature and low temperature were the conditions that posed the greatest risk for infectious diarrhea. This research offers fresh perspectives on preventing infectious diarrhea and will hopefully enlighten future studies on the impact of temperature management on infectious diarrhea.

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Shigella spp. are the causative agent of shigellosis (or bacillary dysentery), a diarrhoeal disease characterized for the bacterial invasion of gut epithelial cells. Among the 4 species included in the genus, Shigella flexneri is principally responsible for the disease in the developing world while Shigella sonnei is the main causative agent in high-income countries. Remarkably, as more countries improve their socioeconomic conditions, we observe an increase in the relative prevalence of S. sonnei. To date, the reasons behind this change in aetiology depending on economic growth are not understood. S. flexneri has been widely used as a model to study the pathogenesis of the genus, but as more research data are collected, important discrepancies with S. sonnei have come to light. In comparison to S. flexneri, S. sonnei can be differentiated in numerous aspects; it presents a characteristic O-antigen identical to that of one serogroup of the environmental bacterium Plesiomonas shigelloides, a group 4 capsule, antibacterial mechanisms to outcompete and displace gut commensal bacteria, and a poorer adaptation to an intracellular lifestyle. In addition, the World Health Organization (WHO) have recognized the significant threat posed by antibiotic-resistant strains of S. sonnei, demanding new approaches. This review gathers knowledge on what is known about S. sonnei within the context of other Shigella spp. and aims to open the door for future research on understanding the increasing spread of this pathogen.

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While the incidence of shigellosis has decreased in developed nations due to improved living conditions and healthcare systems, it remains prevalent in economically developing regions. In recent years, a resurgence of shigellosis has been observed in the United States, Europe, and Taiwan, primarily among men having sex with men and people living with human immunodeficiency virus, along with a rise in antimicrobial resistance. This study aims to review the historical epidemiological trends and drug resistance in shigellosis, with a focus on Taiwan. A comprehensive search was conducted using various databases and sources, including non-English literature in Japanese and Chinese. In developed countries, Shigella sonnei and Shigella flexneri are the most common species, while Shigella dysenteriae infections are sporadic. In Taiwan, the classification and prevalence of Shigella species have evolved over time, with S. flexneri and S. sonnei being the predominant strains. Fluoroquinolone resistance and azithromycin non-susceptibility are the ongoing threat. In conclusion, shigellosis remains a significant global health concern, with recent increases in certain populations and antimicrobial resistance. Further research is necessary to understand the clinical significance and risk factors associated with asymptomatic carriers and to assess the impact of behavioral modifications and interventions in high-risk populations.

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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.

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OBJECTIVES: At present, some studies have pointed out several possible climate drivers of bacillary dysentery. However, there is a complex nonlinear interaction between climate drivers and susceptible population in the spread of diseases, which makes it challenging to detect climate drivers at the size of susceptible population. METHODS: By using empirical dynamic modeling (EDM), the climate drivers of bacillary dysentery dynamic were explored in China's five temperature zones. RESULTS: We verified the availability of climate drivers and susceptible population size on bacillary dysentery, and used this information for bacillary dysentery dynamic prediction. Moreover, we found that their respective effects increased with the increase of temperature and relative humidity, and their states (temperature and relative humidity) were different when they reached their maximum effects, and the negative effect between the effect of temperature and disease incidence increased with the change of temperature zone (from temperate zone to warm temperate zone to subtropical zone) and the climate driving effect of the temperate zone (warm temperate zone) was greater than that of the colder (temperate zone) and warmer (subtropics) zones. When we viewed from single temperature zone, the climatic effect arose only when the size of the susceptible pool was large. CONCLUSIONS: These results provide empirical evidence that the climate factors on bacillary dysentery are nonlinear, complex but dependent on the size of susceptible populations and different climate scenarios.

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Objective To analyze the epidemiological characteristics of bacillary dysentery in Xinjiang from 2005-2018, to explore the feasibility and applicability of seasonal autoregressive moving average model to predict the incidence pattern of bacillary dysentery in Xinjiang, and to provide a scientific basis for decision-making in the prevention and control of bacillary dysentery. Methods Descriptive analysis was used to analyze the epidemiological characteristics of bacillary dysentery, and Python software was used to construct a SARIMA model and predict the incidence trend. Results The average annual reported incidence rate of bacillary dysentery in Xinjiang from 2005-2018 was 35.71/100 000, with peak incidence concentrated in June-October. The difference in the incidence rate of bacillary dysentery among the age groups was statistically significant (χ2=145605.90, P60 years age groups. The resulting model was SARIMA (0,1,2)(0,1,1)12 with all parameters statistically significant (P12 model has good accuracy in predicting the incidence of bacillary dysentery in Xinjiang and can be used for medium-term prediction of the disease.

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Bacillary dysentery is a type of dysentery and a severe form of shigellosis. This dysentery is usually restricted to Shigella infection, but Salmonella enterica and enteroinvasive Escherichia coli strains are also known as this infection's causative agents. The emergence of drug-resistant, bacillary dysentery-causing pathogens is a global burden, especially for developing countries with poor hygienic environments. This study aimed to isolate, identify, and determine the drug-resistant pattern of bacillary dysentery-causing pathogens from the stool samples of the Kushtia region in Bangladesh. Hence, biochemical tests, serotyping, molecular identification, and antibiotic profiling were performed to characterize the pathogens. Among one hundred fifty (150) stool samples, 18 enteric bacterial pathogens were isolated and identified, where 12 were Shigella strains, 5 were S. enterica sub spp. enterica strains and one was the E.coli strain. Among 12 Shigella isolates, 8 were Shigella flexneri 2a serotypes, and 4 were Shigella sonnei Phage-II serotypes. Except for three Salmonella strains, all isolated strains were drug-resistant (83%), whereas 50% were multidrug-resistant (MDR), an alarming issue for public health. In antibiotic-wise analysis, the isolated pathogens showed the highest resistance against nalidixic acid (77.78%), followed by tetracycline (38.89%), kanamycin (38.89%), amoxicillin (27.78%), streptomycin (27.78%), cefepime (22.22%), ceftriaxone (22.22%), ampicillin (16.67%), ciprofloxacin (16.67%), and chloramphenicol (16.67%). The existence of MDR organisms that cause bacillary dysentery in the Kushtia area would warn the public to be more health conscious, and physicians would administer medications cautiously. The gradual growth of MDR pathogenic microorganisms needs immediate attention, and the discovery of effective medications must take precedence. Supplementary information: The online version contains supplementary material available at 10.1007/s11756-022-01299-x.

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BACKGROUND: High atmospheric temperature has been associated with the occurrence of bacillary dysentery (BD). Recent studies have suggested that hot extremes may influence health outcomes, however, none have examined the association between hot extremes and BD risk, especially at the national level. OBJECTIVES: To assess the effect and attributable burden of hot extremes on BD cases and to identify populations at high risk of BD. METHODS: Daily incident BD data of 31 provincial capital cities from 2010 to 2018 were collected from the Chinese Center for Disease Control and Prevention, weather data was obtained from the fifth generation of the European Re-Analysis Dataset. Three types of hot extremes, including hot day, hot night, and hot day and night, were defined according to single or sequential occurrence of daytime hot and nighttime hot within 24 h. A two-stage analytical strategy combined with distributed lag non-linear models (DLNM) was used to evaluate city-specific associations and national pooled estimates. RESULTS: Hot extremes were significantly associated with the risk of BD on lagged 1-6 days. The overall cumulative relative risk (RR) was 1.136 [95% confidence interval (CI): 1.022, 1.263] for hot day, 1.181 (95% CI: 1.019, 1.369) for hot night, and 1.154 (95% CI: 1.038, 1.283) for hot day and night. Northern residents, females, and children younger than or equal to 14 years old were vulnerable under hot night, southern residents were vulnerable under hot day, and males were vulnerable under hot day and night. 1.854% (95% CI: 1.294%, 2.205%) of BD cases can be attributable to hot extremes, among which, hot night accounted for a large proportion. CONCLUSIONS: Hot extremes may significantly increase the incidence risk and disease burden of BD. Type-specific protective measures should be taken to reduce the risk of BD, especially in those we found to be particularly vulnerable.

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BACKGROUND: Although 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. METHODS: Our 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. RESULTS: A 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. CONCLUSIONS: This 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.

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Shigellosis appears to increase in certain at-risk populations in developed countries. Based on the nationwide surveillance, the annual incidence of shigellosis in Taiwan (1999-2019) was 0.38-5.77 cases per 100,000 people. Indigenous shigellosis has mostly affected men who have sex with men (MSM) and people living with HIV (PLWH) since 2015. In this retrospective study, compared with those diagnosed before 2015, indigenous cases diagnosed during 2015-2019 mostly occurred in male adults (96.0% vs 47.1%, P < 0.001), with a longer hospital stay (median 5.0 vs 3.5 days, P = 0.029) and different coinfections. The predominant strains in 2015 and 2016 were ciprofloxacin-resistant Shigella sonnei and azithromycin non-susceptible Shigella flexneri (S. flexneri) 3a, which had been replaced by ciprofloxacin-resistant S. flexneri 2a since 2018. Notably, six indigenous cases were caused by cefotaxime-resistant S. flexneri. Inappropriate use of empiric antibiotic treatment was common. In conclusion, there is an ongoing spread of ciprofloxacin-resistant shigellosis among PLWH and MSM and cefotaxime-resistant S. flexneri is an emerging threat in Taiwan.

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BACKGROUND@#Although 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.@*METHODS@#Our 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.@*RESULTS@#A 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.@*CONCLUSIONS@#This 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.

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Background Climate change leads to frequent heavy rainfall events, and higher incidences of bacillary dysentery after heavy rainfall have been observed. The impacts of heavy rainfall and its antecedent rainfall conditions on the disease are worth paying attention to. Objective To quantitatively analyze how the relationship between heavy rainfall events and bacillary dysentery occurrence is modified by antecedent rainfall conditions in Anhui Province and explore the different moderation effects in urban and rural contexts. Methods CN05.1 meteorological data of Anhui Province and cases of bacillary dysentery of the same area were collected from January 1, 2006 to August 31, 2017. An exposure-response Poisson regression model of heavy rainfall events and the number of daily cases was constructed to explore the moderation effect of antecedent rainfall conditions on the incidence of bacillary dysentery, and further stratified by urban and rural areas. Results This study included 129 459 cases of bacillary dysentery, with a daily average of 30.39. Compared with dry antecedent conditions without heavy rainfall, dry antecedent conditions with heavy rainfall had no obvious different effect on the incidence of bacillary dysentery for the whole province (P>0.05). But wet antecedent conditions significantly increased the risk of bacillary dysentery for the whole province after heavy rainfall (wet antecedent conditions without heavy rainfall: RR=1.281, 95%CI: 1.264-1.298; wet antecedent conditions with heavy rainfall: RR=1.267, 95%CI: 1.167-1.376). After urban and rural stratification, antecedent rainfall conditions also showed a significant moderation effect on the incidence of bacillary dysentery following heavy rainfall events. Compared with dry antecedent conditions without heavy rainfall, dry antecedent conditions with heavy rainfall had no obvious effect on the incidence of bacillary dysentery for the urban and the rural populations (P > 0.05). However, wet antecedent conditions without heavy rainfall (urban: RR=1.391, 95%CI: 1.362-1.421; rural: RR=1.222, 95%CI: 1.201-1.243) and wet antecedent conditions with heavy rainfall (urban: RR=1.364, 95%CI: 1.193-1.559; rural: RR=1.218, 95%CI: 1.098-1.352) significantly increased the risk of bacillary dysentery in both rural and urban areas. Conclusion In the influence of heavy rainfall on the incidence of bacillary dysentery in Anhui Province, antecedent rainfall conditions have a certain moderation effect in the whole province and in both urban and rural areas, and the risk of bacillary dysentery is increased under wet antecedent conditions.

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BACKGROUND: Bacillary dysentery (BD) is a common infectious disease in China and causes enormous economic burdens. The purpose of this study was to describe the epidemiological characteristics of BD and to identify its possible hot spots and potentially high-risk areas in Sichuan province of China. METHODS: In this study, we collected monthly BD incidence reports of 181 counties in Sichuan province, China, from January 2011 to December 2019. Descriptive statistics were used to evaluate the epidemic characteristics of BD. Moran's I index was applied to investigate the yearly patterns of the spatial distribution. And spatio-temporal scanning statistics with the spatial unit set as county and the temporal unit set as month were used to investigate the possible high-risk region. Meanwhile, the circular moving windows were also employed in the spatio-temporal scanning to scan the study areas. RESULTS: The annual incidence of BD ranged between 16.13/100,000 and 6.17/100,000 person-years from 2011 to 2019 in Sichuan. The majority of the cases were children aged 5 years or younger. For the descriptive statistics, a peak from May to October was observed in temporal analysis, the epidemics were mainly concentrated in the northwest and southwest of Sichuan in spatial analysis. After 2016, the scope of BD significantly narrowed and severe epidemic areas were relatively stable. For the spatial autocorrelation analysis, a high global autocorrelation was observed at the county level, and the high-high clusters mainly distributed in the northwest and southwest of Sichuan. For the spatio-temporal scanning, the spatiotemporal clusters of BD occurred every year from 2011 to 2019. The most likely cluster areas mainly distributed in the southwest and northwest of Sichuan at the beginning, and then gradually concentrated in the southwest. The secondary cluster mainly concentrated in the northwest and its surrounding areas. Moreover, the 2nd secondary cluster was relatively small and mainly distributed in the central area. No clusters were noted in eastern Sichuan. CONCLUSIONS: Based on our current analysis, BD is still a common challenge in Sichuan, especially for counties in the southwest and northwest in summer and autumn. More disease prevention and control measures should be taken in such higher-risk susceptible areas at a certain time to allocate the public health resources rationally, and finally reduce the spread of BD.

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BACKGROUND: Many 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. METHODS: Daily 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. RESULTS: The 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. CONCLUSIONS: High 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.

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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.

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BACKGROUND: Understanding 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. METHODS: The 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. RESULTS: After 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. CONCLUSIONS: This 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.

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Bacterial dysentery (BD) brings a major disease burden to developing countries. Exploring the influence of temperature and its interaction with other meteorological factors on BD is significant for the prevention and early warning of BD in the context of climate change. Daily BD cases and meteorological data from 2008 to 2018 were collected in all nine prefecture-level cities in Jilin Province. A one-stage province-level model and a two-stage city-specific multivariate meta-pooled level distributed lag non-linear model were established to explore the correlation between temperature and BD, then the weather-stratified generalised additive model was used to test the interaction. During the study period, a total of 26 971 cases of BD were developed. The one-stage and two-stage cumulative dose-response 'J' curves overlapped, and results showed a positive correlation between temperature and BD with a 1-6 days lag effect. Age group ⩾5 years was found to be more sensitive to the effects. Moreover, there was a significant interaction between temperature, humidity and precipitation (P = 0.004, 0.002, respectively) on BD under high temperature (>0 °C), reminding residents and policymakers to pay attention to the prevention of BD in situations with both high temperature and humidity, high temperature and precipitation during the temperate monsoon climate.

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The association between floods and the risk of dysentery remain controversial. Therefore, we performed a meta-analysis to clarify this relationship. A literature search was performed in PubMed, Web of science, and Embase for relevant articles published up to November 2019. Random-effects model was used to pool relative risks with 95% confidence intervals. The sensitivity analysis was carried out to evaluate the stability of the results. Publication bias was estimated using Egger's test. Eleven studies from 10 articles evaluated the association between floods and the risk of dysentery in China. The pooled RR (95% CI) of dysentery for the flooded time versus non-flooded period was 1.48 (95% CI: 1.14-1.91). Significant association was found in subgroup analysis stratified by dysentery styles [dysentery: 1.61 (95% CI: 1.34-1.93) and bacillary dysentery: 1.46 (95% CI: 1.06-2.01)]. The pooled RR (95%CI) of sensitivity analysis for dysentery was 1.26 (95% CI: 1.05-1.52). No significant publication bias was found in our meta-analysis. This meta-analysis confirms that floods have significantly increased the risk of dysentery in China. Our findings will provide more evidence to reduce negative health outcomes of floods in China.

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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.

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