Spatiotemporal Risk of Bacillary Dysentery and Sensitivity to Meteorological Factors in Hunan Province, China

Using a Leroux-prior-based conditional autoregression-based strategy to map the short-term association between temperature and bacillary dysentery and its attributable burden in China

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.

Antibacterial Activity and Possible Mechanism of Litsea cubeba Essential Oil Against Shigella sonnei and Its Application in Lettuce

Shigella sonnei, the causative agents of bacillary dysentery, remains a significant threat to public health. Litsea cubeba essential oil (LC-EO), one of the natural essential oils, exhibited promising biological activities. In this study, the antibacterial effects and possible mechanisms of LC-EO on S. sonnei and its application in lettuce medium were investigated. The minimum inhibitory concentration (MIC) of LC-EO against S. sonnei ATCC 25931 and CMCC 51592 was 4 and 6 μL/mL, respectively. The LC-EO could inhibit the growth of S. sonnei, and decreased S. sonnei to undetectable levels with 4 μL/mL for 1 h in Luria-Bertani broth. The antibacterial mechanism indicated that after the treatment of LC-EO, the production of reactive oxygen species and the activity of superoxide dismutase were significantly elevated in S. sonnei cells, and eventually led to the lipid oxidation product, the malondialdehyde content that significantly increased. Moreover, LC-EO at 2 MIC could destroy 96.51% of bacterial cell membrane integrity, and made S. sonnei cells to appear wrinkled with a rough surface, so that the intracellular adenosine triphosphate leakage was about 0.352-0.030 μmol/L. Finally, the results of application evaluation indicated that the addition of LC-EO at 4 μL/mL in lettuce leaves and 6 μL/mL in lettuce juice could decrease the number of S. sonnei to undetectable levels without remarkable influence on the lettuce leaf sensory quality. In summary, LC-EO exerted strong antibacterial activity and has the potential to control S. sonnei in food industry.

Shigellosis seasonality and transmission characteristics in different areas of China: A modelling study

Objective

In China, the burden of shigellosis is unevenly distributed, notably across various ages and geographical areas. Shigellosis temporal trends appear to be seasonal. We should clarify seasonal warnings and regional transmission patterns.

Method

This study adopted a Logistic model to assess the seasonality and a dynamics model to compare the transmission in different areas. The next-generation matrix was used to calculate the effective reproduction number (R_eff) to quantify the transmissibility.

Results

In China, the rate of shigellosis fell from 35.12 cases per 100,000 people in 2005 to 7.85 cases per 100,000 people in 2017, peaking in June and August. After simulation by the Logistic model, the ‘peak time’ is mainly concentrated from mid-June to mid-July. China's ‘early warning time’ is primarily focused on from April to May. We predict the ‘peak time’ of shigellosis is the 6.30th month and the ‘early warning time’ is 3.87th month in 2021. According to the dynamics model results, the water/food transfer pathway has been mostly blocked off. The transmissibility of different regions varies greatly, such as the mean R_eff of Longde County (3.76) is higher than Xiamen City (3.15), higher than Chuxiong City (2.52), and higher than Yichang City (1.70).

Conclusion

The ‘early warning time’ for shigellosis in China is from April to May every year, and it may continue to advance in the future, such as the early warning time in 2021 is in mid-March. Furthermore, we should focus on preventing and controlling the person-to-person route of shigellosis and stratified deploy prevention and control measures according to the regional transmission.

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

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.

Supplementary information

The online version contains supplementary material available at https://doi.org/10.1265/ehpm.21-00005.

Temperature and risk of infectious diarrhea: a systematic review and meta-analysis

Infectious diarrhea (ID) is an intestinal infectious disease including cholera, typhoid and paratyphoid fever, bacterial and amebic dysentery, and other infectious diarrhea. There are many studies that have explored the relationship between ambient temperature and the spread of infectious diarrhea, but the results are inconsistent. It is necessary to systematically evaluate the impact of temperature on the incidence of ID. This study was based on the PRISMA statement to report this systematic review. We conducted literature searches from CNKI, VIP databases, CBM, PubMed, Web of Science, Cochrane Library, and other databases. The number registered in PROSPERO is CRD42021225472. After searching a total of 4915 articles in the database and references, 27 studies were included. The number of people involved exceeded 7.07 million. The overall result demonstrated when the temperature rises, the risk of infectious diarrhea increases significantly (RR_cumulative=1.42, 95%CI: 1.07-1.88, RR_single-day=1.08, 95%CI: 1.03-1.14). Subgroup analysis found the effect of temperature on the bacillary dysentery group (RR_cumulative=1.85, 95%CI: 1.48-2.30) and unclassified diarrhea groups (RR_cumulative=1.18, 95%CI: 0.59-2.34). The result of the single-day effect subgroup analysis was similar to the result of the cumulative effect. And the sensitivity analysis proved that the results were robust. This systematic review and meta-analysis support that temperature will increase the risk of ID, which is helpful for ID prediction and early warning in the future.

Spatio-temporal analysis of bacillary dysentery in Sichuan province, China, 2011-2019

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.

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

BACKGROUND

Accurate 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.

OBJECTIVES

This 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.

METHODS

Weekly 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.

RESULTS

Ambient 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.

CONCLUSIONS

Temperature 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.

Transmission pattern of shigellosis in Wuhan City, China: a modelling study

The article aims to estimate and forecast the transmissibility of shigellosis and explore the association of meteorological factors with shigellosis. The mathematical model named Susceptible–Exposed–Symptomatic/Asymptomatic–Recovered–Water/Food (SEIARW) was used to explore the feature of shigellosis transmission based on the data of Wuhan City, China, from 2005 to 2017. The study applied effective reproduction number (R_eff) to estimate the transmissibility. Daily meteorological data from 2008 to 2017 were used to determine Spearman's correlation with reported new cases and R_eff. The SEIARW model fit the data well (χ² = 0.00046, p > 0.999). The simulation results showed that the reservoir-to-person transmission of the shigellosis route has been interrupted. The R_eff would be reduced to a transmission threshold of 1.00 (95% confidence interval (CI) 0.82–1.19) in 2035. Reducing the infectious period to 11.25 days would also decrease the value of R_eff to 0.99. There was a significant correlation between new cases of shigellosis and atmospheric pressure, temperature, wind speed and sun hours per day. The correlation coefficients, although statistically significant, were very low (<0.3). In Wuhan, China, the main transmission pattern of shigellosis is person-to-person. Meteorological factors, especially daily atmospheric pressure and temperature, may influence the epidemic of shigellosis.

Relative transmissibility of shigellosis among male and female individuals: a modeling study in Hubei Province, China

BACKGROUND

Developing countries exhibit a high disease burden from shigellosis. Owing to the different incidences in males and females, this study aims to analyze the features involved in the transmission of shigellosis among male (subscript m) and female (subscript f) individuals using a newly developed sex-based model.

METHODS

The data of reported shigellosis cases were collected from the China Information System for Disease Control and Prevention in Hubei Province from 2005 to 2017. A sex-based Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model was applied to explore the dataset, and a sex-age-based SEIAR model was applied in 2010 to explore the sex- and age-specific transmissions.

RESULTS

From 2005 to 2017, 130 770 shigellosis cases (including 73 981 male and 56 789 female cases) were reported in Hubei Province. The SEIAR model exhibited a significant fitting effect with the shigellosis data (P <  0.001). The median values of the shigellosis transmission were 2.3225 × 10⁸ for SAR_mm (secondary attack rate from male to male), 2.5729 × 10⁸ for SAR_mf, 2.7630 × 10^-8 for SAR_fm, and 2.1061 × 10^-8 for SAR_ff. The top five mean values of the transmission relative rate in 2010 (where the subscript 1 was defined as male and age ≤ 5 years, 2 was male and age 6 to 59 years, 3 was male and age ≥ 60 years, 4 was female and age ≤ 5 years, 5 was female and age 6 to 59 years, and 6 was male and age ≥ 60 years) were 5.76 × 10^-8 for β₆₁, 5.32 × 10^-8 for β₃₁, 4.01 × 10^-8 for β₃₄, 7.52 × 10^-9 for β₆₂, and 6.04 × 10^-9 for β₆₄.

CONCLUSIONS

The transmissibility of shigellosis differed among male and female individuals. The transmissibility between the genders was higher than that within the genders, particularly female-to-male transmission. The most important route in children (age ≤ 5 years) was transmission from the elderly (age ≥ 60 years). Therefore, the greatest interventions should be applied in females and the elderly.

Epidemiological characteristics and transmissibility of shigellosis in Hubei Province, China, 2005 - 2017

BACKGROUND

Shigellosis is one of the main diarrhea diseases in developing countries. However, the transmissibility of shigellosis remains unclear.

METHODS

We used the dataset of shigellosis cases reported between January 2005 and December 2017, from Hubei Province, China. A mathematical model was developed based on the natural history and the transmission mechanism of the disease. By fitting the data using the model, transmission relative rate from person to person (b) and from reservoir to person (bw), and the effective reproduction number (Reff) were estimated. To simulate the contribution of b and bw during the transmission, we performed a "knock-out" simulation in four scenarios: A) b = 0 and bw = 0; B) b = 0; C) bw = 0; D) control (no intervention).

RESULTS

A total of 130,770 shigellosis cases were reported in Hubei province, among which 13 cases were dead. The median annual incidence was 19.96 per 100,000 persons (range: 5.99 per 100,000 persons - 29.47 per 100,000 persons) with a decreased trend (trend χ2 = 25,470.27, P < 0.001). The mean values of b and bw were 0.0898 (95% confidence interval [CI]: 0.0851-0.0946) and 1.1264 × 10- 9 (95% CI: 4.1123 × 10- 10-1.8416 × 10- 9), respectively. The "knock-out" simulation showed that the number of cases simulated by scenario A was almost the same as scenario B, and scenario C was almost the same as scenario D. The mean value of Reff of shigellosis was 1.19 (95% CI: 1.13-1.25) and decreased slightly with a Linear model until it decreased to an epidemic threshold of 0.99 (95% CI: 0.65-1.34) in 2029.

CONCLUSIONS

The incidence of shigellosis is still in high level. The transmissibility of the disease is low in Hubei Province. The transmission would be interrupted in the year of 2029.

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

Background

This 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.

Methods

In 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.

Results

In 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.

Conclusion

From 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.

Spatial-temporal heterogeneity of hand, foot and mouth disease and impact of meteorological factors in arid/ semi-arid regions: a case study in Ningxia, China

Background

The incidence of hand, foot and mouth disease (HFMD) varies over space and time and this variability is related to climate and social-economic factors. Majority of studies on HFMD were carried out in humid regions while few have focused on the disease in arid/semi-arid regions, more research in such climates would potentially make the mechanism of HFMD transmission clearer under different climate conditions.

Methods

In this paper, we explore spatial-temporal distribution of HFMD in Ningxia province, which has an arid/semi-arid climate in northwest China. We first employed a Bayesian space-time hierarchy model (BSTHM) to assess the spatial-temporal heterogeneity of the HFMD cases and its relationship with meteorological factors in Ningxia from 2009 to 2013, then used a novel spatial statistical software package GeoDetector to test the spatial-temporal heterogeneity of HFMD risk.

Results

The results showed that the spatial relative risks in northern part of Ningxia were higher than those in the south. The highest temporal risk of HFMD incidence was in fall season, with a secondary peak in spring. Meteorological factors, such as average temperature, relative humidity, and wind speed played significant roles in the spatial-temporal distribution of HFMD risk.

Conclusions

The study provide valuable information on HFMD distribution in arid/semi-arid areas in northwest China and facilitate understanding of the concentration of HFMD.

Application of kernel smoothing to estimate the spatio-temporal variation in risk of STEC O157 in England

Identifying geographical areas with significantly higher or lower rates of infectious diseases can provide important aetiological clues to inform the development of public health policy and interventions designed to reduce morbidity. We applied kernel smoothing to estimate the spatial and spatio-temporal variation in risk of STEC O157 infection in England between 2009 and 2015, and to explore differences between the residential locations of cases reporting travel and those not reporting travel. We provide evidence that the distribution of STEC O157 infection in England is non-uniform with respect to the distribution of the at-risk population; that the spatial distribution of the three main genetic lineages infecting humans (I, II and I/II) differs significantly and that the spatio-temporal risk is highly dynamic. Our results also indicate that cases of STEC O157 reporting travel within or outside the UK are more likely to live in the south/south-east of the country, meaning that their residential location may not reflect the location of exposure that led to their infection. We suggest that the observed variation in risk reflects exposure to sources of STEC O157 that are geographically prescribed. These differences may be related to a combination of changes in the strains circulating in the ruminant reservoir, animal movements (livestock, birds or wildlife) or the behavior of individuals prior to infection. Further work to identify the importance of behaviours and exposures reported by cases relative to residential location is needed.

Epidemiologic features of shigellosis and associated climatic factors in Taiwan

The consistent, sporadic transmission of shigellosis in Taiwan necessitates an exploration of risk factors for the occurrence of shigellosis. The purpose of this study was to study the epidemiologic characteristics and the relationship between climatic factors and the incidence of shigellosis in Taiwan. We collected data from cases of shigellosis reported to the Taiwan Centers for Disease Control (Taiwan CDC) from 2001 to 2016. Climatic data were obtained from the Taiwan Central Weather Bureau. The relationships between weather variability and the incidence of shigellosis in Taiwan were determined via Poisson regression analyses. During the 16-year study period, a total of 4171 clinical cases of shigellosis were reported to the Taiwan CDC. Among them, 1926 (46.2%) were classified as confirmed cases. The incidence of shigellosis showed significant seasonality, with the majority of cases occurring in summertime (for oscillation, P < .001). The number of shigellosis cases started to increase when temperatures reached 21°C (r = 0.88, P < .001). Similarly, the number of shigellosis cases began to increase at a relative humidity of 70-74% (r = 0.75, P < .005). The number of shigellosis cases was positively associated with the mean temperature and relative humidity in the period preceding the infection. In conclusion, the occurrence of shigellosis is significantly associated with increasing temperature and relative humidity in Taiwan. Therefore, these factors could be regarded as warning signals indicating the need to implement preventive measures.

Spatial variation of heat-related morbidity: A hierarchical Bayesian analysis in multiple districts of the Mekong Delta Region

This study examined spatial variability of heat-related morbidity in multiple districts of the Mekong Delta Region (MDR), Vietnam. It was conducted in 132 district/cities of the MDR. We used a series of hierarchical Bayesian models to examine the region-wide and district-specific association between temperatures and hospitalizations during the period of 2010-2013. The potential effects of seasonality, long-term trends, day of the week and holidays were controlled in the models. We also examined influences of socio-demographic factors on the temperature-hospitalization relationship. The results indicate that an increase of 5 °C in average temperature was associated with a 6.1% increase (95%CI: 5.9, 6.2) in region-wide hospital admissions. However, the district-level risks ranged from a 55.2% decrease {95%CI: (-54), (-56)} to a 24.4% increase (24.3-24.6) in admissions per 5 °C increase in average temperature. This reflects the heterogeneous magnitudes of temperature-hospitalization risk across districts. The results also indicate that temperature-hospitalization risk increased by 1.3% (95%CI: 1.2-1.4), for each increase of 1000 persons/km² in population density, 2.1% (95%CI: 2.04-2.11) for each 1% increase in percent of females, and 2.7% (95%CI: 2.6-2.8) for each 1% increase in percent of pre-school students. In contrast, the temperature-related hospitalization risk decreased up to 6.8% {(95%CI: (-6.6)-(-6.9)} for each 1% increase in rural population. Public health intervention measures for both short-term and long-term effects of heat-related health risk should be developed with consideration of the use of city/district scale for the factors rather than the province scale. The province scale of factors does not accurately represent the variability of health risk due to exposure to high temperatures.

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.

Evaluation of an Agricultural Meteorological Disaster Based on Multiple Criterion Decision Making and Evolutionary Algorithm

The evaluation of a meteorological disaster can be regarded as a multiple-criteria decision making problem because it involves many indexes. Firstly, a comprehensive indexing system for an agricultural meteorological disaster is proposed, which includes the disaster rate, the inundated rate, and the complete loss rate. Following this, the relative weights of the three criteria are acquired using a novel proposed evolutionary algorithm. The proposed algorithm consists of a differential evolution algorithm and an evolution strategy. Finally, a novel evaluation model, based on the proposed algorithm and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), is presented to estimate the agricultural meteorological disaster of 2008 in China. The geographic information system (GIS) technique is employed to depict the disaster. The experimental results demonstrated that the agricultural meteorological disaster of 2008 was very serious, especially in Hunan and Hubei provinces. Some useful suggestions are provided to relieve agriculture meteorological disasters.