Applied mixed generalized additive model to assess the effect of temperature on the incidence of bacillary dysentery and its forecast

Climate change and cutaneous leishmaniasis in the province of Ghardaïa in Algeria: A model-based approach to predict disease outbreaks

BACKGROUND

Cutaneous leishmaniasis (CL) is a vector-borne disease prevalent in Algeria since 2000. The disease has significant impacts on affected communities, including morbidity and social stigma.

OBJECTIVE

Investigate the association between environmental factors and the incidence of CL in the province of Ghardaïa and assess the predictive capacity of these factors for disease occurrence.

DESIGN

Retrospective SETTING: The study area included both urban and rural communities.

METHODS

We analyzed a dataset on CL in the province of Ghardaïa, Algeria, spanning from 2000 to 2020. The dataset included climatic variables such as temperature, average humidity, wind speed, rainfall, and the normalized difference vegetation index (NDVI). Using generalized additive models, we examined the relationships and interactions between these variables to predict the emergence of CL in the study area.

MAIN OUTCOME MEASURES

The identification of the most significant environmental factors associated with the incidence and the predicted incidence rates of CL in the province of Ghardaïa, Algeria.

SAMPLE SIZE AND CHARACTERISTICS

252 monthly observations of both climatic and epidemiological variables.

RESULTS

Relative humidity and wind speed were the primary climatic factors influencing the occurrence of CL epidemics in Ghardaïa, Algeria. Additionally, NDVI was a significant environmental factor associated with CL incidence. Surprisingly, temperature did not show a strong effect on CL occurrence, while rainfall was not statistically significant. The final fitted model predictions were highly correlated with real cases.

CONCLUSION

This study provides a better understanding of the long-term trend in how environmental and climatic factors contribute to the emergence of CL. Our results can inform the development of effective early warning systems for preventing the transmission and emergence of vector-borne diseases.

LIMITATIONS

Incorporating additional reservoir statistics such as rodent density and a human development index in the region could improve our understanding of disease transmission.

Effects of Ambient Temperature, Relative Humidity, and Precipitation on Diarrhea Incidence in Surabaya

BACKGROUND

Diarrhea remains a common infectious disease caused by various risk factors in developing countries. This study investigated the incidence rate and temporal associations between diarrhea and meteorological determinants in five regions of Surabaya, Indonesia.

METHOD

Monthly diarrhea records from local governmental health facilities in Surabaya and monthly means of weather variables, including average temperature, precipitation, and relative humidity from Meteorology, Climatology, and Geophysical Agency were collected from January 2018 to September 2020. The generalized additive model was employed to quantify the time lag association between diarrhea risk and extremely low (5th percentile) and high (95th percentile) monthly weather variations in the north, central, west, south, and east regions of Surabaya (lag of 0-2 months).

RESULT

The average incidence rate for diarrhea was 11.4 per 100,000 during the study period, with a higher incidence during rainy season (November to March) and in East Surabaya. This study showed that the weather condition with the lowest diarrhea risks varied with the region. The diarrhea risks were associated with extremely low and high temperatures, with the highest RR of 5.39 (95% CI 4.61, 6.17) in the east region, with 1 month of lag time following the extreme temperatures. Extremely low relative humidity increased the diarrhea risks in some regions of Surabaya, with the highest risk in the west region at lag 0 (RR = 2.13 (95% CI 1.79, 2.47)). Extremely high precipitation significantly affects the risk of diarrhea in the central region, at 0 months of lag time, with an RR of 3.05 (95% CI 2.09, 4.01).

CONCLUSION

This study identified a high incidence of diarrhea in the rainy season and in the deficient developed regions of Surabaya, providing evidence that weather magnifies the adverse effects of inadequate environmental sanitation. This study suggests the local environmental and health sectors codevelop a weather-based early warning system and improve local sanitation practices as prevention measures in response to increasing risks of infectious diseases.

Temperature might increase the hospital admission risk for rheumatoid arthritis patients in Anqing, China: a time-series study

Temperature has been studied in relation to many health outcomes. However, few studies have explored its effect on the risk of hospital admission for rheumatoid arthritis (RA). A distributed lag non-linear model (DLNM) was used to analyze associations between mean temperature, diurnal temperature range (DTR), temperature change between neighboring days (TCN), and daily admissions for RA from 2015 to 2019 in Anqing, China. Subgroup analyses based on age, gender, rheumatoid factors, and admission route were performed. In total, 1456 patients with RA were hospitalized. Regarding the cumulative-lag effects of extreme cold temperature (5th percentile = 3℃), the risks of admissions for RA were increased and highest at lag 0-11 (RR = 2.68, 95% CI: 1.23-5.86). Exposing to low (5th percentile = 1.9℃) and high (95th percentile = 14.2℃) DTRs both had increased risks of RA admission, with highest RRs of 1.40 (95% CI: 1.03-1.91) and 1.24 (95% CI: 1.0-1.53) at lag 0 day, respectively. As for TCN, the marginal risk of admission in RA patients was found when exposed to high TCN (95th percentile = 2.9℃) with the largest single-day effect at lag 10 (RR = 1.11, 95% CI: 1.01-1.23). In subgroup analyses, females were more susceptible to extreme cold temperature, low and high DTRs, and high TCN. In regard to extreme cold temperature, significant risk of hospital admission in females only appeared at lag 2 (RR = 1.48, 95% CI: 1.02-2.15) and lag 0-2 (RR = 2.35, 95% CI: 1.11-4.95). It is clear that RA patients exposed to changing temperature may increase risks of admission.

The effect and prediction of diurnal temperature range in high altitude area on outpatient and emergency room admissions for cardiovascular diseases

PURPOSE

Diurnal temperature range (DTR) is a meteorological indicator closely associated with global climate change. Thus, we aim to explore the effects of DTR on the outpatient and emergency room (O&ER) admissions for cardiovascular diseases (CVDs), and related predictive research.

METHODS

The O&ER admissions data for CVDs from three general hospitals in Jinchang of Gansu Province were collected from 2013 to 2016. A generalized additive model (GAM) with Poisson regression was employed to analyze the effect of DTR on the O&ER admissions for all cardiovascular diseases, hypertension, ischemic heart disease (IHD) and stoke. GAM was also used to preform predictive research of the effect of DTR on the O&ER admissions for CVDs.

RESULTS

There were similar positive linear relationships between DTR and the O&ER visits with the four cardiovascular diseases. And the cumulative lag effects were higher than the single lag effects. A 1 °C increase in DTR corresponded to a 1.30% (0.99-1.62%) increase in O&ER admissions for all cardiovascular diseases. Males and elderly were more sensitivity to DTR. The estimates in non-heating season were higher than in heating season. The trial prediction accuracy rate of CVDs based on DTR was between 59.32 and 74.40%.

CONCLUSIONS

DTR has significantly positive association with O&ER admissions for CVDs, which can be used as a prediction index of the admissions of O&ER with CVDs.

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.

Importance of applying Mixed Generalized Additive Model (MGAM) as a method for assessing the environmental health impacts: Ambient temperature and Acute Myocardial Infarction (AMI), among elderly in Shanghai, China

Association between acute myocardial infarction (AMI) morbidity and ambient temperature has been examined with generalized linear model (GLM) or generalized additive model (GAM). However, the effect size by these two methods might be biased due to the autocorrelation of time series data and arbitrary selection of degree of freedom of natural cubic splines. The present study analyzed how the climatic factors affected AMI morbidity for older adults in Shanghai with Mixed generalized additive model (MGAM) that addressed these shortcomings mentioned. Autoregressive random effect was used to model the relationship between AMI and temperature, PM10, week days and time. The degree of freedom of time was chosen based on the seasonal pattern of temperature. The performance of MGAM was compared with GAM on autocorrelation function (ACF), partial autocorrelation function (PACF) and goodness of fit. One-year predictions of AMI counts in 2011 were conducted using MGAM with the moving average. Between 2007 and 2011, MGAM adjusted the autocorrelation of AMI time series and captured the seasonal pattern after choosing the degree of freedom of time at 5. Using MGAM, results were well fitted with data in terms of both internal (R2 = 0.86) and external validity (correlation coefficient = 0.85). The risk of AMI was relatively high in low temperature (Risk ratio = 0.988 (95% CI 0.984, 0.993) for under 12°C) and decreased as temperature increased and speeded up within the temperature zone from 12°C to 26°C (Risk ratio = 0.975 (95% CI 0.971, 0.979), but it become increasing again when it is 26°C although not significantly (Risk ratio = 0.999 (95% CI 0.986, 1.012). MGAM is more appropriate than GAM in the scenario of response variable with autocorrelation and predictors with seasonal variation. The risk of AMI was comparatively higher when temperature was lower than 12°C in Shanghai as a typical representative location of subtropical climate.

Associations between floods and bacillary dysentery cases in main urban areas of Chongqing, China, 2005-2016: a retrospective study

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12199-021-00971-z.

Daily Temperature and Bacillary Dysentery: Estimated Effects, Attributable Risks, and Future Disease Burden in 316 Chinese Cities

BACKGROUND

Bacillary dysentery (BD) remains a significant public health issue, especially in developing countries. Evidence assessing the risk of BD from temperature is limited, particularly from national studies including multiple locations with different climatic characteristics.

OBJECTIVES

We estimated the effect of temperature on BD across China, assessed heterogeneity and attributable risks across cities and regions, and projected the future risk of BD under climate change.

METHODS

Daily BD surveillance and meteorological data over 2014-2016 were collected from the Chinese Center for Disease Control and Prevention and the China Meteorology Administration, respectively. A two-stage statistical model was used to estimate city-specific temperature-BD relationships that were pooled to derive regional and national estimates. The risk of BD attributable to temperature was estimated, and the future burden of BD attributable to temperature was projected under different climate change scenarios.

RESULTS

A positive linear relationship for the pooled effect was estimated at the national level. Subgroup analyses indicate that the estimated effect of temperature on BD was similar by age (≤5y or >5y) and gender. At baseline, estimated attributable risks for BD due to average daily mean temperatures above the 50th percentile were highest for the Inner Mongolia (16%), Northeast China (14%), and Northern China (13%). Most of the individual cities in the same regions and most of the cities in the Northwest, Southern, and Southwest regions, had high attributable risks (≥5%). The Northern, Northeast, Inner Mongolia, Northwest, and Southern China regions were identified as high risk for future BD, with estimated increases by the 2090s compared with baseline of 20% (95% confidence interval: 11%, 27%), 15% (6%, 20%), 15% (-1%, 22%), 12% (1%, 19%), and 11% (5%, 15%), respectively, under Representative Concentration Pathway 8.5.

CONCLUSIONS

The positive association between temperature and BD in different climatic regions of China, and the projection for increased risk due to climate change, support efforts to mitigate future risks. https://doi.org/10.1289/EHP5779.

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

BACKGROUND

Rising 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.

OBJECTIVES

We used city-specific data including BD cases and meteorological variables to determine the relationship between BD incidence and temperature at provincial level.

METHODS

Weekly 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.

RESULTS

In 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).

CONCLUSIONS

This 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.

The Epidemiological Influence of Climatic Factors on Shigellosis Incidence Rates in Korea

Research has shown the effects of climatic factors on shigellosis; however, no previous study has evaluated climatic effects in regions with a winter seasonality of shigellosis incidence. We examined the effects of temperature and precipitation on shigellosis incidence in Korea from 2002–2010. The incidence of shigellosis was calculated based on data from the Korean Center for Disease Control and Prevention (KCDC, Cheongju, Korea), and a generalized additive model (GAM) was used to analyze the associations between the incidence and climatic factors. The annual incidence rate of shigellosis was 7.9 cases/million persons from 2002–2010. During 2007–2010, high incidence rates and winter seasonality were observed among those aged ≥65 years, but not among lower age groups. Based on the GAM model, the incidence of shigellosis is expected to increase by 13.6% and 2.9% with a temperature increase of 1 °C and a lag of two weeks and with a mean precipitation increase of 1 mm and a lag of five weeks after adjustment for seasonality, respectively. This study suggests that the incidence of shigellosis will increase with global climate change despite the winter seasonality of shigellosis in Korea. Public health action is needed to prevent the increase of shigellosis incidence associated with climate variations.

Upstream watershed condition predicts rural children's health across 35 developing countries

Diarrheal disease (DD) due to contaminated water is a major cause of child mortality globally. Forests and wetlands can provide ecosystem services that help maintain water quality. To understand the connections between land cover and childhood DD, we compiled a database of 293,362 children in 35 countries with information on health, socioeconomic factors, climate, and watershed condition. Using hierarchical models, here we find that higher upstream tree cover is associated with lower probability of DD downstream. This effect is significant for rural households but not for urban households, suggesting differing dependence on watershed conditions. In rural areas, the effect of a 30% increase in upstream tree cover is similar to the effect of improved sanitation, but smaller than the effect of improved water source, wealth or education. We conclude that maintaining natural capital within watersheds can be an important public health investment, especially for populations with low levels of built capital.Globally diarrheal disease through contaminated water sources is a major cause of child mortality. Here, the authors compile a database of 293,362 children in 35 countries and find that upstream tree cover is linked to a lower probability of diarrheal disease and that increasing tree cover may lower mortality.

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

Objectives

Influence 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.

Methods

A 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).

Results

Firstly, 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.

Conclusions

The 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.

Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors

Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009-2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia.

Seasonal and geographical distribution of bacillary dysentery (shigellosis) and associated climate risk factors in Kon Tam Province in Vietnam from 1999 to 2013

Background

Bacillary dysentery (BD) is an acute bacterial infection of the intestine caused by Shigella spp., with clinical symptoms ranging from fever to bloody diarrhoea to abdominal cramps to tenesmus. In Vietnam, enteric bacterial pathogens are an important cause of diarrhoea and most cases in children under 5 years of age are due to Shigella strains. The serogroups S. flexneri and S. sonnei are considered to be the most common. The main objective of this study was to, for the first time, assess the seasonal patterns and geographic distribution of BD in Vietnam, and to determine the climate risk factors associated with the incidence of BD in Kon Tum Province, where the highest rate of bacillary dysentery was observed from 1999 to 2013.

Methods

The seasonal patterns and geographic distribution of BD was assessed in Vietnam using a seasonal-trend decomposition procedure based on loess. In addition, negative binomial regression models were used to determine the climate risk factors associated with the incidence of BD in Kon Tum Province, from 1999 to 2013.

Results

Overall, incidence rates of BD have slightly decreased over time (except for an extremely high incidence in 2012 in the north of Vietnam). The central regions (north/south central coast and central highlands) had relatively high incidence rates, whereas the northwest/east and Red River Delta regions had low incidence rates. Overall, seasonal plots showed a high peak in the mid-rainy reason and a second smaller peak in the early or late rainy season. The incidence rates significantly increased between May and October (“wet season”) across the country. In Kon Tum Province, temperature, humidity, and precipitation were found to be positively associated with the incidence of BD.

Conclusions

Our findings provide insights into the seasonal patterns and geographic distribution of BD in Vietnam and its associated climate risk factors in Kon Tum Province. This study may help clinicians and the general public to better understand the timings of outbreaks and therefore equip them with the knowledge to plan better interventions (such as improving water, sanitation, and hygiene conditions) during peak seasons. This can, in turn, prevent or reduce outbreaks and onwards transmission during an outbreak.

Electronic supplementary material

The online version of this article (doi:10.1186/s40249-017-0325-z) contains supplementary material, which is available to authorized users.

The Effects of Floods on the Incidence of Bacillary Dysentery in Baise (Guangxi Province, China) from 2004 to 2012

Research shows potential effects of floods on intestinal infections. Baise, a city in Guangxi Province (China) had experienced several floods between 2004 and 2012 due to heavy and constant precipitation. This study aimed to examine the relationship between floods and the incidence of bacillary dysentery in Baise. A mixed generalized additive model and Spearman correlation were applied to analyze the relationship between monthly incidence of bacillary dysentery and 14 flood events with two severity levels. Data collected from 2004 to 2010 were utilized to estimate the parameters, whereas data from 2011 to 2012 were used to validate the model. There were in total 9255 cases of bacillary dysentery included in our analyses. According to the mixed generalized additive model, the relative risks (RR) of moderate and severe floods on the incidence of bacillary dysentery were 1.40 (95% confidence interval (CI): 1.16–1.69) and 1.78 (95% CI: 1.61–1.97), respectively. The regression analysis also indicated that the flood duration was negatively associated with the incidence of bacillary dysentery (with RR: 0.57, 95% CI: 0.40–0.86). Therfore, this research suggests that floods exert a significant part in enhancing the risk of bacillary dysentery in Baise. Moreover, severe floods have a higher proportional contribution to the incidence of bacillary dysentery than moderate floods. In addition, short-term floods may contribute more to the incidence of bacillary dysentery than a long-term flood. The findings from this research will provide more evidence to reduce health risks related to floods.

Association between flood and the morbidity of bacillary dysentery in Zibo City, China: a symmetric bidirectional case-crossover study

This study examined the relationship between daily morbidity of bacillary dysentery and flood in 2007 in Zibo City, China, using a symmetric bidirectional case-crossover study. Odds ratios (ORs) and 95 % confidence intervals (CIs) on the basis of multivariate model and stratified analysis at different lagged days were calculated to estimate the risk of flood on bacillary dysentery. A total of 902 notified bacillary dysentery cases were identified during the study period. The median of case distribution was 7-year-old and biased to children. Multivariable analysis showed that flood was associated with an increased risk of bacillary dysentery, with the largest OR of 1.849 (95 % CI 1.229-2.780) at 2-day lag. Gender-specific analysis showed that there was a significant association between flood and bacillary dysentery among males only (ORs >1 from lag 1 to lag 5), with the strongest lagged effect at 2-day lag (OR = 2.820, 95 % CI 1.629-4.881), and the result of age-specific indicated that youngsters had a slightly larger risk to develop flood-related bacillary dysentery than older people at one shorter lagged day (OR = 2.000, 95 % CI 1.128-3.546 in youngsters at lag 2; OR = 1.879, 95 % CI 1.069-3.305 in older people at lag 3). Our study has confirmed that there is a positive association between flood and the risk of bacillary dysentery in selected study area. Males and youngsters may be the vulnerable and high-risk populations to develop the flood-related bacillary dysentery. Results from this study will provide recommendations to make available strategies for government to deal with negative health outcomes due to floods.

The changing epidemiology of bacillary dysentery and characteristics of antimicrobial resistance of Shigella isolated in China from 2004-2014

Background

Bacillary dysentery caused by bacteria of the genus Shigella is a significant public health problem in developing countries such as China. The objective of this study was to analyze the epidemiological pattern of bacillary dysentery, the diversity of the causative agent, and the antimicrobial resistance patterns of Shigella spp. for the purpose of determining the most effective allocation of resources and prioritization of interventions.

Methods

Surveillance data were acquired from the National Infectious Disease Information Reporting System (2004–2014) and from the sentinel hospital-based surveillance system (2005–2014). We analyzed the spatial and temporal distribution of bacillary dysentery, age and sex distribution, species diversity, and antimicrobial resistance patterns of Shigella spp.

Results

The surveillance registry included over 3 million probable cases of bacillary dysentery during the period 2004–2014. The annual incidence rate of bacillary dysentery decreased from 38.03 cases per 100,000 person-years in 2004 to 11.24 cases per 100,000 person-years in 2014. The case-fatality rate decreased from 0.028% in 2004 to 0.003% in 2014. Children aged <1 year and 1–4 years were most affected, with higher incidence rates (228.59 cases per 100,000 person-years and 92.58 cases per 100,000 person-years respectively). The annual epidemic season occurred between June and September. A higher incidence rate of bacillary dysentery was found in the Northwest region, Beijing and Tianjin during the study period. Shigella flexneri was the most prevalent species that caused bacillary dysentery in China (63.86%), followed by Shigella sonnei (34.89%). Shigella isolates were highly resistant to nalidixic acid (89.13%), ampicillin (88.90%), tetracycline (88.43%), and sulfamethoxazole (82.92%). During the study period, isolates resistant to ciprofloxacin and cefotaxime increased from 8.53 and 7.87% in 2005 to 44.65 and 29.94% in 2014, respectively.

Conclusions

The incidence rate of bacillary dysentery has undergone an obvious decrease from 2004 to 2014. Priority interventions should be delivered to populations in northwest China and to individuals aged <5 years. Antimicrobial resistance of Shigella is a serious public health problem and it is important to consider the susceptibility profile of isolates before determining treatment.

Short-term effects of meteorological factors on pediatric hand, foot, and mouth disease in Guangdong, China: a multi-city time-series analysis

Background

Literature shows inconsistency in meteorological effects on Hand, foot, and mouth disease (HFMD) in different cities. This multi-city study aims to investigate the meteorological effects on pediatric HFMD occurrences and the potential effect modification by geographic factors.

Methods

Based on daily time-series data in eight major cities in Guangdong, China during 2009–2013, mixed generalized additive models were employed to estimate city-specific meteorological effects on pediatric HFMD. Then, a random-effect multivariate meta-analysis was conducted to obtain the pooled risks and to explore heterogeneity explained by city-level factors.

Results

There were a total of 400,408 pediatric HFMD cases (children aged 0–14 years old) with an annual incidence rate of 16.6 cases per 1,000 children, clustered in males and children under 3 years old. Daily average temperature was positively associated with pediatric HFMD cases with the highest pooled relative risk (RR) of 1.52 (95 % CI: 1.30–1.77) at the 95th percentile of temperature (30.5 °C) as compared to the median temperature (23.5 °C). Significant non-linear positive effects of high relative humidity were also observed with a 13 % increase (RR = 1.13, 95 % CI: 1.00–1.28) in the risk of HFMD at the 99th percentile of relative humidity (86.9 %) as compared to the median value (78 %). The effect estimates showed geographic variations among the cities which was significantly associated with city’s latitude and longitude with an explained heterogeneity of 32 %.

Conclusions

Daily average temperature and relative humidity had non-linear and delayed effects on pediatric HFMD and the effects varied across different cities. These findings provide important evidence for comprehensive understanding of the climatic effects on pediatric HFMD and for the authority to take targeted interventions and measures to control the occurrence and transmission of HFMD.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-016-1846-y) contains supplementary material, which is available to authorized users.

Time series analysis of the association between ambient temperature and cerebrovascular morbidity in the elderly in Shanghai, China

Research on the association between ambient temperature and cerebrovascular morbidity is scarce in China. In this study, we applied mixed generalized additive model (MGAM) to daily counts of cerebrovascular disease of Shanghai residents aged 65 years or older from 2007-2011, stratified by gender. Weighted daily mean temperature up to lags of one week was smoothed by natural cubic spline, and was added into the model to assess both linear and nonlinear effects of temperature. We found that when the mean temperature increased by 1 °C, the male cases of cerebrovascular disease reduced by 0.95% (95% Confidence Interval (CI): 0.80%, 1.10%) or reduced by 0.34% (95% CI: -0.68, 1.36%) in conditions of temperature was below or above 27 °C. However, for every 1 °C increase in temperature, the female cases of cerebrovascular disease increased by 0.34% (95% CI: -0.26%, 0.94%) or decreased by 0.92% (95% CI: 0.72, 1.11%) in conditions of temperature was below or above 8 °C, respectively. Temperature and cerebrovascular morbidity is negatively associated in Shanghai. MGAM is recommended in assessing the association between environmental hazards and health outcomes in time series studies.

Spatio-Temporal Pattern and Socio-Economic Factors of Bacillary Dysentery at County Level in Sichuan Province, China

Bacillary dysentery (BD) remains a big public health problem in China. Effective spatio-temporal monitoring of BD incidence is important for successful implementation of control and prevention measures. This study aimed to examine the spatio-temporal pattern of BD and analyze socio-economic factors that may affect BD incidence in Sichuan province, China. Firstly, we used space-time scan statistic to detect the high risk spatio-temporal clusters in each year. Then, bivariate spatial correlation and Bayesian spatio-temporal model were utilized to examine the associations between the socio-economic factors and BD incidence. Spatio-temporal clusters of BD were mainly located in the northern-southern belt of the midwest area of Sichuan province. The proportion of primary industry, the proportion of rural population and the rates of BD incidence show statistically significant positive correlation. The proportion of secondary industry, proportion of tertiary Industry, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons, per capital GDP and the rate of BD incidence show statistically significant negative correlation. The best fitting spatio-temporal model showed that medical and technical personnel per thousand persons and per capital GDP were significantly negative related to the risk of BD.

High mean water vapour pressure promotes the transmission of bacillary dysentery

Bacillary dysentery is an infectious disease caused by Shigella dysenteriae, which has a seasonal distribution. External environmental factors, including climate, play a significant role in its transmission. This paper identifies climate-related risk factors and their role in bacillary dysentery transmission. Harbin, in northeast China, with a temperate climate, and Quzhou, in southern China, with a subtropical climate, are chosen as the study locations. The least absolute shrinkage and selectionator operator is applied to select relevant climate factors involved in the transmission of bacillary dysentery. Based on the selected relevant climate factors and incidence rates, an AutoRegressive Integrated Moving Average (ARIMA) model is established successfully as a time series prediction model. The numerical results demonstrate that the mean water vapour pressure over the previous month results in a high relative risk for bacillary dysentery transmission in both cities, and the ARIMA model can successfully perform such a prediction. These results provide better explanations for the relationship between climate factors and bacillary dysentery transmission than those put forth in other studies that use only correlation coefficients or fitting models. The findings in this paper demonstrate that the mean water vapour pressure over the previous month is an important predictor for the transmission of bacillary dysentery.

Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi Province, China

BACKGROUND

In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year.

METHODS

Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i.

RESULTS

The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other.

Identifying high-risk areas of bacillary dysentery and associated meteorological factors in Wuhan, China

Spatial distribution of bacillary dysentery incidence was mapped at the district level in Wuhan, China. And a generalized additive time series model was used to examine the effect of daily weather factors on bacillary dysentery in the high-risk areas, after controlling for potential confounding factors. Central districts were found to be the high-risk areas. The time series analysis found an acute effect of meteorological factors on bacillary dysentery occurrence. A positive association was found for mean temperature (excess risk (ER) for 1°C increase being 0.94% (95% confidence interval (CI): 0.46% to 1.43% on the lag day 2), while a negative effect was observed for relative humidity and rainfall, the ER for 1% increase in relative humidity was −0.21% (95% CI: −0.34% to −0.08%), and the ER for 1 mm increase in rainfall was −0.23% (95% CI: −0.37% to −0.09%). This study suggests that bacillary dysentery prevention and control strategy should consider local weather variations.