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Background China's capacity to control and prevent emerging and re-emerging infectious diseases is critical to the nation's population health. This study aimed to explore the capacity of Centers for Disease Control and Prevention (CDCs) in China to deal with infectious diseases now and in the future. Methods A survey was conducted in 2015 among 973 public health professionals at CDCs in Beijing and four provinces, to assess their capacity to deal with emerging and re-emerging infectious diseases. Results Although most professionals were confident with the current capacity of CDCs to cope with outbreaks, nearly all indicated more funding was required to meet future challenges. Responses indicated that Yunnan Province faced more challenges than Anhui, Henan and Liaoning Provinces in being completely prepared and able to deal with outbreaks. Participants aged 20–39 years were more likely than those aged 40 and over to believe strategies such as interdisciplinary and international collaborations for disease surveillance and control, would assist capacity building. Conclusion The capacity of China's CDCs to deal with infectious diseases was excellent. However, findings suggest it is imperative to increase the number of skilled CDC staff, financial support, and strengthen county level staff training and health education programs. [ABSTRACT FROM AUTHOR]

Accurate analysis of targeted sentiment in online course reviews helps in understanding emotional changes of learners and improving the course quality. In this paper, we propose a fine-tuned bidirectional encoder representation from transformers (BERT) model for targeted sentiment analysis of course reviews. Specifically, it consists of two parts: binding corporate rules — conditional random field (BCR-CRF) target extraction model and a binding corporate rules — double attention (BCR-DA) target sentiment analysis model. Firstly, based on a large-scale Chinese review corpus, intra-domain unsupervised training of a BERT pre-trained model (BCR) is performed. Then, a Conditional Random Field (CRF) layer is introduced to add grammatical constraints to the output sequence of the semantic representation layer in the BCR model. Finally, a BCR-DA model containing double attention layers is constructed to express the sentiment polarity of the course review targets in a classified manner. Experiments are performed on Chinese online course review datasets of China MOOC. The experimental results show that the F1 score of the BCR-CRF model reaches above 92%, and the accuracy of the BCR-DA model reaches above 72%. [ABSTRACT FROM AUTHOR]

Aim: The frailty index is used to measure the health status of older individuals. However, its association with self‐neglect, social support and sociodemographic characteristics of older adults is underexplored. The purpose of the present study was to explore such associations among the rural older adults in Anhui Province of China, and to provide scientific evidence for policy‐makers to improve the health and well‐being of older adults in rural China. Methods: A cross‐sectional survey was undertaken among 3048 older adults in rural China. The frailty index was measured by an accumulation of deficits of 40 items. Ordinal logistic regression models were carried out to explore the associations of self‐neglect, social support and sociodemographic characteristics with the frailty index. Results: The frailty rate was 15.8% among the participants. Older adults who showed self‐neglect, were female, had a lower education level, had a lower monthly income and did not drink alcohol were more prone to having frailty in the 60–76 years age group, whereas older adults who showed self‐neglect, had poor social support, were female, were not smokers and did not drink alcohol were more likely to have frailty in the ≥77 years age group (P < 0.05). The interaction effect on frailty between self‐neglect and social support was found in the 60–76 years age group. Conclusions: Age differences were shown in the associations between self‐neglect, social support, sociodemographic characteristics and frailty index, which suggests different measures should be used accordingly for frailty prevention and management. Geriatr Gerontol Int 2018; 18: 987–996 [ABSTRACT FROM AUTHOR]

Background: There was a dengue epidemic in several regions of China in 2013. No study has explored the dynamics of dengue transmission between different geographical locations with dengue outbreaks in China. The purpose of the study is to analyze the epidemiological characteristics and to explore the dynamic transmission of dengue in China, 2013. Methodology and Principal Findings: Records of dengue cases of 2013 were obtained from the China Notifiable Disease Surveillance System. Full E-gene sequences of dengue virus detected from the outbreak regions of China were download from GenBank. Geographical Information System and heatmaps were used to describe the epidemiological characteristics. Maximum Likelihood phylogenetic and Bayesian phylogeographic analyses were conducted to explore the dengue dynamic transmission. Yunnan Province and Guangdong Province had the highest imported cases in the 2013 epidemic. In the locations with local dengue transmission, most of imported cases occurred from June to November 2013 while local dengue cases developed from July to December, 2013. There were significant variations for the incidences of dengue, in terms of age distributions, among different geographic locations. However, gender differences were identified in Guangzhou, Foshan and Xishuangbanna. DENV 1–3 were detected in all locations with the disease outbreaks. Some genotypes were detected in more than one locations and more than one genotypes have been detected in several locations. The dengue viruses introduced to outbreak areas were predominantly from Southeast Asia. In Guangdong Province, the phylogeographical results indicated that dengue viruses of DENV 1 were transmitted to neighboring cities Foshan and Zhongshan from Guangzhou city, and then transmitted to Jiangmen city. The virus in DENV 3 was introduced to Guangzhou city, Guangdong Province from Xishuangbanna prefecture, Yunnan Province. Conclusions: Repeated dengue virus introductions from Southeast Asia and subsequent domestic dengue transmission within different regions may have contributed to the dengue epidemics in China, 2013. [ABSTRACT FROM AUTHOR]

Introduction: Dengue is endemic in more than 100 countries, mainly in tropical and subtropical regions, and the incidence has increased 30-fold in the past 50 years. The situation of dengue in China has become more and more severe, with an unprecedented dengue outbreak hitting south China in 2014. Building a dengue early warning system is therefore urgent and necessary for timely and effective response. Methodology and Principal Findings: In the study we developed a time series Poisson multivariate regression model using imported dengue cases, local minimum temperature and accumulative precipitation to predict the dengue occurrence in four districts of Guangzhou, China. The time series data were decomposed into seasonal, trend and remainder components using a seasonal-trend decomposition procedure based on loess (STL). The time lag of climatic factors included in the model was chosen based on Spearman correlation analysis. Autocorrelation, seasonality and long-term trend were controlled in the model. A best model was selected and validated using Generalized Cross Validation (GCV) score and residual test. The data from March 2006 to December 2012 were used to develop the model while the data from January 2013 to September 2014 were employed to validate the model. Time series Poisson model showed that imported cases in the previous month, minimum temperature in the previous month and accumulative precipitation with three month lags could project the dengue outbreaks occurred in 2013 and 2014 after controlling the autocorrelation, seasonality and long-term trend. Conclusions: Together with the sole transmission vector Aedes albopictus, imported cases, monthly minimum temperature and monthly accumulative precipitation may be used to develop a low-cost effective early warning system. Author Summary: Dengue has emerged as the most important mosquito-borne viral disease globally. With increasing global trade and population movement, the disease is transferred to regions which were previously dengue free. When dengue vector exists and weather factors are suitable, there is the possibility for dengue transmission and even outbreaks happening. Dengue is still believed to be a non-endemic disease in China, with imported cases playing a vital role in local dengue transmission. The situation of dengue is becoming more and more severe with two successive large outbreaks hitting southern China in 2013 and 2014, and the dengue outbreak in 2014 was unprecedented. In this study, we aim to develop a dengue forecasting model that would provide an early warning of dengue outbreak to allow local health authorities and communities to implement timely effective control measures. Our model showed that imported cases in the previous month, monthly minimum temperature in the previous month and monthly accumulative precipitation with three month lags could predict dengue outbreak ahead by one month. We concluded that these variables could be used to develop an early dengue warning model to provide evidence-based decisions for disease control and prevention and including the utilization of limited resources. [ABSTRACT FROM AUTHOR]

Background: Increased risks for hemorrhagic fever with renal syndrome (HFRS) caused by Hantaan virus have been observed since 2005, in Xi'an, China. Despite increased vigilance and preparedness, HFRS outbreaks in 2010, 2011, and 2012 were larger than ever, with a total of 3,938 confirmed HFRS cases and 88 deaths in 2010 and 2011. Methods and Findings: Data on HFRS cases and weather were collected monthly from 2005 to 2012, along with active rodent monitoring. Wavelet analyses were performed to assess the temporal relationship between HFRS incidence, rodent density and climatic factors over the study period. Results showed that HFRS cases correlated to rodent density, rainfall, and temperature with 2, 3 and 4-month lags, respectively. Using a Bayesian time-series Poisson adjusted model, we fitted the HFRS outbreaks among humans for risk assessment in Xi'an. The best models included seasonality, autocorrelation, rodent density 2 months previously, and rainfall 2 to 3 months previously. Our models well reflected the epidemic characteristics by one step ahead prediction, out-of-sample. Conclusions: In addition to a strong seasonal pattern, HFRS incidence was correlated with rodent density and rainfall, indicating that they potentially drive the HFRS outbreaks. Future work should aim to determine the mechanism underlying the seasonal pattern and autocorrelation. However, this model can be useful in risk management to provide early warning of potential outbreaks of this disease. Author Summary: Hemorrhagic fever with renal syndrome (HFRS, caused by hantavirus) is a zoonotic infectious disease reservoired in rodent populations worldwide, but with 90% of the total cases occurring in China. Xi'an is one of the most endemic areas in China, with a total of 7,748 confirmed HFRS cases from 2005 to 2012. HFRS came to the attention of the public when two larger outbreaks occurred in Xi'an in 2010 and 2011, with 1,366 and 1,067 cases being reported, respectively. By using 8 years of surveillance data (2005–2012) on HFRS dynamics, including data on the main rodent host reservoir, human cases, and weather conditions, we show how the epidemic dynamics of HFRS were associated with seasonality, rodent abundance, rainfall, and temperature. We find that the two larger HFRS outbreaks coincided with the abrupt increase of rodent abundance and/or rainfall. We present a statistical model revealing strong effects of seasonality and autocorrelation and additional effects of rodent density and rainfall on HFRS incidence that gives robust prediction; this approach could be a very practical tool in Xi'an. [ABSTRACT FROM AUTHOR]

Increased incidence of hand, foot and mouth disease (HFMD) has been recognized as a critical challenge to communicable disease control and public health response. This study aimed to quantify the association between climate variation and notified cases of HFMD in selected cities of Shanxi Province, and to provide evidence for disease control and prevention. Meteorological variables and HFMD cases data in 4 major cities (Datong, Taiyuan, Changzhi and Yuncheng) of Shanxi province, China, were obtained from the China Meteorology Administration and China CDC respectively over the period 1 January 2009 to 31 December 2013. Correlations analyses and Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to identify and quantify the relationship between the meteorological variables and HFMD. HFMD incidence varied seasonally with the majority of cases in the 4 cities occurring from May to July. Temperatures could play important roles in the incidence of HFMD in these regions. The SARIMA models indicate that a 1° C rise in average, maximum and minimum temperatures may lead to a similar relative increase in the number of cases in the 4 cities. The lag times for the effects of temperatures were identified in Taiyuan, Changzhi and Yuncheng. The numbers of cases were positively associated with average and minimum temperatures at a lag of 1 week in Taiyuan, Changzhi and Yuncheng, and with maximum temperature at a lag of 2 weeks in Yuncheng. Positive association between the temperature and HFMD has been identified from the 4 cities in Shanxi Province, although the role of weather variables on the transmission of HFMD varied in the 4 cities. Relevant prevention measures and public health action are required to reduce future risks of climate change with consideration of local climatic conditions. [ABSTRACT FROM AUTHOR]

Background: Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by many serotypes of hantaviruses. In China, HFRS has been recognized as a severe public health problem with 90% of the total reported cases in the world. This study describes the spatiotemporal dynamics of HFRS cases in China and identifies the regions, time, and populations at highest risk, which could help the planning and implementation of key preventative measures. Methods: Data on all reported HFRS cases at the county level from January 2005 to December 2012 were collected from Chinese Center for Disease Control and Prevention. Geographic Information System-based spatiotemporal analyses including Local Indicators of Spatial Association and Kulldorff's space-time scan statistic were performed to detect local high-risk space-time clusters of HFRS in China. In addition, cases from high-risk and low-risk counties were compared to identify significant demographic differences. Results: A total of 100,868 cases were reported during 2005–2012 in mainland China. There were significant variations in the spatiotemporal dynamics of HFRS. HFRS cases occurred most frequently in June, November, and December. There was a significant positive spatial autocorrelation of HFRS incidence during the study periods, with Moran's I values ranging from 0.46 to 0.56 (P<0.05). Several distinct HFRS cluster areas were identified, mainly concentrated in northeastern, central, and eastern of China. Compared with cases from low-risk areas, a higher proportion of cases were younger, non-farmer, and floating residents in high-risk counties. Conclusions: This study identified significant space-time clusters of HFRS in China during 2005–2012 indicating that preventative strategies for HFRS should be particularly focused on the northeastern, central, and eastern of China to achieve the most cost-effective outcomes. Author Summary: Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne viral disease caused by many serotypes of hantaviruses. In China, HFRS has been recognized as a severe public health problem and accounts for 90% of the reported cases in the world. We examined the spatiotemporal dynamics of HFRS cases in China during 2005–2012 and compared characteristics between cases from high-risk and low-risk counties. Several distinct HFRS cluster areas were identified, concentrated in northeastern, central, and eastern of China. Compared with cases from low-risk areas, a higher proportion of cases were younger, non-farmer, and floating residents in high-risk counties. These findings suggest preventative strategies for HFRS should be focused on the identified clusters in order to achieve the most cost-effective outcomes. [ABSTRACT FROM AUTHOR]

There have been increasing concerns about the challenge of emerging and re-emerging infectious diseases due to climate change, especially in developing countries including China. Health professionals play a significant role in the battle to control and prevent infectious diseases. This study therefore aims to investigate the perceptions and attitudes of health professionals at the Centers for Disease Control and Prevention (CDC) in different levels in China, and to consider adaptation measures to deal with the challenge of climate change. In 2013, a cross-sectional questionnaire survey was undertaken among 314 staff in CDCs in Shanxi Province, China, whose routine work involves disease control and prevention. Data were analyzed using descriptive methods and logistic regression. A majority of the CDC staff were aware of the health risks from climate change, especially its impacts on infectious disease transmission in their jurisdictions, and believed climate change might bring about both temporal and spatial change in transmission patterns. It was thought that adaptation measures should be established including: strengthening/improving currently existing disease surveillance systems and vector monitoring; building CDC capacity in terms of infrastructure and in-house health professional training; development and refinement of relevant legislation, policies and guidelines; better coordination among various government departments; the involvement of the community in infectious disease interventions; and collaborative research with other institutions. This study provides a snapshot of the understanding of CDC staff regarding climate change risks relevant to infectious diseases and adaptation in China. Results may help inform future efforts to develop adaptation measures to minimize infectious disease risks due to climate change. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study is to examine the spatiotemporal pattern of Japanese Encephalitis (JE) in mainland China during 2002–2010. Specific objectives of the study were to quantify the temporal variation in incidence of JE cases, to determine if clustering of JE cases exists, to detect high risk spatiotemporal clusters of JE cases and to provide evidence-based preventive suggestions to relevant stakeholders. Methods: Monthly JE cases at the county level in mainland China during 2002–2010 were obtained from the China Information System for Diseases Control and Prevention (CISDCP). For the purpose of the analysis, JE case counts for nine years were aggregated into four temporal periods (2002; 2003–2005; 2006; and 2007–2010). Local Indicators of Spatial Association and spatial scan statistics were performed to detect and evaluate local high risk space-time clusters. Results: JE incidence showed a decreasing trend from 2002 to 2005 but peaked in 2006, then fluctuated over the study period. Spatial cluster analysis detected high value clusters, mainly located in Southwestern China. Similarly, we identified a primary spatiotemporal cluster of JE in Southwestern China between July and August, with the geographical range of JE transmission increasing over the past years. Conclusion: JE in China is geographically clustered and its spatial extent dynamically changed during the last nine years in mainland China. This indicates that risk factors for JE infection are likely to be spatially heterogeneous. The results may assist national and local health authorities in the development/refinement of a better preventive strategy and increase the effectiveness of public health interventions against JE transmission. Author Summary: Japanese encephalitis (JE) is a mosquito-borne disease, which primarily occurs in rural and suburban areas of Southeast Asia and the Western Pacific region. JE still remains a significant public health problem in mainland China, with approximately 50% of global cases annually. Few studies have explored the spatiotemporal patterns of JE cases in China. Here we reported the results of Local Indicators of Spatial Association and spatial scan statistics of JE cases in mainland China at the county level during the four periods: 2002; 2003–2005; 2006; 2007–2010. The primary spatiotemporal cluster of JE was detected in Southwestern China between July and August, with the geographical range of JE transmission increasing over the past years. The results of LISA and spatial scan statistics were consistent which indicates that these methods are reliable and could have wider applications in the fields of disease surveillance and management in China, particularly in the surveillance and monitoring of other vector-borne diseases. These findings may assist in informing prevention and control strategies and increase the effectiveness of public health interventions against JE transmission. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: This study aimed to examine the impact of climate variation on malaria in a temperate region of China. Methods: A 20-year historical time-series data analysis was conducted to examine the relationship between meteorological variables, including maximum and minimum temperatures, rainfall, humidity, and cases of malaria in Jinan, a temperate city in northern China. Data were retrieved from 1959 and 1979 and analyzed on a monthly basis. Spearman correlation and cross-correlation analyses were performed to identify time lag values between each meteorological variable and the number of malaria cases. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to quantify the relationship between the meteorological variables and malaria cases. Results: The SARIMA models indicate that a 1°C rise in maximum temperature may be related to a 7.7% to 12.7% increase and a 1°C rise in minimum temperature may result in approximately 11.8% to 15.8% increase in the number of malaria cases. A clear association between malaria and other selected weather variables, including rainfall and humidity, has not been detected in this study. Conclusions: Temperature could play an important role in the transmission of malaria in temperate regions of China. [Copyright &y& Elsevier]

Background: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by climatic variables. However, few studies have examined the quantitative relationship between climate variation and HFRS transmission. Objective: We examined the potential impact of climate variability on HFRS transmission and developed climate-based forecasting models for HFRS in northeastern China. Methods: We obtained data on monthly counts of reported HFRS cases in Elunchun and Molidawahaner counties for 1997-2007 from the Inner Mongolia Center for Disease Control and Prevention and climate data from the Chinese Bureau of Meteorology. Cross-correlations assessed crude associations between climate variables, including rainfall, land surface temperature (LST), relative humidity (RH), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI) and monthly HFRS cases over a range of lags. We used time-series Poisson regression models to examine the independent contribution of climatic variables to HFRS transmission. Results: Cross-correlation analyses showed that rainfall, LST, RH, and MEI were significantly associated with monthly HFRS cases with lags of 3-5 months in both study areas. The results of Poisson regression indicated that after controlling for the autocorrelation, seasonality, and longterm trend, rainfall, LST, RH, and MEI with lags of 3-5 months were associated with HFRS in both study areas. The final model had good accuracy in forecasting the occurrence of HFRS. Conclusions: Climate variability plays a significant role in HFRS transmission in northeastern China. The model developed in this study has implications for HFRS control and prevention. [ABSTRACT FROM AUTHOR]

This study compared the difference between two samples of men who have sex with men (MSM) in Harbin, China, using cross-sectional data that were collected via the Internet and through conventional venue-based outreach. All participants in both samples lived in or nearby Harbin in northeast China. Results showed that the Internet sample was significantly younger, more educated and more likely to be students and to self-identify as homosexual than the community sample. After controlling for demographic characteristics, the community sample was more likely to have had sex with females (OR 2.01, CI 1.22-3.30, p=0.006) and to have had ≥6 male partners in the previous six months than the Internet sample (OR 4.88, CI 3.51-6.80, p<0.001). No significant difference was observed in the prevalence of unprotected anal intercourse, exchanging sex for money, exchanging money for sex or illicit drug use between the two samples. For those seeking sex both on the Internet and in traditional gay venues, participants in the community sample were nearly three times more likely to have had ≥6 male partners during the previous six months than those in the Internet sample (p=0.001). In conclusion, the online and offline samples of MSM are significantly different and carry different levels of risk for HIV transmission. Using the Internet as a data collection method may serve as an additional mechanism for the existing gay venue-based behavioral surveillance system in China. [ABSTRACT FROM AUTHOR]

Summary: Objectives: This paper was aimed at examining the relationship between meteorological variables and bacillary dysentery in different climatic and geographic areas in China. Methods: Jinan in northern China, with a temperate climate, and Baoan in southern China, with a subtropical climate were chosen as study areas. Spearman correlations and seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to quantify the association between meteorological variables and dysentery. The Hockey Stick model was used to explore the threshold of the effect of temperatures. Results: Maximum temperature, minimum temperature, rainfall, relative humidity and air pressure were significantly correlated with the incidence of dysentery in the both cities, with lag effects varying from zero to two months. In the SARIMA models, maximum and minimum temperatures were significantly associated with dysentery transmission. The thresholds for the effects of maximum and minimum temperatures were 17°C and 8°C, respectively, in the northern city. No thresholds were detected in the southern city. Conclusions: Climate variations have different impacts on the transmission of bacillary dysentery in temperate and subtropical cities in China. Public health action should be taken at this stage to reduce future risks of climate change with consideration of local climatic conditions. [Copyright &y& Elsevier]

Abstract: To investigate the impact of the El Niño Southern Oscillation (ENSO) on dysentery transmission, the relationship between monthly dysentery cases in Shandong Province of China and the monthly Southern Oscillation Index (SOI), a broad index of ENSO, was examined over the period 1991–2003. Spearman correlations and generalized linear models were calculated to detect the association between the SOI and dysentery cases. Data from 1991 to 2001 were used to estimate the parameters, while data from 2002 to 2003 were used to test the forecasting ability of the model. After controlling for seasonality, autocorrelation, and a time-lagged effect, the results indicate that there was a significant negative association between the number of dysentery cases and the SOI, with a lagged effect of 2 months. A one-standard-deviation decrease in the SOI might cause up to 207 more dysentery cases per month in Shandong Province. This is the first report of the impact of the Southern Oscillation on dysentery risk in China, indicating that the SOI may be a useful early indicator of potential dysentery risk in Shandong Province. [Copyright &y& Elsevier]

To investigate determinants of hemorrhagic fever with renal syndrome (HFRS) in low-lying areas of China, the authors studied Chuigang and Wanggang communities in Anhui Province. These adjacent farming communities have a population of about 100,000. Data were collected from the two communities in 1961–1977 and from Yingshang County in 1983–1995; information covered the incidence of HFRS, amount of precipitation, differences in the water level of the Huai River, density of Apodemus agrarius, autumn crop production, and areas of inundated farmland. Correlation and multiple linear regression analyses were used to estimate the relation between seasonal rainfall, density of mice, occupational factors, and occurrence of the disease. Associations were observed between the incidence of HFRS and the amount of precipitation, the water level of the Huai River, and the areas of inundated farmland in Chuigang community. The smaller the water-level difference, the less farmland was inundated and the higher the incidence of HFRS. In Wanggang community, the density of A. agrarius (r1 = 0.63, p = 0.02), the water-level difference in the Huai River (r2 = −0.81, p = 0.007), and crop production (r3 = 0.96, p = 0.005) were correlated with the incidence of HFRS. The regression analyses based on Wanggang community suggested that these indexes could be used as predictive variables, and the results from the model were well calibrated with the actual incidence of HFRS in that community (R2 = 0.88, p < 0.01) and Yingshang County (R2 = 0.91, p < 0.01). Am J Epidemiol 1998;148:276–81. [ABSTRACT FROM AUTHOR]

Few studies have explored the associations between air pollutants and influenza across seasons, especially at large scales. This study aimed to evaluate seasons' modifying effects on associations between air pollutants and influenza from 10 cities of southern China. Through scientific evidence, it provides mitigation and adaptation strategies with practical guidelines to local health authorities and environmental protection agencies. Daily influenza incidence, meteorological, and air pollutants data from 2016 to 2019 were collected. Quasi-Poisson regression with a distributed lag nonlinear model was used to evaluate city-specific air pollutants and influenza associations. Meta-analysis was used to pool site-specific estimates. Attributable fractions (AFs) of influenza incidence due to pollutants were calculated. Stratified analyses were conducted by season, sex, and age. Overall, the cumulative relative risk (CRR) of influenza incidence for a 10-unit increase in PM 2.5 , PM 10 , SO 2 , NO 2 , and CO was 1.45 (95% CI: 1.25, 1.68), 1.53 (95% CI: 1.29, 1.81), 1.87 (95% CI: 1.40, 2.48), 1.74 (95% CI: 1.49, 2.03), and 1.19 (95% CI: 1.04, 1.36), respectively. Children aged 0–17 were more sensitive to air pollutants in spring and winter. PM 10 had greater effect on influenza than PM 2.5 in autumn, winter, and overall, lesser in spring. The overall AF due to PM 2.5 , PM 10 , SO 2 , NO 2, and CO was 4.46% (95% eCI: 2.43%, 6.43%), 5.03% (95% eCI: 2.33%, 7.56%), 5.36% (95% eCI: 3.12%, 7.58%), 24.88% (95% eCI: 18.02%, 31.67%), and 23.22% (95% eCI: 17.56%, 28.61%), respectively. AF due to O 3 was 10.00% (95% eCI: 4.76%, 14.95%) and 3.65% (95% eCI: 0.50%, 6.59%) in spring and summer, respectively. The seasonal variations in the associations between air pollutants and influenza in southern China would provide evidence to service providers for tailored intervention, especially for vulnerable populations. [Display omitted] • First multi-site study on pollutants' effects to influenza in southern China. • PM 2.5 , PM 10 , SO 2 , and NO 2 increased influenza infection risks in winter and overall. • PM 10 had greater effects on influenza than PM 2.5 in autumn, winter, and overall. • Children aged 0–17 were more sensitive to air pollutants in spring and winter. [ABSTRACT FROM AUTHOR]

Climate change and extreme weather poses significant threats to community health, which need to be addressed by local health workforce. This study investigated the perceptions of primary healthcare professionals in Southern China on individual and institutional strategies for actions on health impacts of climate change and the related barriers. A mixed methodological approach was adopted, involving a cross-sectional questionnaire survey of 733 primary healthcare professionals (including medical doctors, nurses, public health practitioners, allied health workers and managers) selected through a multistage cluster randomized sampling strategy, and in-depth interviews of 25 key informants in Guangdong Province, China. The questionnaire survey investigated the perceptions of respondents on the health impacts of climate change and the individual and institutional actions that need to be taken in response to climate change. Multivariate logistic regression models were established to determine sociodemographic factors associated with the perceptions. The interviews tapped into coping strategies and perceived barriers in primary health care to adapt to tackle challenges of climate change. Contents analyses were performed to extract important themes. The majority (64%) of respondents agreed that climate change is happening, but only 53.6% believed in its human causes. Heat waves and infectious diseases were highly recognized as health problems associated with climate change. There was a strong consensus on the need to strengthen individual and institutional capacities in response to health impacts of climate change. The respondents believed that it is important to educate the public, take active efforts to control infectious vectors, and pay increased attention to the health care of vulnerable populations. The lack of funding and limited local workforce capacity is a major barrier for taking actions. Climate change should be integrated into primary health care development through sustainable governmental funding and resource support. • Heatwave and infectious diseases were highly recognized by primary healthcare professionals as health risks of climate change. • Weak individual and institutional capacities in response to climate change in primary health care raised concerns. • Lack of funding and limited workforce capacity was believed to jeopardize local actions to reduce health risks under climate change. [ABSTRACT FROM AUTHOR]

Climate change may lead to emerging and re-emerging infectious diseases and pose public health challenges to human health and the already overloaded healthcare system. It is therefore important to review current knowledge and identify further directions in China, the largest developing country in the world. A comprehensive literature review was conducted to examine the relationship between climate variability and infectious disease transmission in China in the new millennium. Literature was identified using the following MeSH terms and keywords: climatic variables [temperature, precipitation, rainfall, humidity, etc.] and infectious disease [viral, bacterial and parasitic diseases]. Fifty-eight articles published from January 1, 2000 to May 30, 2018 were included in the final analysis, including bacterial diarrhea, dengue, malaria, Japanese encephalitis, HFRS, HFMD, Schistosomiasis. Each 1 °C rise may lead to 3.6%–14.8% increase in the incidence of bacillary dysentery disease in south China. A 1 °C rise was corresponded to an increase of 1.8%–5.9% in the weekly notified HFMD cases in west China. Each 1 °C rise of temperature, 1％ rise in relative humidity and one hour rise in sunshine led to an increase of 0.90%, 3.99% and 0.68% in the monthly malaria cases, respectively. Climate change with the increased temperature and irregular patterns of rainfall may affect the pathogen reproduction rate, their spread and geographical distribution, change human behavior and influence the ecology of vectors, and increase the rate of disease transmission in different regions of China. Exploring relevant adaptation strategies and the health burden of climate change will assist public health authorities to develop an early warning system and protect China's population health, especially in the new 1.5 °C scenario of the newly released IPCC special report. • Many infectious diseases such as malaria and dengue fever are mostly affected by climate variability and climate change. • The impact of climate change on infectious disease transmission may be more prevalent in southern cities of China. • More infectious studies with multiple-locations and a long study period as well as adaptation strategies are required. [ABSTRACT FROM AUTHOR]

Objectives Infectious diseases are a major cause of morbidity and mortality in China. The capacity of hospitals to deal with the challenge from emerging and re-emerging infectious diseases due to climate change is of great importance to population health. This study aimed to explore the capacity of hospitals in China to deal with such challenges. Methods A cross-sectional questionnaire survey was utilized to gauge information regarding capacity of hospitals to deal with infectious diseases in the context of climate change among 611 clinical professionals whose roles pertained to infectious disease diagnosis, treatment and management in Anhui Province of China. Descriptive analysis and logistic regression analysis were performed on the data. Results More than 90% of participants believed climate change would have an adverse influence on population health and infectious disease control in China. Most indicated that their hospitals were well prepared for emerging infectious diseases at present, and they considered that logistical support in hospitals (e.g. administrative and maintenance services) should be strengthened for future capacity building. The majority of participants suggested that effective prevention and control measures, more interdisciplinary collaborations, more funding in rural areas for health care, and improved access to facilities enabling online reporting of infectious diseases, were extremely important strategies in building capacity to curb the population health impact of emerging and re-emerging infectious diseases due to climate change in China. Conclusions Clinical professionals recognized that climate change will likely increase the transmission of infectious diseases. Although rural health care and hospitals’ logistical support need to be improved, most professionals believed their hospitals to be capable of dealing with emerging diseases. They thought that interdisciplinary and cross-regional collaborations, together with necessary resource support (e.g. improved facilities for rural health care) would be important control strategies. [ABSTRACT FROM AUTHOR]

Objectives There is a paucity of epidemiological data on chronic pain and obesity among older adults. This study attempted to present the characterization of chronic pain and its association with obesity among the Chinese elderly. Methods A cross-sectional survey was undertaken among 6524 elderly individuals aged ≥60 years in China. Chronic pain was identified by self-reports based on the definition from the International Association for the Study of Pain (IASP). Body Mass Index (BMI) was measured to assess obesity. Binary logistic regression analysis was performed to explore the association between obesity and chronic pain. Results The prevalence of chronic pain was 49.8%. The legs/feet (25.5%), back (23.2%), and neck/shoulder (14.6%) were the most salient locations for chronic pain. Compared with normal weight, subjects with overweight (OR = 1.234, 95%CI = 1.100–1.384) and obesity (OR = 1.715, 95%CI = 1.418–2.073) were considerably more likely to have chronic pain after adjusting for covariates (p < .05). Age was not significantly associated with chronic pain (p > .05). Further analyses revealed that the associations between chronic pain and obesity were restricted to the legs/feet and back. Conclusion Chronic pain is common among older adults in China. Understanding the role of obesity in chronic pain is important for preventing and treating chronic pain. [ABSTRACT FROM AUTHOR]

Background: Despite increasing concerns about the health effects of climate change, the extent to which workers are affected by hot weather is not well documented. This study aims to investigate the association between high temperatures and work-related injuries using data from a large subtropical city in China.Methods: We used workers' compensation claims to identify work-related injuries in Guangzhou, China during 2011-2012. To feature the heat effect, the study period was restricted to the warm seasons in Guangzhou (1 May-31 October). We conducted a time-stratified case-crossover study to examine the association between ambient outdoor temperatures, including daily maximum and minimum temperatures, and cases of work-related injury. The relationships were assessed using conditional Poisson regression models.Results: Overall, a total of 5418 workers' compensation claims were included over the study period. Both maximum and minimum temperatures were significantly associated with work-related injuries, but associations varied by subgroup. One °C increase in maximum temperature was associated with a 1.4% (RR = 1.014, 95%CIs 1.012-1.017) increase in daily injury claims. Significant associations were seen for male and middle-aged workers, workers in small and medium-sized enterprises, and those working in manufacturing sector. And 1 °C increase in minimum temperature was associated with 1.7% (RR = 1.017, 95%CIs 1.012-1.021) increase in daily injury claims. Significant associations were observed for female and middle-aged workers, workers in large-sized enterprises, and those working in transport and construction sectors.Conclusions: We found a higher risk of work-related injuries due to hot weather in Guangzhou, China. This study provides important epidemiological evidence for policy-makers and industry that may assist in the formulation of occupational safety and climate adaptation strategies. [ABSTRACT FROM AUTHOR]

Background Mumps is still an important public health issue in the world with several recent outbreaks. The seasonable distribution of the disease suggested that meteorological factors may influence the incidence of mumps. The aim of this study was to explore the possible association between meteorological factors and the incidence of mumps, and to provide scientific evidence to relevant health authorities for the disease control and prevention. Methods We obtained the data of mumps cases and daily meteorological factors in Fujian Province in Eastern China over the period of 2005–2013. Using distributed lag non-linear model (DLNM) approach, we assessed the relationship between the meteorological factors and mumps incidence. Results The effects of meteorological factors on the mumps incidence were all non-linear. Compared with the lowest risk values, the upper level of precipitation, atmospheric pressure and relative humidity could increase the risk of mumps, whereas the low level of wind velocity, temperature, diurnal temperature range and sunshine duration may also increase the risk. Moderate atmospheric pressure and low wind velocity had larger cumulative effects within 30 lag days and the relative risks were 10.02 (95%CI: 2.47–40.71) and 12.45 (95%CI: 1.40–110.78). For temperature, the cumulative effect within 30 lag days of minimum temperature was higher than that from maximum temperature in most populations. The cumulative effects of minimum temperature for males, children aged 10–14 and students were higher than those in other populations. Conclusions Meteorological factors, especially temperature and wind velocity, should be taken into consideration in the prevention and warning of possible mumps epidemic. Special attention should be paid to the vulnerable populations, such as teenagers and young adults. [ABSTRACT FROM AUTHOR]

Many studies have explored the epidemiological characteristics of influenza. However, most previous studies were conducted in a specific region without a national picture which is important to develop targeted strategies and measures on influenza control and prevention. To explore the association between ambient temperature and incidence of influenza, to estimate the attributable risk from temperature in 30 Chinese cities with different climatic characteristics for a national picture, and to identify the vulnerable populations for national preventative policy development. Daily meteorological and influenza incidence data from the 30 Chinese cities over the period 2016–19 were collected. We estimated the city-specific association between daily mean temperature and influenza incidence using a distributed lag non-linear model and evaluated the pooled effects using multivariate meta-analysis. The attributable fractions compared with reference temperature were calculated. Stratified analyses were performed by region, sex and age. Overall, an N-shape relationship between temperature and influenza incidence was found in China. The cumulative relative risk of the peak risk temperature (5.1 °C) was 2.13 (95%CI: 1.41, 3.22). And 60% (95%eCI: 54.3%, 64.3%) of influenza incidence was attributed to ambient temperature during the days with sensitive temperatures (1.6°C–14.4 °C). The ranges of sensitive temperatures and the attributable disease burden due to temperatures varied for different populations and regions. The residents in South China and the children aged ≤5 and 6–17 years had higher fractions attributable to sensitive temperatures. Tailored preventions targeting on most vulnerable populations and regions should be developed to reduce influenza burden from sensitive temperatures. • National picture of impacts of temperature on influenza was explored in China. • An N-shape relationship between temperature and influenza incidence was discovered. • Nationwide, AF was 60.0% during the days with sensitive temperatures (1.6°C–14.4 °C). • Ranges of sensitive temperatures varied for different populations and regions. • Juveniles, children and people living in South China were more vulnerable. [ABSTRACT FROM AUTHOR]

There is limited evidence of effects and seasonal variation of temperature change on emergency department visits (EDVs). To investigate the association between diurnal temperature range (DTR), temperature change between neighboring days (TCN) and a comprehensive collection of cause-specific EDVs in China. We collected EDVs, weather, and air pollution data in 20 sites in China from 2014 to 2018. We applied a quasi–Poisson regression with distributed lag nonlinear model to evaluate DTR- and TCN-EDVs association. We used meta-analysis to pool site-specific estimates. We also conducted seasonal analysis and assess effects of modifiers. A 1 °C increase of DTR and TCN was associated with 0.29% [95% confidence interval (CI): 0.07%, 0.51%)] and 1.44% (95% CI: 0.93%, 1.96%) increase of total EDVs, respectively. People aged 18–44 were sensitive to DTR and TCN, while the elderly population was sensitive to TCN only in spring and autumn. In seasonal analysis, effects of temperature change on total EDVs were lower in summer. TCN increased risks of genitourinary diseases in summer, respiratory diseases in winter, injury in autumn, and mental diseases in spring. DTR increased the risk of respiratory diseases in autumn. Exposure to DTR and TCN was associated with elevated risk of EDVs but with great seasonal variations. Our results provided potential time and target populations for adaptive strategies and preventive measures. • Temperature change increased risks of visiting the emergency department. • Male and people aged 18–44 were sensitive to DTR and TCN. • The elderly population was vulnerable to TCN in spring and autumn. • Effects of DTR and TCN on total EDVs were lower in summer. • Seasonal variation exists in effects of DTR and TCN by age and disease. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the change and associated risk and protective factors of social anxiety symptoms among Chinese children. A 2-year longitudinal study was performed in a general primary and secondary school population in Anhui Province, China including 816 children in grades 3, 4, and 7. Children's social anxiety symptoms were assessed using the Social Anxiety Scales for Children (SASC) at three assessments. The overall prevalence of children's elevated social anxiety symptoms ranged from 15.2% to 16.4% across three assessments. Children's overall mean SASC scores were 5.6 (SD =3.7), 5.3 (SD =3.8), and 5.3 (SD =4.1) at three assessments, respectively, but the difference was not statistically significant. However, children's social anxiety symptom levels and change among different subgroups was not stable across 2-year follow-up. Multivariable logistic regression analysis indicated that age, severe family dysfunction, quality of life, positive coping, negative coping, depressive symptoms and self-esteem were predictive factors for childhood elevated social anxiety symptoms. The findings suggested that the overall social anxiety symptoms showed a relatively stable pattern over time. The identified risk and protective factors may provide scientific evidence for school, family, and health authorities to conduct necessary intervention. [ABSTRACT FROM AUTHOR]

Haemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease that poses a serious public health threat in China. HFRS is caused by hantaviruses, mainly Seoul virus in urban areas and Hantaan virus in agricultural areas. Although preventive measures including vaccination programs and rodent control measures have resulted in a decline in cases in recent years, there has been an increase in incidence in some areas and new endemic areas have emerged. This review summarises the recent literature relating to the effects of climatic factors on the incidence of HFRS in China and discusses future research directions. Temperature, precipitation and humidity affect crop yields, rodent breeding patterns and disease transmission, and these can be influenced by a changing climate. Detailed surveillance of infections caused by Hantaan and Seoul viruses and further research on the viral agents will aid in interpretation of spatiotemporal patterns and a better understanding of the environmental and ecological drivers of HFRS amid China's rapidly urbanising landscape and changing climate. [ABSTRACT FROM AUTHOR]

Japanese encephalitis (JE) is the most common cause of viral encephalitis and an important public health concern in the Asia-Pacific region, particularly in China where 50% of global cases are notified. To explore the association between environmental factors and human JE cases and identify the high risk areas for JE transmission in China, we used annual notified data on JE cases at the center of administrative township and environmental variables with a pixel resolution of 1 km × 1 km from 2005 to 2011 to construct models using ecological niche modeling (ENM) approaches based on maximum entropy. These models were then validated by overlaying reported human JE case localities from 2006 to 2012 onto each prediction map. ENMs had good discriminatory ability with the area under the curve (AUC) of the receiver operating curve (ROC) of 0.82–0.91, and low extrinsic omission rate of 5.44–7.42%. Resulting maps showed JE being presented extensively throughout southwestern and central China, with local spatial variations in probability influenced by minimum temperatures, human population density, mean temperatures, and elevation, with contribution of 17.94%–38.37%, 15.47%–21.82%, 3.86%–21.22%, and 12.05%–16.02%, respectively. Approximately 60% of JE cases occurred in predicted high risk areas, which covered less than 6% of areas in mainland China. Our findings will help inform optimal geographical allocation of the limited resources available for JE prevention and control in China, find hidden high-risk areas, and increase the effectiveness of public health interventions against JE transmission. [ABSTRACT FROM AUTHOR]

Abstract: Background: Devastating health effects from recent heat waves in China have highlighted the importance of understanding health consequences from extreme heat stress. Despite the increasing mortality from extreme heat, very limited studies have quantified the effects of summer extreme temperature on heat-related illnesses in China. Methods: The associations between extreme heat and daily heat-related illnesses that occurred in the summers of 2011–2013 in Ningbo, China, have been examined, using a distributed lag non-linear model (DLNM) based on 3862 cases. The excess morbidities of heat-related illness during each heat wave have been calculated separately and the cumulative heat wave effects on age-, sex-, and cause-specific illnesses in each year along lags have been estimated as well. Results: After controlling the effect of relative humidity, it is found that maximum temperature, rather than heat index, was a better predictor of heat-related illnesses in summers. A positive association between maximum temperatures and occurrence of heat-related diseases was apparent, especially at short lag effects. Six heat waves during the period of 2011–2013 were identified and all associated with excess heat-related illnesses. Relative to the average values for the corresponding periods in 2011 and 2012, a total estimated 679 extra heat-related illnesses occurred during three heat waves in 2013. The significant prolonged heat wave effects on total heat-related illnesses during heat waves in three study years have also been identified. The strongest cumulative effect of heat waves was on severe heat diseases in 2013, with a 10-fold increased risk. More males than females, individuals with more severe forms of illness, were more affected by the heat. However, all age groups were vulnerable. Conclusions: Recent heat waves had a substantial and delayed effect on heat illnesses in Ningbo. Relevant active well-organized public health initiatives should be implemented to reduce the adverse effects of heat extremes on the illnesses. [Copyright &y& Elsevier]

Evidence is limited regarding the association between temperatures and health costs. We tried to investigate the association between temperatures and emergency department visits (EDVs) costs in China. Daily data on EDVs costs, weather, air pollution were collected from 17 sites in China during 2014–2018. A quasi–Poisson generalized additive regression with distributed lag nonlinear model was applied to assess the temperature–EDVs cost association. Random-effect meta-analysis was used to pool the estimates from each site. Attributable fractions and national attributable EDVs costs due to heat and cold were calculated. Relative risk (RR) due to extreme heat over 0–7 lag days was 1.14 [95% confidence intervals (CI): 1.08–1.19] and 1.11 (95% CI: 1.07–1.16) for EDVs examination (including treatment) and medicine cost, respectively. People aged 18–44 and those with genitourinary diseases were at higher risk from heat. 0.72% of examination cost and 0.57% of medicine cost were attributed to extreme heat, costing 274 million Chinese Yuan annually. Moderate heat had lower RR but higher attributable fraction of EDVs costs. Exposure to extreme cold over 0–21 lag days increased the risk of medicine cost for people aged 18–44 [RR: 1.30 (95% CI: 1.10–1.55)] and those with respiratory diseases [RR: 1.56 (95% CI: 1.14–2.14)], but had non-statistically significant attributable fraction of the total EDVs cost. Exposure to heat and cold resulted in remarkable health costs. More resources and preparedness are needed to tackle such a challenge as our climate is rapidly changing. • Exposure to heat and cold result in remarkable health costs of patients. • Heat annually attributed 1.21 billion CNY (0.18 billion USD) of costs on EDVs. • People aged 18–44 and with genitourinary diseases were at higher cost risk from heat. • Cold increased EDVs costs risk for people aged 18–44 and with respiratory diseases. [ABSTRACT FROM AUTHOR]

[Display omitted] • There is a nonlinear and lag relationship between ambient temperatures and TAIs. • Both low temperatures and high temperatures increase the incidence of TAIs. • Temperature triggers the highest cumulative effects within 7 lag days. • Temperatures have different effects on TAIs of different age and gender groups. Although traffic accidents cause considerable economic losses and injuries to individuals, families, and communities, little is known about the impact of meteorological factors on the incidence of traffic accident injuries (TAIs). Therefore, a time-series study was conducted to explore the effect of meteorological variables on TAIs in Dalian, Northern China. Poisson generalized linear models (PGLM) combined with distributed lag nonlinear models (DLNM) were used to estimate the association between daily TAIs and ambient temperature in Dalian, China, 2015–2017. The injury data collected by Dalian national injury surveillance hospitals, and meteorological data were extracted and accumulated from the National Meteorological Information Center. Modified the model with variables such as pressure, humidity, precipitation, PM 2.5 , SO 2 , O 3 , day of the week, seasonality, and time trend. In the subgroup analysis, the modification effects of gender and age were also examined. Both high temperatures (RR = 1.198, 95％CI：1.017–1.411) and low temperatures (RR = 1.017, 95％CI：1.001–1.035) increased the risk of TAIs. The cumulative lag effect would last until after the 7th day. While the 40−59 years subgroup seemed to be more vulnerable in high temperature environments, those who are more than 60 years showed higher TAIs in low temperatures for both single-day and cumulative TAI risks. Identifying the association between ambient temperature and traffic injuries could provide needed scientific evidence for relevant public health actions. [ABSTRACT FROM AUTHOR]

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China. Early warning and forecasting are one of the most cost-effective ways for HFMD control and prevention. However, relevant research is limited, especially in China with a large population and diverse climatic characteristics. This study aims to identify local specific HFMD epidemic thresholds and construct a weather-based early warning model for HFMD control and prevention across China. Monthly notified HFMD cases and meteorological data for 22 cities selected from different climate zones from 2014 to 2018 were extracted from the National Notifiable Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. A generalized additive model (GAM) based on meteorological factors was conducted to forecast HFMD epidemics. The receiver operator characteristic curve (ROC) was generated to determine the value of optimal warning threshold. The developed model was solid in forecasting the epidemic of HFMD with all R square (R2) in the 22 cities above 85%, and mean absolute percentage error (MAPE) less than 1%. The warning thresholds varied by cities with the highest threshold observed in Shenzhen (n = 7195) and the lowest threshold in Liaoyang (n = 12). The areas under the curve (AUC) was greater than 0.9 for all regions, indicating a satisfied discriminating ability in epidemics detection. The weather-based HFMD forecasting and early warning model we developed for different climate zones provides needed information on occurrence time and size of HFMD epidemics. An effective early warning system for HFMD could provide sufficient time for local authorities to implement timely interventions to minimize the HFMD morbidity and mortality. [ABSTRACT FROM AUTHOR]

• Exposure to high temperatures resulted in extra burden to emergency departments in China. • People in southern China and counties are more vulnerable to high temperatures. • People under 18 are more vulnerable to high temperatures. • Endocrine, respiratory, digestive diseases and injury are sensitive to high temperatures. Health impacts of high temperatures on hospital emergency department visits (EDVs) have been less reported, especially from developing countries. To investigate high temperature–EDVs relationship in various regions with different climatic characteristics, to explore the regional differences, to identify vulnerable populations, and to provide scientific evidence for climate change adaptation strategies in China. Daily data on weather, air pollution and EDVs were collected from 18 sites in China from June to August during 2014–2017. A quasi–Poisson generalized additive regression model was applied to examine the high temperature–EDVs relationship in each site. Site–specific risks of EDVs were pooled using a random effect meta–analysis model. Stratified analyses were performed by gender, age–groups, cause–specific EDVs and regions. Attributable fractions of EDVs due to high temperatures were calculated in different regions. 1 °C increase in daily mean temperature was associated with 1.07% (95% CI, 0.46–1.67%) increase in EDVs across all study regions. The negative health effects from high temperatures were worse for the people living in southern China, in subtropical monsoon climate zone or in counties, with percentage change of 1.96% (95% CI, 0.92–3.02%), 1.35% (95% CI, 0.95–1.76%) and 1.41% (95% CI, 0.48–2.34%), respectively. People under 18 were more vulnerable to high temperatures. Exposure to high temperatures increased EDVs risks from endocrine, respiratory, and digestive diseases and injury. The attributable fraction due to high temperatures was 8.64% for overall EDVs, 11.70% for the people living in southern China, 10.80% for people living in subtropical monsoon climate zone and 12.65% for the county population. Exposure to high temperatures resulted in extra burden to China's already overloaded hospital emergency departments. More resources are needed to meet increasing demands and effective preventative measurements are warranted to tackle such a challenge. Further studies should pay more attention to both heat and cold-related EDVs risks and socioeconomic cost for better climate change adaptation. [ABSTRACT FROM AUTHOR]

Background: Many studies have shown that heatwaves are associated with an increased prevalence of urinary diseases. However, few national studies have been undertaken in China, and none have considered the associated economic losses. Such information would be useful for health authorities and medical service providers to improve their policy-making and medical resource allocation decisions., Objectives: To explore the association between heatwaves and hospital admissions for urinary diseases and assess the related medical costs and indirect economic losses in China from 2014 to 2019., Methods: Daily meteorological and hospital admission data from 2014 to 2019 were collected from 23 study sites with different climatic characteristics in China. We assessed the heatwave-hospitalization associations and evaluated the location-specific attributable fractions (AFs) of urinary-related hospital admissions due to heatwaves by using a time-stratified case-crossover method with a distributed lag nonlinear model. We then pooled the AFs in a meta-analysis and estimated the national excess disease burden and associated economic losses. We also performed stratified analyses by sex, age, climate zone, and urinary disease subtype., Results: A significant association between heatwaves and urinary-related hospital admissions was found with a relative risk of 1.090 (95 % confidence interval (CI): 1.050, 1.132). The pooled AF was 8.27 % (95%CI: 4.77 %, 11.63 %), indicating that heatwaves during the warm season (May to September) caused 248,364 urinary-related hospital admissions per year, with 2.42 (95%CI: 1.35, 3.45) billion CNY in economic losses, including 2.23 (95%CI: 1.29, 3.14) billion in direct losses and 0.19 (95%CI, 0.06, 0.31) billion in indirect losses, males, people aged 15-64 years, residents of temperate continental climate zones, and patients with urolithiasis were at higher risk., Conclusion: Tailored community health campaigns should be developed and implemented to reduce the adverse health effects and economic losses of heatwave-related urinary diseases, especially in the context of climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Evidence of the effectiveness of intervention against extreme heat remains unclear, especially among children, one of the vulnerable populations. This study aimed to evaluate the effectiveness of a primary school-based intervention program against heatwave and climate change in China to provide evidence for development of policies for adaptation to climate change., Methods: Two primary schools in Dongtai City, Jiangsu Province, China, were randomly selected as intervention and control schools (CTR registration number: ChiCTR2200056005). Health education was conducted at the intervention school to raise students' awareness and capability to respond to extreme heat during May to September in 2017. Knowledge, attitude, and practice (KAP) of students and their parents at both schools were investigated by questionnaire surveys before and after intervention. The changes in KAP scores after intervention were evaluated using multivariable difference-in-difference (DID) analysis, controlling for age, sex, etc. Results: The scores of knowledge, attitude, and practice of students and their parents increased by 19.9% (95%CI: 16.3%, 23.6%) and 22.5% (95%CI: 17.8%, 27.1%); 9.60% (95%CI: 5.35%, 13.9%) and 7.22% (95%CI: 0.96%, 13.5%); and 9.94% (95%CI: 8.26%, 18.3%) and 5.22% (95%CI: 0.73%, 9.71%), respectively, after intervention. The KAP score changes of boys were slightly higher than those of girls. Older students had higher score changes than younger students. For parents, the higher the education level, the greater the score change, and change in scores was greater in females than in males. All the health education activities in the program were significantly correlated with the changes in KAP scores of primary school students after intervention, especially those curricula with interesting activities and experiential learning approaches., Conclusions: Heat and health education program in primary school was an effective approach to improve cognition and behavior for both students and their parents to better adapt to heatwaves and climate change. The successful experience can be generalized to respond to the increasing extreme weather/climate events in the context of climate change, such as heatwaves, and other emergent occasions or public health education, such as the control and prevention of COVID-19.

The impact of temperature and rainfall on the occurrence of typhoid/paratyphoid fever are not fully understood. This study aimed to characterize the effect of daily ambient temperature and total rainfall on the incidence of typhoid/paratyphoid in a sub-tropical climate city of China and to identify the vulnerable groups for disease prevention. Daily notified typhoid/paratyphoid fever cases and meteorological data for Taizhou from 2005 to 2013 were extracted from the National Notifiable Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. Distributed lag nonlinear model was used to quantify the association between daily mean temperature, total rainfall, and typhoid/paratyphoid fever. Subgroup analyses by gender, age, and occupation were conducted to identify the vulnerable groups. A total of 625 typhoid fever cases and 1,353 paratyphoid fever cases were reported during the study period. An increased risk of typhoid fever was detected with the increase of temperature (Each 2°C rise resulted in 6%, 95% [confidence interval] CI: 2-10% increase in typhoid cases), while the increased risk was associated with the higher temperature for paratyphoid (the highest cumulative risk of temperature was 33.40 [95% CI: 12.23-91.19] at 33°C). After the onset of mild precipitation, the relative risk of typhoid fever increased in a short-lasting and with a 13-26 days delay, and the risk was no significant after the continuous increase of precipitation (the highest cumulative risk of rainfall was 24.96 [95% CI: 4.54-87.21] at 100 mm). Whereas the risk of paratyphoid fever was immediate and long lasting, and increase rapidly with the increase of rainfall (each 100 mm increase was associated with 26% increase in paratyphoid fever cases). Significant temperature-typhoid/paratyphoid fever and rainfall-typhoid/paratyphoid fever associations were found in both genders and those aged 0-4 years old, 15-60 years old, farmers, and children. Characterized with a lagged, nonlinear, and cumulative effect, high temperature and rainfall could increase the risk of typhoid/paratyphoid fever in regions with a subtropical climate. Public health interventions such as early warning and community health education should be taken to prevent the increased risk of typhoid/paratyphoid fever, especially for the vulnerable groups.

Although strict lockdown measurements implemented during the COVID-19 pandemic have dramatically reduced the anthropogenic-based emissions, changes in air quality and its health impacts remain unclear in China. We comprehensively described air pollution during and after the lockdown periods in 2020 compared with 2018-2019, and estimated the mortality burden indicated by the number of deaths and years of life lost (YLL) related to the air pollution changes. The mean air quality index (AQI), PM 10 , PM 2.5 , NO 2 , SO 2 and CO concentrations during the lockdown across China declined by 18.2 (21.2%), 27.0 μg/m 3 (28.9%), 10.5 μg/m 3 (18.3%), 8.4 μg/m 3 (44.2%), 13.1 μg/m 3 (38.8%), and 0.3 mg/m 3 (27.3%) respectively, when compared to the same periods during 2018-2019. We observed an increase in O 3 concentration during the lockdown by 5.5 μg/m 3 (10.4%), and a slight decrease after the lockdown by 3.4 μg/m 3 (4.4%). As a result, there were 51.3 (95%CI: 32.2, 70.1) thousand fewer premature deaths (16.2 thousand during and 35.1 thousand after the lockdown), and 1066.8 (95%CI: 668.7, 1456.8) thousand fewer YLLs (343.3 thousand during and 723.5 thousand after the lockdown) than these in 2018-2019. Our findings suggest that the COVID-19 lockdown has caused substantial decreases in air pollutants except for O 3 , and that substantial human health benefits can be achieved when strict control measures for air pollution are taken to reduce emissions from vehicles and industries. Stricter tailored policy solutions of air pollution are urgently needed in China and other countries, especially in well-developed industrial regions, such as upgrading industry structure and promoting green transportation., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Malaria is a climate-sensitive infectious disease. Many ecological studies have investigated the independent impacts of ambient temperature on malaria. However, the optimal temperature measures of malaria and its interaction with other meteorological factors on malaria transmission are less understood. This study aims to investigate the effect of ambient temperature and its interactions with relative humidity and rainfall on malaria in Suzhou, a temperate climate city in Anhui Province, China. Weekly malaria and meteorological data from 2005 to 2012 were obtained for Suzhou. A distributed lag nonlinear model was conducted to quantify the effect of different temperature measures on malaria. The best measure was defined as that with the minimum quasi-Akaike information criterion. GeoDetector and Poisson regression models were employed to quantify the interactions of temperature, relative humidity, and rainfall on malaria transmission. A total of 13,382 malaria cases were notified in Suzhou from 2005 to 2012. Each 5 °C rise in average temperature over 10 °C resulted in a 22% (95% CI: 17%, 28%) increase in malaria cases at lag of 4 weeks. In terms of cumulative effects from lag 1 to 8 weeks, each 5 °C increase over 10 °C caused a 175% growth in malaria cases (95% CI: 139%, 216%). Average temperature achieved the best performance in terms of model fitting, followed by minimum temperature, most frequent temperature, and maximum temperature. Temperature had an interactive effect on malaria with relative humidity and rainfall. High temperature together with high relative humidity and high rainfall could accelerate the transmission of malaria. Meteorological factors may affect malaria transmission interactively. The research findings could be helpful in the development of weather-based malaria early warning system, especially in the context of climate change for the prevention of possible malaria resurgence.

Background: The adverse effects of heat on workers' health and work productivity are well documented. However, the resultant economic consequences and productivity loss are less understood. This review aims to summarize the retrospective and potential future economic burden of workplace heat exposure in the context of climate change., Methods: Literature was searched from database inception to October 2020 using Embase, PubMed, and Scopus. Articles were limited to original human studies investigating costs from occupational heat stress in English., Results: Twenty studies met criteria for inclusion. Eighteen studies estimated costs secondary to heat-induced labor productivity loss. Predicted global costs from lost worktime, in US$, were 280 billion in 1995, 311 billion in 2010 (≈0.5% of GDP), 2.4-2.5 trillion in 2030 (>1% of GDP) and up to 4.0% of GDP by 2100. Three studies estimated heat-related healthcare expenses from occupational injuries with averaged annual costs (US$) exceeding 1 million in Spain, 1 million in Guangzhou, China and 250,000 in Adelaide, Australia. Low- and middle-income countries and countries with warmer climates had greater losses as a proportion of GDP. Greater costs per worker were observed in outdoor industries, medium-sized businesses, amongst males, and workers aged 25-44 years., Conclusions: The estimated global economic burden of occupational heat stress is substantial. Climate change adaptation and mitigation strategies should be implemented to likely minimize future costs. Further research exploring the relationship between occupational heat stress and related expenses from lost productivity, decreased work efficiency and healthcare, and costs stratified by demographic factors, is warranted. Key messages. The estimated retrospective and future economic burden from occupational heat stress is large. Responding to climate change is crucial to minimize this burden. Analyzing heat-attributable occupational costs may guide the development of workplace heat management policies and practices as part of global warming strategies., (Copyright © 2021 Elsevier Inc. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions., Methods: Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature., Results: A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier., Conclusions: The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: The link between heat exposure and adverse health outcomes in workers is well documented and a growing body of epidemiological evidence from various countries suggests that extreme heat may also contribute to increased risk of occupational injuries (OI). Previously, there have been no comparative reviews assessing the risk of OI due to extreme heat within a wide range of global climate zones. The present review therefore aims to summarise the existing epidemiological evidence on the impact of extreme heat (hot temperatures and heatwaves (HW)) on OI in different climate zones and to assess the individual risk factors associated with workers and workplace that contribute to heat-associated OI risks., Methods: A systematic review of published peer-reviewed articles that assessed the effects of extreme heat on OI among non-military workers was undertaken using three databases (PubMed, Embase and Scopus) without temporal or geographical limits from database inception until July 2020. Extreme heat exposure was assessed in terms of hot temperatures and HW periods. For hot temperatures, the effect estimates were converted to relative risks (RR) associated with 1 °C increase in temperature above reference values, while for HW, effect estimates were RR comparing heatwave with non-heatwave periods. The patterns of heat associated OI risk were investigated in different climate zones (according to Köppen Geiger classification) based on the study locations and were estimated using random-effects meta-analysis models. Subgroup analyses according to workers' characteristics (e.g. gender, age group, experience), nature of work (e.g. physical demands, location of work i.e. indoor/outdoor) and workplace characteristics (e.g. industries, business size) were also conducted., Results: A total of 24 studies published between 2005 and 2020 were included in the review. Among these, 22 studies met the eligibility criteria, representing almost 22 million OI across six countries (Australia, Canada, China, Italy, Spain, and USA) and were included in the meta-analysis. The pooled results suggested that the overall risk of OI increased by 1% (RR 1.010, 95% CI: 1.009-1.011) for 1 °C increase in temperature above reference values and 17.4% (RR 1.174, 95% CI: 1.057-1.291) during HW. Among different climate zones, the highest risk of OI during hot temperatures was identified in Humid Subtropical Climates (RR 1.017, 95% CI: 1.014-1.020) followed by Oceanic (RR 1.010, 95% CI: 1.008-1.012) and Hot Mediterranean Climates (RR 1.009, 95% CI: 1.008-1.011). Similarly, Oceanic (RR 1.218, 95% CI: 1.093-1.343) and Humid Subtropical Climates (RR 1.213, 95% CI: 0.995-1.431) had the highest risk of OI during HW periods. No studies assessing the risk of OI in Tropical regions were found. The effects of hot temperatures on the risk of OI were acute with a lag effect of 1-2 days in all climate zones. Young workers (age < 35 years), male workers and workers in agriculture, forestry or fishing, construction and manufacturing industries were at high risk of OI during hot temperatures. Further young workers (age < 35 years), male workers and those working in electricity, gas and water and manufacturing industries were found to be at high risk of OI during HW., Conclusions: This review strengthens the evidence on the risk of heat-associated OI in different climate zones. The risk of OI associated with extreme heat is not evenly distributed and is dependent on underlying climatic conditions, workers' attributes, the nature of work and workplace characteristics. The differences in the risk of OI across different climate zones and worker subgroups warrant further investigation along with the development of climate and work-specific intervention strategies., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Although previous studies have reported that meteorological factors might affect the risk of Japanese encephalitis (JE), the relationship between meteorological factors and JE remains unclear. This study aimed to evaluate the relationship between meteorological factors and JE and identify the threshold temperature. Daily meteorological data and JE surveillance data in Dazhou, Sichuan, were collected for the study period from 2005 to 2012 (restricting to May-October because of the seasonal distribution of JE). A distributed lag nonlinear model was used to analyze the lagged and cumulative effect of daily average temperature and daily rainfall on JE transmission. A total of 622 JE cases were reported over the study period. We found JE was positively associated with daily average temperature and daily rainfall with a 25-day lag and 30-day lag, respectively. The threshold value of the daily average temperature is 20°C. Each 5°C increase over the threshold would lead to a 13% (95% CI: 1-17.3%) increase in JE. Using 0 mm as the reference, a daily rainfall of 100 mm would lead to a 132% (95% CI: 73-311%) increase in the risk of JE. Japanese encephalitis is climate-sensitive; meteorological factors should be taken into account for the future prevention and control measure making, especially in a warm and rainy weather condition.

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 ( ≤ 5 y or > 5 y ) 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.

Background: Very few studies have focused on the relationship between ambient apparent temperature (AT) and admission of mental and behaviour disorders (MDs). Therefore, a time-series study was conducted in Yancheng, China, to explore the effects of AT on the daily emergency admissions of patients with MDs over the period of 2014-17., Methods: A quasi-Poisson generalized linear model (GLM) combined with a distributed lag non-linear model (DLNM) was adopted to explore the associations after adjusting for time trend, day of the week, humidity, sunshine duration, rainfall, holidays and air pollutants. In the subgroup analysis, the modification effects of age and sex were also examined., Results: Overall, 8438 cases of MDs emergency admissions were identified. With the apparent temperature with the minimum number of admissions (- 3.4 °C) serving as a reference, a positive correlation emerged between high AT and daily emergency admissions of patients with MDs in Yancheng, China, with the lagged effect of 1 to 5 days. The subgroup analysis demonstrated a positive relationship between AT and MDs emergency admissions among males and individuals younger than 45 years old, with no lagged effect., Conclusions: The results will provide important scientific evidence for mental health policy-makers and practitioners for possible intervention, especially among the vulnerable populations.

Few studies have examined the attributable fraction (AF) of temperature to mortality and Years of Life Lost (YLL), especially in developing countries. This study aims to explore the short-term effect of the cold and hot temperatures on the cause-specific YLL and mortality, discover the attributable contributions from the temperature variations, and identify the vulnerable populations in Weifang, China. Daily registered death information and meteorological data over the period 2010-2016 were obtained in Weifang, a northern Chinese city. Generalized additive Poisson and Gaussian regression models were used to assess the impacts of temperatures on both mortality and YLL, explore the AF of the temperature variations on mortality, after adjusting for other covariates. Both hot and cold temperatures have had significant negative impacts on cause-specific mortality counts and YLL, with heat presented an acute and short effect and the cold temperatures had delayed effects and lasted for several days. In terms of the attributable fraction calculations, the contributions from cold effects was higher than that of hot effects on non-accidental, cardiovascular, and respiratory deaths (YLL 10.88 vs. 1.23%, 19.58 vs. 1.71%, and 14.47 vs. 3.05%; mortality 13.97 vs. 1.65%, 19.20 vs. 1.59%, and 14.89 vs. 3.09%), respectively. The elderly and women and people with low education level were the most vulnerable. The findings will provide important scientific evidences and policy implications for developing adaptation strategies to reduce the adverse effect of cold and hot exposure in Weifang, in terms of resource allocation, healthcare workforce capacity building, and community health education, especially for the vulnerable groups.

Background: Dengue is a significant climate-sensitive disease. Public health professionals play an important role in prevention and control of the disease. This study aimed to explore dengue control and prevention in the context of climate change in China., Methods: A cross-sectional survey was conducted among 630 public health professionals in 2015. Descriptive analysis and logistic regression were performed., Results: More than 80% of participants from southwest and central China believed climate change would affect dengue. However, participants from northeast China were less likely to believe so (65%). Sixty-nine percent of participants in Yunnan perceived that dengue had emerged/re-emerged in recent years, compared with 40.6% in Henan and 23.8% in Liaoning. Less than 60% of participants thought current prevention and control programs had been effective. Participants believed mosquitoes in high abundance, imported cases and climate change were main risk factors for dengue in China., Conclusion: There were varying views of dengue in China. Professionals in areas susceptible to dengue were more likely to be concerned about climate change and dengue. Current prevention and control strategies need to be improved. Providing more information for staff in lower levels of Centers for Disease Control and Prevention may help in containing a possible increase of dengue., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The aim of this study was to investigate the prevalence and factors associated with suicidal ideation among HIV-positive men who have sex with men (MSM) in Anhui, China. A cross-sectional study was conducted to recruit HIV-positive MSM in Anhui, China. A total of 184 HIV-positive MSM gave informed consent and completed the interview. Correlates of suicidal ideation were assessed using multivariable logistic regression. Fifty-seven (31%) of HIV-positive MSM had suicidal ideations within six months before the interview. Multivariable analyses showed that learning of their HIV status in the past 12 months (adjusted odds ratio (AOR) = 3.4, 95% CI = 1.6-7.3), perceived HIV stigma (AOR = 2.4, 95% CI = 1.1-5.2), depression symptoms (AOR = 2.6, 95% CI = 1.1-5.9) and anxiety symptoms (AOR = 2.7, 95% CI = 1.2-6.1) were significantly associated with the suicidal ideation among HIV-positive MSM. The results indicated that suicidal ideation was common among HIV-positive MSM in Anhui, China. There is an urgent need to establish psychological counselling services among HIV-positive MSM in China. Targeting of these potential risk factors could be an effective approach to reduce the suicide risk among this high-risk subgroup by the implementation of early intervention measurements., (© The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.)

Background: A better understanding of public perceptions, attitude and behavior in relation to climate change will provide an important foundation for government׳s policy-making, service provider׳s guideline development and the engagement of local communities. The purpose of this study was to assess the perception towards climate change, behavior change, mitigation and adaptation measures issued by the central government among the health professionals in the Centres for Disease Control and Prevention (CDC) in China., Methods: In 2013, a cross-sectional questionnaire survey was undertaken among 314 CDC health professionals in various levels of CDC in Shanxi Province, China. Descriptive analyses were performed., Results: More than two thirds of the respondents believed that climate change has happened at both global and local levels, and climate change would lead to adverse impacts to human beings. Most respondents (74.8%) indicated the emission of greenhouse gases was the cause of climate change, however there was a lack of knowledge about greenhouse gases and their sources. Media was the main source from which respondents obtained the information about climate change. A majority of respondents showed that they were willing to change behavior, but their actions were limited. In terms of mitigation and adaptation measures issued by the Chinese Government, respondents׳ perception showed inconsistency between strategies and relevant actions. Moreover, although the majority of respondents believed some strategies and measures were extremely important to address climate change, they were still concerned about economic development, energy security, and local environmental protection., Conclusion: There are gaps between perceptions and actions towards climate change among these health professionals. Further efforts need to be made to raise the awareness of climate change among health professionals, and to promote relevant actions to address climate change in the context of the proposed policies with local sustainable development., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Introduction: Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose., Methodology and Principal Findings: Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags., Conclusions: Imported DF cases and mosquito density play a critical role in local DF transmission, together with weather variables. The establishment of an early warning system, using existing surveillance datasets will help to control and prevent dengue in Guangzhou, China.