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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]

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. A cross-sectional survey was conducted among 630 public health professionals in 2015. Descriptive analysis and logistic regression were performed. 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. 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. [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]

Japanese encephalitis (JE) is one of the major vector-borne diseases in Southeast Asia and the Western Pacific region, posing a threat to human health. In rural and suburban areas, traditional rice farming and intensive pig breeding provide an ideal environment for both mosquito development and the transmission of JEV among human beings. Combining surveillance data for mosquito vectors, human JE cases, and environmental conditions in Changsha, China, 2004–2009, generalized threshold models were constructed to project the mosquito and JE dynamics. Temperature and rainfall were found to be closely associated with mosquito density at 1, and 4 month lag, respectively. The two thresholds, maximum temperature of 22–23 °C for mosquito development and minimum temperature of 25–26 °C for JEV transmission, play key roles in the ecology of JEV. The model predicts that, in the upper regime, a 1 g/m 3 increase in absolute humidity would on average increase human cases by 68–84%. A shift in mosquito species composition in 2007 was observed, and possibly caused by a drought. Effective predictive models could be used in risk management to provide early warnings for potential 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]

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]

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]

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]

• 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]