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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]

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]