BackgroundThe 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.ObjectiveWe examined the potential impact of climate variability on HFRS transmission and developed climate-based forecasting models for HFRS in northeastern China.MethodsWe 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.ResultsCross-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 long-term 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.ConclusionsClimate variability plays a significant role in HFRS transmission in northeastern China. The model developed in this study has implications for HFRS control and prevention.

BackgroundHemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by Hantaviruses. It is endemic in all 31 provinces, autonomous regions, and metropolitan areas in mainland China where human cases account for 90% of the total global cases. Shandong Province is among the most serious endemic areas. HFRS cases in Shandong Province were first reported in Yutai County in 1968. Since then, the disease has spread across the province, and as of 2005, all 111 counties were reported to have local human infections. However, causes underlying such rapid spread and wide distribution remain less well understood.Methods and FindingsHere we report a spatiotemporal analysis of human HFRS cases in Shandong using data spanning 1973 to 2005. Seasonal incidence maps and velocity vector maps were produced to analyze the spread of HFRS over time in Shandong Province, and a panel data analysis was conducted to explore the association between HFRS incidence and climatic factors. Results show a rapid spread of HFRS from its epicenter in Rizhao, Linyi, Weifang Regions in southern Shandong to north, east, and west parts of the province. Based on seasonal shifts of epidemics, three epidemic phases were identified over the 33-year period. The first phase occurred between 1973 and 1982 during which the foci of HFRS was located in the south Shandong and the epidemic peak occurred in the fall and winter, presenting a seasonal characteristic of Hantaan virus (HTNV) transmission. The second phase between 1983 and 1985 was characterized by northward and westward spread of HFRS foci, and increases in incidence of HFRS in both fall-winter and spring seasons. The human infections in the spring reflected a characteristic pattern of Seoul virus (SEOV) transmission. The third phase between 1986 and 2005 was characterized by the northeast spread of the HFRS foci until it covered all counties, and the HFRS incidence in the fall-winter season decreased while it remained high in the spring. In addition, our findings suggest that precipitation, humidity, and temperature are major environmental variables that are associated with the seasonal variation of HFRS incidence in Shandong Province.ConclusionsThe spread of HFRS in Shandong Province may have been accompanied by seasonal shifts of HTNV-dominated transmission to SEOV-dominated transmission over the past three decades. The variations in HFRS incidence were significantly associated with local precipitation, humidity, and temperature.

BackgroundScrub typhus is endemic in the Asia-Pacific region including China, and the number of reported cases has increased dramatically in the past decade. However, the spatial-temporal dynamics and the potential risk factors in transmission of scrub typhus in mainland China have yet to be characterized.ObjectiveThis study aims to explore the spatiotemporal dynamics of reported scrub typhus cases in mainland China between January 2006 and December 2014, to detect the location of high risk spatiotemporal clusters of scrub typhus cases, and identify the potential risk factors affecting the re-emergence of the disease.MethodMonthly cases of scrub typhus reported at the county level between 2006 and 2014 were obtained from the Chinese Center for Diseases Control and Prevention. Time-series analyses, spatiotemporal cluster analyses, and spatial scan statistics were used to explore the characteristics of the scrub typhus incidence. To explore the association between scrub typhus incidence and environmental variables panel Poisson regression analysis was conducted.ResultsDuring the time period between 2006 and 2014 a total of 54,558 scrub typhus cases were reported in mainland China, which grew exponentially. The majority of cases were reported each year between July and November, with peak incidence during October every year. The spatiotemporal dynamics of scrub typhus varied over the study period with high-risk clusters identified in southwest, southern, and middle-eastern part of China. Scrub typhus incidence was positively correlated with the percentage of shrub and meteorological variables including temperature and precipitation.ConclusionsThe results of this study demonstrate areas in China that could be targeted with public health interventions to mitigate the growing threat of scrub typhus in the country.

Data from all reported cases of 2009 pandemic influenza A (H1N1) were obtained from the China Information System for Disease Control and Prevention. The spatiotemporal distribution patterns of cases were characterized through spatial analysis. The impact of travel-related risk factors on invasion of the disease was analyzed using survival analysis, and climatic factors related to local transmission were identified using multilevel Poisson regression, both at the county level. The results showed that the epidemic spanned a large geographic area, with the most affected areas being in western China. Significant differences in incidence were found among age groups, with incidences peaking in school-age children. Overall, the epidemic spread from southeast to northwest. Proximity to airports and being intersected by national highways or freeways but not railways were variables associated with the presence of the disease in a county. Lower temperature and lower relative humidity were the climatic factors facilitating local transmission after correction for the effects of school summer vacation and public holidays, as well as population density and the density of medical facilities. These findings indicate that interventions focused on domestic travel, population density, and climatic factors could play a role in mitigating the public health impact of future influenza pandemics.

Abstract. Scrub typhus is a vector-borne disease, which has recently reemerged in China. In this study, we describe the distribution and incidence of scrub typhus cases in China from 2006 to 2014 and quantify differences in scrub typhus cases with respect to sex, age, and occupation. The results of our study indicate that the annual incidence of scrub typhus has increased during the study period. The number of cases peaked in 2014, which was 12.8 times greater than the number of cases reported in 2006. Most (77.97%) of the cases were reported in five provinces (Guangdong, Yunnan, Anhui, Fujian, and Shandong). Our study also demonstrates that the incidence rate of scrub typhus was significantly higher in females compared to males (P < 0.001) and was highest in the 60-69 year age group, and that farmers had a higher incidence rate than nonfarmers (P < 0.001). Different seasonal trends were identified in the number of reported cases between the northern and southern provinces of China. These findings not only demonstrate that China has experienced a large increase in scrub typhus incidence, but also document an expansion in the geographic distribution throughout the country.

Abstract. Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in Shandong Province, China. In this study, we combined ecologic niche modeling with geographic information systems (GIS) and remote sensing techniques to identify the risk factors and affected areas of hantavirus infections in rodent hosts. Land cover and elevation were found to be closely associated with the presence of hantavirus-infected rodent hosts. The averaged area under the receiver operating characteristic curve was 0.864, implying good performance. The predicted risk maps based on the model were validated both by the hantavirus-infected rodents' distribution and HFRS human case localities with a good fit. These findings have the applications for targeting control and prevention efforts. Ecological niche models. The ENMs were developed to understand environmental variation associated with the distribution of infected rodent reservoirs. 21 A recent introduced presence-only distribution modeling technique-the Maximum Entropy approach, was applied in various domains and achieved high predictive accuracy, [22][23][24][25][26][27][28] and showed the best predictive power across all sample sizes. 3,25,[29][30][31] Detailed descriptions of the Maximum Entropy program (MAXENT, version 3.3.1) can be found in References 25 and 32. There were 33 sample sites positive for hantavirus infection in rodents from the study areas during [2005][2006][2007][2008], and 10,000 background points (2,500 for each year) are sampled by a spatially random method. The importance of EGVs contributing to the distribution of hantavirus infection was determined by three analyses. In the jackknife analysis of the average gain with training and test data, models were respectively created with each individual variable, all the remaining variables and all variables in turn. Next, corresponding results were compared. Second, the average values of area under the curve (AUC) of 10 iterations were compared. Third, the average percentage contribution of each variable was evaluated. In each iteration of the training algorithm, the increase or decrease in regularized gain was added or subtracted with the input of the corresponding variable, giving a heuristic estimate of variable contribution for the model. 25The final model predictors were selected using a stepwise fashion, as saturated models are likely to be oversized, overfitted, or redundant. 33,34 To determine variable significance, several models using the same occurrence data but different variable sets were examined. These included models with single predictors alone, as well as leaving out individual predictors from suites of variables. The loss in modeling performance for individual models were compared with the model generated using all predictors. The algorithm converges to the optimum probable distribution, and the gain is interpreted as representing how much better the distribution fits the sample points than a uniform distribution. 25,29,32 Model evaluation. To validate the accuracy and p...

BackgroundQinghai-Tibetan Plateau of China is known to be the plague endemic region where marmot (Marmota himalayana) is the primary host. Human plague cases are relatively low incidence but high mortality, which presents unique surveillance and public health challenges, because early detection through surveillance may not always be feasible and infrequent clinical cases may be misdiagnosed.MethodsBased on plague surveillance data and environmental variables, Maxent was applied to model the presence probability of plague host. 75% occurrence points were randomly selected for training model, and the rest 25% points were used for model test and validation. Maxent model performance was measured as test gain and test AUC. The optimal probability cut-off value was chosen by maximizing training sensitivity and specificity simultaneously.ResultsWe used field surveillance data in an ecological niche modeling (ENM) framework to depict spatial distribution of natural foci of plague in Qinghai-Tibetan Plateau. Most human-inhabited areas at risk of exposure to enzootic plague are distributed in the east and south of the Plateau. Elevation, temperature of land surface and normalized difference vegetation index play a large part in determining the distribution of the enzootic plague.ConclusionsThis study provided a more detailed view of spatial pattern of enzootic plague and human-inhabited areas at risk of plague. The maps could help public health authorities decide where to perform plague surveillance and take preventive measures in Qinghai-Tibetan Plateau.

Background:There is limited evidence about the association between ambient temperature and the incidence of pediatric hand, foot, and mouth disease (HFMD) nationwide in China.Objectives:We examined the childhood temperature-HFMD associations across mainland China, and we projected the change in HFMD cases due to projected temperature change by the 2090s.Methods:Data on daily HFMD (children 0–14 y old) counts and weather were collected from 362 sites during 2009–2014. Daily temperature by the 2090s was downscaled under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. Temperature-HFMD associations were quantified using a two-stage Poisson regression with a distributed lag nonlinear model. The impact of changes in temperature on the incidence of HFMD was estimated by combining the fitted temperature-HFMD associations with projected temperatures under each scenario, assuming a constant population structure. Sensitivity analyses were performed to assess the influence of primary model assumptions.Results:During 2009–2014, >11 million HFMD cases were reported. In most regions, the temperature-HFMD association had an inverted U shape with a peak at approximately 20°C, but the association leveled off or continued to increase in the Inner Mongolia and Northeast regions. When estimates were pooled across all regions and the population size was held constant, the projected incidence of HFMD increased by 3.2% [95% empirical confidence interval (eCI): −13.5%, 20.0%] and 5.3% (95% eCI: −33.3%, 44.0%) by the 2090s under the RCP 4.5 and 8.5 scenarios, respectively. However, regional projections suggest that HFMD may decrease with climate change in temperate areas of central and eastern China.Conclusion:Our estimates suggest that the association between temperature and HFMD varies across China and that the future impact of climate change on HFMD incidence will vary as well. Other factors, including changes in the size of the population at risk (children 0–14 y old) will also influence future HFMD trends. https://doi.org/10.1289/EHP3062