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Background: China's "13th 5-Year Plan" (2016-2020) for the prevention and control of sudden acute infectious diseases emphasizes that epidemic monitoring and epidemic focus surveys in key areas are crucial for strengthening national epidemic prevention and building control capacity. Establishing an epidemic hot spot areas and prediction model is an effective means of accurate epidemic monitoring and surveying. Objective: This study predicted hemorrhagic fever with renal syndrome (HFRS) epidemic hot spot areas, based on multi-source environmental variable factors. We calculated the contribution weight of each environmental factor to the morbidity risk, obtained the spatial probability distribution of HFRS risk areas within the study region, and detected and extracted epidemic hot spots, to guide accurate epidemic monitoring as well as prevention and control. Methods: We collected spatial HFRS data, as well as data on various types of natural and human social activity environments in Hunan Province from 2010 to 2014. Using the information quantity method and logistic regression modeling, we constructed a risk-area-prediction model reflecting the epidemic intensity and spatial distribution of HFRS. Results: The areas under the receiver operating characteristic curve of training samples and test samples were 0.840 and 0.816. From 2015 to 2019, HRFS case site verification showed that more than 82% of the cases occurred in high-risk areas., Discussion: This research method could accurately predict HFRS hot spot areas and provided an evaluation model for Hunan Province. Therefore, this method could accurately detect HFRS epidemic high-risk areas, and effectively guide epidemic monitoring and surveyance., Competing Interests: The authors have declared that no competing interests exist.

Objective: To analyze the epidemic characteristics and spatio-temporal distribution of hemorrhagic fever with renal syndrome (HFRS) in Guangzhou from 2010 to 2019 and provide a basis for prevention and control strategies. Methods: The data of HFRS was from National Disease Reporting Information System and the epidemic investigation. A descriptive analysis was used. OpenGeoDa 1.2.0 software was used for global spatial autocorrelation and local spatial autocorrelation analysis. SatScan 9.6 software was used for detecting the hot spot area in time and space. ArcGIS 10.2 software was used for map visualization. Results: 1 298 cases of HFRS were reported, and three patients died in Guangzhou in 2010-2019. The annual incidence rate was 0.99/100 000. The proportion of 21-50 years old cases accounted for 70.88% and the male to female ratio was 2.98∶1. Most patients were house workers or unemployed, accounting for 31.28%, followed by business servants (accounting for 17.33%). The incidence peak in spring and winter accounted for 33.74% and 26.35% of the year. All districts reported cases in recent ten years. A total of 407 cases had been reported in Haizhu district, accounting for 31.36% of the total number of cases in the whole city. The annual incidence rate was 2.52/100 000. The number of reported cases and the annual incidence rate were the highest in Guangzhou. The clustered area showed that there was spatio-temporal clustering in Guangzhou. The aggregation area was mainly concentrated in the urban villages adjacent to Wan-mu orchard and the Haizhu Lake Wetland Park in Haizhu district (logarithmic likelihood ratio was 44.08, P <0.001). Conclusions: The prevalence and concentration of HFRS in winter and spring Guangzhou city from 2010 to 2019, showed a high incidence. Young and middle-aged men engaged in domestic and unemployed, and commercial services appeared the main risk groups. The urban-rural junction with many immigrants and low health environment, streets adjacent to Wan-mu orchard, and the Haizhu Lake Wetland Park in Haizhu district were the important regions for preventing and controlling HFRS. The government should formulate prevention and control measures to curb the rise and spread of the HFRS epidemic.

Are predators of rodents beneficial for public health? This question focuses on whether predators regulate the spillover transmission of rodent-borne diseases. No clear answer has emerged because of the complex linkages across multiple trophic levels and the lack of accessible data. Although previous empirical findings have suggested ecological mechanisms, such as resource partitioning, which implies protective effects from predator species richness, epidemiological evidence is needed to bolster these arguments. Thus, we investigated the association between predator species richness and incidence of rodent-borne haemorrhagic fever with renal syndrome in the human population using district-level longitudinal data of 13 years for South Korea. With the exception of districts with low species richness, we found a significant negative association between the incidence of haemorrhagic fever with renal syndrome and the species richness of both avian and mammalian predators; the trends for both predator types were similar. Thus, biodiversity conservation may benefit public health.

Background: Haemorrhagic fever with renal syndrome (HFRS) is a natural epidemic disease caused by various types of viruses of the genus Hantavirus, which are mainly transmitted by contact with the infected rodents and their droppings. Pregnancy complicated with HFRS is rare; however, adverse maternal and foetal outcomes may be noted. In this report, we describe a case involving a pregnant woman with HFRS who was in a state of multiple organ dysfunction syndrome (MODS) and was successfully treated with continuous renal replacement therapy (CRRT)., Case Presentation: A 32-year-old pregnant woman at 29 weeks of gestation was hospitalised for a fever and upper respiratory tract infection due to HFRS in winter. Persistent fever, coagulation disorder, thrombocytopenia, electrolyte imbalance, abnormal liver function, and renal failure were noted during the progression of the disease. The patient was treated with CRRT. She recovered after 21 days, and delivered a live infant by caesarean section at 38 weeks of gestation. Furthermore, obvious abnormalities were not detected during the follow-up of the mother and infant at 42 days, 3 months, 6 months, and 1 year after the delivery., Conclusions: Early diagnosis, timely application of CRRT, and comprehensive treatment may be essential for the successful treatment of patients with HFRS during pregnancy.

Introduction : Hemorrhagic fever with renal syndrome (HFRS) is a life-threatening public health problem in China, accounting for ~90% of HFRS cases reported globally. Accurate analysis and prediction of the HFRS epidemic could help to establish effective preventive measures. Materials and Methods : In this study, the geographical information system (GIS) explored the spatiotemporal features of HFRS, the wavelet power spectrum (WPS) unfolded the cyclical fluctuation of HFRS, and the wavelet neural network (WNN) model predicted the trends of HFRS outbreaks in mainland China. Results : A total of 209,209 HFRS cases were reported in mainland China from 2004 to 2019, with the annual incidence ranged from 0 to 13.05 per 100,0000 persons at the province level. The WPS proved that the periodicity of HFRS could be half a year, 1 year, and roughly 7-year at different time intervals. The WNN structure of 12-6-1 was set up as the fittest forecasting model for the HFRS epidemic. Conclusions : This study provided several potential support tools for the control and risk-management of HFRS in China., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Zou and Sun.)

In recent years, hemorrhagic fever with renal syndrome (HFRS) incidence has been becoming a severe public health problem again due to its significant increase in Shaanxi Province, China. Baoji, located in the Guanzhong Plain in the central part of Shaanxi Province, has been severely affected by HFRS since its first emergence in 1955. To better understand the epidemiology of orthohantaviruses infection in humans and the causative agents carried by the rodents, the long-term incidence patterns were analyzed and a molecular epidemiological investigation of orthohantaviruses infection in humans and rodents was performed. During 1984-2019, 13,042 HFRS cases were registered in Baoji, including 275 death cases. Except the first high prevalence of HFRS in 1988-1993, another two epidemic peaks were observed in 1998-2003 and 2012, respectively, although vaccination project was started since 1996. During the same period, HFRS cases in Baoji mainly were recorded in winter suggesting they may be caused by Hantaan orthohantavirus (HTNV), while a small peak of HFRS was also found in summer with unknown reason. Nucleotide identity and phylogenetic analyses demonstrated that a novel clade of HTNV sequences recovered from HFRS cases were closely related to those from rodents, including species close contact with humans, suggesting a direct viral transmission from rodents to humans and the important role in the HTNV transmission the nontraditional rodent hosts may play. Moreover, two distant related Dabieshan orthohantavirus (DBSV) lineages were also identified in Niviventer niviventer in this area demonstrating its considerable genetic diversity. Our data indicated that continual spillover of HTNV from rodents to humans, contributing to the high prevalence of HFRS in humans in Baoji., Competing Interests: The authors have declared that no competing interests exist.

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease of natural infectious focus caused by Hantavirus (HV) with clinical characteristics as fever, hemorrhage, hyperemia, hypotensive shock and renal damage. Through contacting the excreta or secretion of infected rats, human may get infected. The epidemiological characteristics of HFRS are significantly different in terms of population differences, geographical heterogeneity and seasonal variation, which are all closely related to the habitat of host animals and human productive activities. The reported number of HFRS is about 150 000 to 200 000 each year worldwide, and China accounted for 70 % -90 % of the total reported cases standing the most seriously infected country. In this study, we reviewed the epidemiological characteristics and the influencing factors of HFRS as well as the models and methods used in relevant ecological studies, in order to understand the distribution of time, regional and population and potential influencing factors on the transmission of HFRS better, so as to improve the strategies on investigation, monitoring, prevention and control of the diseases.

Haemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a major public health concern in both developed and developing countries. China is the most severe endemic country in the world, constituting 90% of the cases. Although the incidence of HFRS has substantively decreased in most areas of China, HFRS has rebounded remarkably in some epidemic areas. Xuancheng is one of these areas. In this study, we collected the case data reported recently in Xuancheng and designed a 1:3 case-control study. The Chi-square test, univariate and multivariate logistic regression analysis were performed. In all cases, farmers made up the highest proportion of occupations. And there were 20 variables with statistical significance including indoor hygienic conditions; the surrounding environment; whether bitten by rats at work and other criteria. In addition, exposure to rodents and rats bites is a high-risk factor for HFRS. Rodent density was calculated at 20.9% (159/760), the virus carrier rate was 9.4% (15/159) and the index of rats with a virus was about 2.0%. Exposure to rodents and insect bites is also high-risk factors for HFRS among local residents in Xuancheng. More importantly, during the flood years, the increased density of rodents led to an increased risk of human exposure to rodents. As our statistical analysis proves, targeted strategies should be developed and implemented to reduce the incidence of local diseases in the future.

Background: In Europe, hantaviruses cause serious human disease, hemorrhagic fever with renal syndrome (HFRS). The geographic distribution of human cases of HFRS is a consequence of distribution of reservoir host species. Epidemiology of HFRS is well-studied in Western Europe, while data from Central and Eastern Europe are poor or unavailable., Methods: The data on hantavirus infections in humans during 2007-2017 were gathered to distinguish pattern of HFRS occurrence and characterize potential factors shaping HFRS epidemiology in Poland., Results: The south-eastern part of Poland (Podkarpackie voivodeship) was recognized as endemic area of hantavirus prevalence. Incidence rate of HFRS in Poland was positively correlated with mast years and higher abundance of rodents, urbanization index, and forest cover, while the climatic factors (average temperatures in January and July and average annual precipitation) have had no significant impact., Conclusions: In Poland, HFRS is still not recognized entity. Further studies on hantavirus infection rate in reservoir host species (rodents, shrews, and bats) and virus transmission to humans are needed to prevent outbreaks of HFRS in the future., (© The Author(s) 2019. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.)

Hantaviruses cause hemorrhagic fever in humans worldwide. However, few hantavirus surveillance campaigns occur in Africa. We detected Seoul orthohantavirus in black rats in Senegal, although we did not find serologic evidence of this disease in humans. These findings highlight the need for increased surveillance of hantaviruses in this region.

Background: The early warning model of infectious diseases plays a key role in prevention and control. This study aims to using seasonal autoregressive fractionally integrated moving average (SARFIMA) model to predict the incidence of hemorrhagic fever with renal syndrome (HFRS) and comparing with seasonal autoregressive integrated moving average (SARIMA) model to evaluate its prediction effect., Methods: Data on notified HFRS cases in Weifang city, Shandong Province were collected from the official website and Shandong Center for Disease Control and Prevention between January 1, 2005 and December 31, 2018. The SARFIMA model considering both the short memory and long memory was performed to fit and predict the HFRS series. Besides, we compared accuracy of fit and prediction between SARFIMA and SARIMA which was used widely in infectious diseases., Results: Model assessments indicated that the SARFIMA model has better goodness of fit (SARFIMA (1, 0.11, 2)(1, 0, 1) 12 : Akaike information criterion (AIC):-631.31; SARIMA (1, 0, 2)(1, 1, 1) 12 : AIC: - 227.32) and better predictive ability than the SARIMA model (SARFIMA: root mean square error (RMSE):0.058; SARIMA: RMSE: 0.090)., Conclusions: The SARFIMA model produces superior forecast performance than the SARIMA model for HFRS. Hence, the SARFIMA model may help to improve the forecast of monthly HFRS incidence based on a long-range dataset.

Background: During 2017, a multistate outbreak investigation occurred after the confirmation of Seoul virus (SEOV) infections in people and pet rats. A total of 147 humans and 897 rats were tested., Methods: In addition to immunoglobulin (Ig)G and IgM serology and traditional reverse-transcription polymerase chain reaction (RT-PCR), novel quantitative RT-PCR primers/probe were developed, and whole genome sequencing was performed., Results: Seventeen people had SEOV IgM, indicating recent infection; 7 reported symptoms and 3 were hospitalized. All patients recovered. Thirty-one facilities in 11 US states had SEOV infection, and among those with ≥10 rats tested, rat IgG prevalence ranged 2%-70% and SEOV RT-PCR positivity ranged 0%-70%. Human laboratory-confirmed cases were significantly associated with rat IgG positivity and RT-PCR positivity (P = .03 and P = .006, respectively). Genomic sequencing identified >99.5% homology between SEOV sequences in this outbreak, and these were >99% identical to SEOV associated with previous pet rat infections in England, the Netherlands, and France. Frequent trade of rats between home-based ratteries contributed to transmission of SEOV between facilities., Conclusions: Pet rat owners, breeders, and the healthcare and public health community should be aware and take steps to prevent SEOV transmission in pet rats and to humans. Biosecurity measures and diagnostic testing can prevent further infections., (Published by Oxford University Press for the Infectious Diseases Society of America 2020.)

Historically, Jiangxi province has had the largest HFRS burden in China. However, thus far, the comprehensive understanding of the spatiotemporal distributions of HFRS is limited in Jiangxi. In this study, seasonal decomposition analysis, spatial autocorrelation analysis, and space-time scan statistic analyses were performed to detect the spatiotemporal dynamics distribution of HFRS cases from 2005 to 2018 in Jiangxi at the county scale. The epidemic of HFRS showed the characteristic of bi-peak seasonality, the primary peak in winter (November to January) and the second peak in early summer (May to June), and the amplitude and the magnitude of HFRS outbreaks have been increasing. The results of global and local spatial autocorrelation analysis showed that the HFRS epidemic exhibited the characteristic of highly spatially heterogeneous, and Anyi, Fengxin, Yifeng, Shanggao, Jing'an and Gao'an county were hot spots areas. A most likely cluster, and two secondary likely clusters were detected in 14-years duration. The higher risk areas of the HFRS outbreak were mainly located in Jiangxi northern hilly state, spreading to Wuyi mountain hilly state as time advanced. This study provided valuable information for local public health authorities to design and implement effective measures for the control and prevention of HFRS.

Background: Hemorrhagic fever with renal syndrome (HFRS) is an illness caused by hantaviruses. Numerous factors modify the risk of hantavirus transmission. This study explored the epidemiological characteristics, differences, and trends in terms of gender, age, season, and living areas of those diagnosed with domestically acquired HFRS in Taiwan from 2001 to 2019., Methods: We examined publicly available annual summary data on the domestic cases with HFRS from 2001 to 2019; these data were obtained from the web database of Taiwan's Centers for Disease Control (CDC)., Results: This study analyzed 21 domestic cases with HFRS from Taiwan's CDC databases. In this study of the cases of HFRS in Taiwan, a gradual increase in the cases of those aged ≥40 years acquiring the disease was noted, and a distinct pattern of seasonal variation (spring) was observed. Furthermore, more men had domestically acquired HFRS, and living in Taipei metropolitan area (6 cases [28.6%]) and the rural areas (Gao-Ping region, 9 cases [42.9%]) was identified as a potential risk factor. This study represents the first report of confirmed cases of domestically acquired HFRS from surveillance data from Taiwan's CDC, 2001-2019., Conclusion: This study highlights the importance of longitudinal studies covering a wide geographical area, particularly for highly fluctuating pathogens, to understanding the implications of the transmission of zoonotic diseases in human populations. Important data were identified to inform future surveillance and research efforts in Taiwan.

Hemorrhagic fever with renal syndrome (HFRS) is seriously endemic in China with 70%~90% of the notified cases worldwide and showing an epidemic tendency of upturn in recent years. Early detection for its future epidemic trends plays a pivotal role in combating this threat. In this scenario, our study investigates the suitability for application in analyzing and forecasting the epidemic tendencies based on the monthly HFRS morbidity data from 2005 through 2019 using the nonlinear model-based self-exciting threshold autoregressive (SETAR) and logistic smooth transition autoregressive (LSTAR) methods. The experimental results manifested that the SETAR and LSTAR approaches presented smaller values among the performance measures in both two forecasting subsamples, when compared with the most extensively used seasonal autoregressive integrated moving average (SARIMA) method, and the former slightly outperformed the latter. Descriptive statistics showed an epidemic tendency of downturn with average annual percent change (AAPC) of -5.640% in overall HFRS, however, an upward trend with an AAPC = 1.213% was observed since 2016 and according to the forecasts using the SETAR, it would seemingly experience an outbreak of HFRS in China in December 2019. Remarkably, there were dual-peak patterns in HFRS incidence with a strong one occurring in November until January of the following year, additionally, a weak one in May and June annually. Therefore, the SETAR and LSTAR approaches may be a potential useful tool in analyzing the temporal behaviors of HFRS in China.

Background: Endemic outbreaks of hantaviruses pose a critical public health threat worldwide. Hantaan orthohantavirus (HTNV) causes hemorrhagic fever with renal syndrome (HFRS) in humans. Using comparative genomic analyses of partial and nearly complete sequences of HTNV from humans and rodents, we were able to localize, with limitations, the putative infection locations for HFRS patients. Partial sequences might not reflect precise phylogenetic positions over the whole-genome sequences; finer granularity of rodent sampling reflects more precisely the circulation of strains., Methods: Five HFRS specimens were collected. Epidemiological surveys were conducted with the patients during hospitalization. We conducted active surveillance at suspected HFRS outbreak areas. We performed multiplex polymerase chain reaction-based next-generation sequencing to obtain the genomic sequence of HTNV from patients and rodents. The phylogeny of human- and rodent-derived HTNV was generated using the maximum likelihood method. For phylogeographic analyses, the tracing of HTNV genomes from HFRS patients was defined on the bases of epidemiological interviews, phylogenetic patterns of the viruses, and geographic locations of HTNV-positive rodents., Results: The phylogeographic analyses demonstrated genetic clusters of HTNV strains from clinical specimens, with HTNV circulating in rodents at suspected sites of patient infections., Conclusions: This study demonstrates a major shift in molecular epidemiological surveillance of HTNV. Active targeted surveillance was performed at sites of suspected infections, allowing the high-resolution phylogeographic analysis to reveal the site of emergence of HTNV. We posit that this novel approach will make it possible to identify infectious sources, perform disease risk assessment, and implement preparedness against vector-borne viruses., (© The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Seoul virus (SEOV), which causes hemorrhagic fever with renal syndrome (HFRS) in humans, has spread all over the world, especially in mainland China. Understanding basic mechanisms of SEOV evolution is essential to better combat and prevent viral diseases. Here, we examined SEOV prevalence and evolution in the residential area of four districts in Guangzhou city, China. The carriage of SEOV was observed in 33.33% of the sampled rodents, with 35.96% of the sampled Rattus norvegicus and 13.33% of R. tanezumi . Based on the comprehensive analyses of large (L), medium (M), and small (S) segments, our study first demonstrated that the genetic characterization of urban SEOV was shaped by high nucleotide substitution rates, purifying selection, and recombination. Additionally, we detected mutational saturation in the S segment of SEOV, which may lead to the biases of genetic divergence and substitution rates in our study. Importantly, we have filled the gap of SEOV evolution in the urban area. The genetic variation of SEOV may highlight the risk of HFRS, which merits further investigation.

Background: Some of the hantavirus species in Euro-Asia cause haemorrhagic fever with renal syndrome (HFRS) in humans. The first documented human hantavirus infection in Turkey was diagnosed in 2009. This report describes the dynamics of the first hantavirus outbreak that emerged in humans in the Western Black Sea Region of Turkey., Methods: All the suspected cases of hantavirus infection were admitted to the Infectious Diseases and Clinical Microbiology Department at the Zonguldak Bülent Ecevit University Hospital in Zonguldak, Turkey. The patients were carefully interviewed, examined and evaluated using routine laboratory tests and hantavirus diagnostic tools. Hantavirus-reactive antibodies (IgM and IgG) in serum samples were detected via enzyme immune assay (EIA) and immunofluorescence assay (IFA) in the acute and convalescence stages of the disease. The presence of hantavirus ribonucleic acid (RNA) was analysed via reverse transcription polymerase chain reaction (RT-PCR) in serum and urine samples. A focus reduction neutralization test (FRNT) was performed to confirm specific hantavirus serotypes. In addition, a case-control study was conducted to identify possible risk factors for hantavirus transmission in the outbreak area. A control group was composed of asymptomatic individuals who were seronegative for hantavirus IgM and IgG and living in the outbreak area., Results: A total of 55 suspected cases of hantavirus infection were admitted to the inpatient clinic between February and June of 2009. Twenty-four patients were diagnosed with acute HFRS via EIA or IFA. In 22 of the 24 infected patients, Puumala virus (PUUV) was identified as the causative hantavirus type by detecting IgM in the acute stage and an increase in the IgG level in follow-up serum samples. PUUV was also verified as the infecting agent by FRNT in two of the 24 cases. Among the 24 laboratory-confirmed HFRS cases, 21 (87.5%) were males and 3 (12.5%) were females, and the mean age was 45.92 years (standard deviation ± 16.90 years). Almost all these individuals were living in villages or rural areas. The 24 HFRS cases were matched with 26 healthy controls for statistical analyses and according to binary logistic regression analysis, and dealing with rodent control activities in gardens or in annexes of their homes (p = 0.021 and Odds ratio [OR] = 17.11) and being male (p = 0.019 and OR = 22.37) were detected as statistically significant risk factors for hantavirus infection. The most commonly observed clinical complaints were fatigue (95.8%), shivering (91.7%), fever (87.1%), headache (70.8%) and nausea (70.8%). Haemodialysis was required for four patients (16.7%). Except for the first case diagnosed with acute hantavirus infection, no patient died. The mean delay time to hospital admission from initiation of symptoms was 5.3 days, the mean duration of febrile days was 2.6 days, and the mean duration of hospital stay was 8.5 days., Conclusion: Hantaviruses are circulating in Turkey and causing sporadic or epidemic infection in humans. Additional investigations are needed to better understand the dynamics of hantaviruses in this country., (© 2019 Blackwell Verlag GmbH.)

Shandong Province is an area of China with a high incidence of haemorrhagic fever with renal syndrome (HFRS); however, the general epidemic trend of HFRS in Shandong remains unclear. Therefore, we established a mathematical model to predict the incidence trend of HFRS and used Joinpoint regression analysis, a generalised additive model (GAM), and other methods to evaluate the data. Incidence data from the first half of 2018 were included in a range predicted by a modified sum autoregressive integrated moving average-support vector machine (ARIMA-SVM) combination model. The highest incidence of HFRS occurred in October and November, and the annual mortality rate decreased by 7.3% (p < 0.05) from 2004 to 2017. In cold months, the incidence of HFRS increased by 4%, -1%, and 0.8% for every unit increase in temperature, relative humidity, and rainfall, respectively; in warm months, this incidence changed by 2%, -3%, and 0% respectively. Overall, HFRS incidence and mortality in Shandong showed a downward trend over the past 10 years. In both cold and warm months, the effects of temperature, relative humidity, and rainfall on HFRS incidence varied. A modified ARIMA-SVM combination model could effectively predict the occurrence of HFRS.

Seoul hantavirus (SEOV) has recently raised concern by causing geographic range expansion of hemorrhagic fever with renal syndrome (HFRS). SEOV infections in humans are significantly underestimated worldwide and epidemic dynamics of SEOV-related HFRS are poorly understood because of a lack of field data and empirically validated models. Here, we use mathematical models to examine both intrinsic and extrinsic drivers of disease transmission from animal (the Norway rat) to humans in a SEOV-endemic area in China. We found that rat eradication schemes and vaccination campaigns, but below the local elimination threshold, could diminish the amplitude of the HFRS epidemic but did not modify its seasonality. Models demonstrate population dynamics of the rodent host were insensitive to climate variations in urban settings, while relative humidity had a negative effect on the seasonality in transmission. Our study contributes to a better understanding of the epidemiology of SEOV-related HFRS, demonstrates asynchronies between rodent population dynamics and transmission rate, and identifies potential drivers of the SEOV seasonality., Competing Interests: The authors have declared that no competing interests exist.

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne infectious disease caused by hantaviruses. About 90% of global cases were reported in China. We collected monthly data on counts of HFRS cases, climatic factors (mean temperature, rainfall, and relative humidity), and vegetation (normalized difference vegetation index (NDVI)) in 109 Chinese counties from January 2002 to December 2013. First, we used a quasi-Poisson regression with a distributed lag non-linear model to assess the impacts of these four factors on HFRS in 109 counties, separately. Then we conducted a multivariate meta-analysis to pool the results at the national level. The results of our study showed that there were non-linear associations between the four factors and HFRS. Specifically, the highest risks of HFRS occurred at the 45th, 30th, 20th, and 80th percentiles (with mean and standard deviations of 10.58 ± 4.52 °C, 18.81 ± 17.82 mm, 58.61 ± 6.33%, 198.20 ± 22.23 at the 109 counties, respectively) of mean temperature, rainfall, relative humidity, and NDVI, respectively. HFRS case estimates were most sensitive to mean temperature amongst the four factors, and the lag patterns of the impacts of these factors on HFRS were heterogeneous. Our findings provide rigorous scientific support to current HFRS monitoring and the development of early warning systems.

Background: Hemorrhagic fever with renal syndrome (HFRS) is an emerging zoonotic infectious disease caused by hantaviruses which circulate worldwide. So far, it was still considered as one of serious public health problems in China. The present study aimed to reveal the stabilities and variations of hantavirus infection in Hebei province located in North China through a long-term retrospective observation., Methods: The epidemiological data of HFRS cases from all 11 cities of Hebei province since 1981 through 2016 were collected and descriptively analyzed. The rodent densities, species compositions and virus-carrying rates of different regions were collected from six separated rodent surveillance points which set up since 2007. The molecular diversity and phylogenetic relationship of hantaviruses circulating among rodents were analyzed based on partial viral glycoprotein gene., Results: HFRS cases have been reported every year in Hebei province, since the first local case was identified in 1981. The epidemic history can be artificially divided into three phases and a total of 55,507 HFRS cases with 374 deaths were reported during 1981-2016. The gender and occupational factors of susceptible population were invarible throughout, however age of that was gradually aging. The annual outbreak peak always present in spring, while the main epidemic region had gradully altered from south to northeast. Surveillance of rodents revealed that residential rodents significantly possessed higher density and virus-carring rate than field rodents. The house rat, Rattus norvegicus, was the dominant rodent species and Seoul virus S3 sub-genotype which is continued but slightly evolving perhaps to be the sole pathogen for local HFRS cases of Hebei province., Conclusions: This long-term province-wide surveillance and epidemiological analysis has revealed the stabilities and variations of hantavirus infection in North China. In order to improve current prevention and control strategies of HFRS in China, all surveillance should be continuously enhanced and variations should be paid more attentions.

Predicting risk of zoonotic diseases, i.e., diseases shared by humans and animals, is often complicated by the population ecology of wildlife host(s). We here demonstrate how ecological knowledge of a disease system can be used for early prediction of human risk using Puumala hantavirus (PUUV) in bank voles (Myodes glareolus), which causes Nephropathia epidemica (NE) in humans, as a model system. Bank vole populations at northern latitudes exhibit multiannual fluctuations in density and spatial distribution, a phenomenon that has been studied extensively. Nevertheless, existing studies predict NE incidence only a few months before an outbreak. We used a time series on cyclic bank vole population density (1972-2013), their PUUV infection rates (1979-1986; 2003-2013), and NE incidence in Sweden (1990-2013). Depending on the relationship between vole density and infection prevalence (proportion of infected animals), either overall density of bank voles or the density of infected bank voles may be used to predict seasonal NE incidence. The density and spatial distribution of voles at density minima of a population cycle contribute to the early warning of NE risk later at its cyclic peak. When bank voles remain relatively widespread in the landscape during cyclic minima, PUUV can spread from a high baseline during a cycle, culminating in high prevalence in bank voles and potentially high NE risk during peak densities.

Background: Changes in climate and environmental conditions could be the driving factors for the transmission of hantavirus. Thus, a thorough collection and analysis of data related to the epidemic status of hemorrhagic fever with renal syndrome (HFRS) and the association between HFRS incidence and meteorological factors, such as air temperature, is necessary for the disease control and prevention., Methods: Journal articles and theses in both English and Chinese from Jan 2014 to Feb 2019 were identified from PubMed, Web of Science, Chinese National Knowledge Infrastructure, Wanfang Data and VIP Info. All identified studies were subject to the six criteria established to ensure the consistency with research objectives, (i) they provided the data of the incidence of HFRS in mainland China; (ii) they provided the type of air temperature indexes; (iii) they indicated the underlying geographical scale information, temporal data aggregation unit, and the data sources; (iv) they provided the statistical analysis method that had been used; (v) from peer-reviewed journals or dissertation; (vi) the time range for the inclusion of data exceeded two consecutive calendar years., Results: A total of 27 publications were included in the systematic review, among them, the correlation between HFRS activity and air temperature was explored in 12 provinces and autonomous regions and also at national level. The study period ranged from 3 years to 54 years with a median of 10 years, 70.4% of the studies were based on the monthly HFRS incidence data, 21 studies considered the lagged effect of air temperature factors on the HFRS activity and the longest lag period considered in the included studies was 34 weeks. The correlation between HFRS activity and air temperature varied widely, and the effect of temperature on the HFRS epidemic was seasonal., Conclusions: The present systematic review described the heterogeneity of geographical scale, data aggregation unit and study period chosen in the ecological studies that seeking the correlation between air temperature indexes and the incidence of HFRS in mainland China during the period from January 2014 to February 2019. The appropriate adoption of geographical scale, data aggregation unit, the length of lag period and the length of incidence collection period should be considered when exploring the relationship between HFRS incidence and meteorological factors such as air temperature. Further investigation is warranted to detect the thresholds of meteorological factors for the HFRS early warning purposes, to measure the duration of lagged effects and determine the timing of maximum effects for reducing the effects of meteorological factors on HFRS via continuous interventions and to identify the vulnerable populations for target protection., Competing Interests: The authors have declared that no competing interests exist.

Objective: To analyze the epidemiological and spatial-temporal distribution of Brucellosis, epidemic encephalitis B and hemorrhagic fever with renal syndrome (HFRS) in Gansu province during 2014-2018 so as to provide evidence for the prevention and control of those diseases. Methods: A database was established in Gansu province from 2014 to 2018, using the geographical information system. A spatial distribution map was drawn, with trend analysis and space-time clustering used to study the 3-dimention of the diseases, by using both ArcGIS 10.5 and SaTScan 9.6 softwares. Results: Results from the trend surface analysis showed that the incidence of Brucellosis decreased gradually from north to south parts while the U type curve could reflect the distribution from the east to the west areas. Incidence of epidemic encephalitis B decreased significantly from south to north areas in the province, with incidence higher in the eastern than in the mid-west region. Difference on the incidence of HFRS was not significantly visible in the eastern and western regions, while the incidence was slightly higher in the southern than the northern parts of the province. Spatial and space-time clustering did exist among the 3 diseases in Gansu from 2014 to 2018. The areas with clusters of Brucellosis appeared in the eastern parts during 2014-2015, including 19 counties. The areas with secondary clusters of Brucellosis were seen in the Hexi district, including 4 counties, during 2017-2018. The areas with high incidence of epidemic encephalitis B were clustered in the middle and southeast areas, including 32 counties, during 2017-2018. Areas with most clusters of HFRS appeared in Min county of Dingxi city in 2018, with the areas of secondary clusters in 8 counties of the eastern areas in 2018. Conclusions: The overall incidence rates of the 3 natural focus diseases were in a upward trend and showing obvious characteristics on spatial clustering. According to the distributive characteristics, effective measures should be developed accordingly.

Objective: To explore the spatial-temporal distribution and epidemic characteristics of hemorrhagic fever with renal syndrome (HFRS) in Hebei province from 2005 to 2016. Methods: Records of HFRS cases reported from each county in Hebei during January 2005 to December 2016 were collected from National Notifiable Disease Surveillance System (NNDSS). Global and local spatial association statistics were used to measure the spatial autocorrelation and software GeoDa 1.2.0. Software SaTScan 9.4.1 was used to analyze spatiotemporal clusters. Software ArcGIS 10.2 was used to visualize the yearly scan results. Results: In Hebei province, a total of 8 437 human HFRS cases reported from 170 counties with an annual incidence rate of 0.99/100 000 population during 2005-2016. The peak incidence season was spring. Global spatial autocorrelation analysis on the incidence of HFRS at county-level showed that the value of Moran's I were all above 0 ( P <0.05), indicating that the significant spatial cluster. The result of local indicators on spatial association (LISA) analysis revealed that identified hot spots were mainly in northeastern area, while cold spots were found in some counties of central and southern areas. Spatial-temporal scan detected that the primary cluster of HFRS incidence was mainly distributed in Qinhuangdao city and Tangshan city, including 11 counties (city/district): Beidaihe district, Haigang district, Funing district, Shanhaiguan district, Changli county, Lulong county and Qinglong Manchu autonomous county in Qinhuangdao city, and Qian'an city, Laoting county, Luanzhou city and Luannan county in Tangshan city ( RR =39.64, P <0.001), during January-July in 2005. Conclusions: There were significant spatial-temporal cluster of HFRS in Hebei from 2005 to 2016. The cluster areas of HFRS were mainly in northeastern Hebei, it is necessary to strengthen the prevention and control programs of HFRS in these areas.

IntroductionTwo hantavirus species, Puumala (PUUV) and Dobrava-Belgrade (DOBV) virus (genotype Kurkino), are endemic in Germany. Recent PUUV outbreaks raised questions concerning increasing frequency of outbreaks and expansion of PUUV endemic areas.AimsTo describe the epidemiology of human PUUV and DOBV infections in Germany.MethodsWe conducted an observational retrospective study analysing national hantavirus surveillance data notified to the national public health institute and hantavirus nucleotide sequences from patients collected at the national consultation laboratory between 2001 and 2017. Matching molecular sequences with surveillance data, we conducted epidemiological, phylogenetic and phylogeographic analyses.ResultsIn total, 12,148 cases of symptomatic hantavirus infection were notified 2001-17 (mean annual incidence: 0.87/100,000; range: 0.09-3.51). PUUV infections showed a highly variable space-time disease incidence pattern, causing large outbreaks every 2-3 years with peaks in early summer and up to 3,000 annually reported cases. Sex-specific differences in disease presentation were observed. Of 202 PUUV nucleotide sequences obtained from cases, 189 (93.6%) fall into well-supported phylogenetic clusters corresponding to different endemic areas in Germany. DOBV infections caused few, mostly sporadic cases in autumn and winter in the north and east of Germany.ConclusionsThe frequency of PUUV outbreaks increased between 2001 and 2017 but our data does not support the suggested expansion of endemic areas. The epidemiology of PUUV and DOBV-Kurkino infections differs in several aspects. Moreover, the latter are relatively rare and combining efforts and data of several countries to identify risk factors and develop specific recommendations for prevention could be worthwhile.

Puumala virus (PUUV) is the most common cause of hantavirus infection in Europe, with thousands of cases occurring particularly in Northern, Central and Eastern Europe and Russia. It causes a mild form of hemorrhagic fever with renal syndrome also known as nephropathia epidemica (NE) with clinical picture ranging from mild to severe. Currently, the laboratory diagnosis of NE is mainly based on serology. Here, we evaluated a real-time one-step qRT-PCR (PUUV-qRT-PCR) for detection of PUUV with 238 consecutive diagnostic serum samples from patients with suspected PUUV infection. The PUUV-qRT-PCR was both specific and sensitive for PUUV RNA. The analytical sensitivity (limit of detection) was estimated to be four copies of PUUV per reaction. Altogether 28 out of 30 (93%) PUUV IgM positive samples were positive also for PUUV RNA. No false positives were detected and the specificity was thus 100%. Interestingly, one sample was found positive in PUUV-qRT-PCR prior to subsequent IgM and IgG seroconversion. PUUV-qRT-PCR could be used for diagnostics in the early phase of NE infection and might be helpful especially in the rare severe cases when the patient's condition may deteriorate rapidly.

Recent reports from Europe and the USA described Seoul orthohantavirus infection in pet rats and their breeders/owners, suggesting the potential emergence of a "new" public health problem. Wild and laboratory rat-induced Seoul infections have, however, been described since the early eighties, due to the omnipresence of the rodent reservoir, the brown rat Rattus norvegicus . Recent studies showed no fundamental differences between the pathogenicity and phylogeny of pet rat-induced Seoul orthohantaviruses and their formerly described wild or laboratory rat counterparts. The paucity of diagnosed Seoul virus-induced disease in the West is in striking contrast to the thousands of cases recorded since the 1980s in the Far East, particularly in China. This review of four continents (Asia, Europe, America, and Africa) puts this "emerging infection" into a historical perspective, concluding there is an urgent need for greater medical awareness of Seoul virus-induced human pathology in many parts of the world Given the mostly milder and atypical clinical presentation, sometimes even with preserved normal kidney function, the importance of simple but repeated urine examination is stressed, since initial but transient proteinuria and microhematuria are rarely lacking.

Objectives: Haemorrhagic fever with renal syndrome (HFRS) is a serious threat to public health in China, accounting for almost 90% cases reported globally. Infectious disease prediction may help in disease prevention despite some uncontrollable influence factors. This study conducted a comparison between a hybrid model and two single models in forecasting the monthly incidence of HFRS in China., Design: Time-series study., Setting: The People's Republic of China., Methods: Autoregressive integrated moving average (ARIMA) model, generalised regression neural network (GRNN) model and hybrid ARIMA-GRNN model were constructed by R V.3.4.3 software. The monthly reported incidence of HFRS from January 2011 to May 2018 were adopted to evaluate models' performance. Root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were adopted to evaluate these models' effectiveness. Spatial stratified heterogeneity of the time series was tested by month and another GRNN model was built with a new series., Results: The monthly incidence of HFRS in the past several years showed a slight downtrend and obvious seasonal variation. A total of four plausible ARIMA models were built and ARIMA(2,1,1) (2,1,1) 12 model was selected as the optimal model in HFRS fitting. The smooth factors of the basic GRNN model and the hybrid model were 0.027 and 0.043, respectively. The single ARIMA model was the best in fitting part (MAPE=9.1154, MAE=89.0302, RMSE=138.8356) while the hybrid model was the best in prediction (MAPE=17.8335, MAE=152.3013, RMSE=196.4682). GRNN model was revised by building model with new series and the forecasting performance of revised model (MAPE=17.6095, MAE=163.8000, RMSE=169.4751) was better than original GRNN model (MAPE=19.2029, MAE=177.0356, RMSE=202.1684)., Conclusions: The hybrid ARIMA-GRNN model was better than single ARIMA and basic GRNN model in forecasting monthly incidence of HFRS in China. It could be considered as a decision-making tool in HFRS prevention and control., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

In Bulgaria, only Dobrava orthohantavirus has been detected in patients and in rodents. In order to elucidate possible Puumala orthohantavirus (PUUV) circulation, 131 bank voles (Myodes glareolus) were captured. PUUV RNA was detected in 14 (10.7%). Partial L segment sequences were recovered from six M. glareolus. Phylogenetic analysis showed that all PUUV sequences from this study clustered together among the Alpe-Adrian lineage. It is the first genetic evidence of the virus circulation in a Balkan country outside north-western Balkans. The findings in this study extended the known edge of virus distribution towards Southeastern Europe., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Hemorrhagic fever with renal syndrome (HFRS), an infectious disease caused by hantaviruses, is endemic in China and remains a serious public health problem. Historically, Shandong Province has had the largest HFRS burden in China. However, we do not have a comprehensive and clear understanding of the current epidemic foci of HFRS in Shandong Province., Methodology/principal Findings: The incidence and mortality rates were calculated, and a phylogenetic analysis was performed after laboratory testing of the virus in rodents. Spatial epidemiology analysis was applied to investigate the epidemic foci, including their sources. A total of 6,206 HFRS cases and 59 related deaths were reported in Shandong Province. The virus carriage rates of the rodents Rattus norvegicus, Apodemus agrarius and Mus musculus were 10.24%, 6.31% and 0.27%, respectively. The phylogenetic analysis indicated that two novel viruses obtained from R. norvegicus in Anqiu City and Qingzhou City were dissimilar to the other strains, but closely related to strains previously isolated in northeastern China. Three epidemic foci were defined, two of which were derived from the Jining and Linyi epidemic foci, respectively, while the other was the residue of the Jining epidemic focus., Conclusions/significance: The southeastern and central Shandong Province are current key HFRS epidemic foci dominated by A. agrarius and R. norvegicus, respectively. Our study could help local departments to strengthen prevention and control measures in key areas to reduce the hazards of HFRS., Competing Interests: The authors have declared that no competing interests exist.

Introduction: Hantaviruses are maintained by mammalian hosts, such as rodents, and are shed in their excretions. Clinical disease can occur in humans from spillover infection. Brown rats ( Rattus norvegicus) are the globally distributed reservoir host of Seoul virus (SEOV). Human cases of SEOV-associated haemorrhagic fever with renal syndrome (SEOV-HFRS)have been reported in Great Britain (GB) since 1977., Methods: Brown rats (n=68) were trapped from a variety of peridomestic locations, with a focus on pig farms. Kidney and lung tissues were tested for viral RNA using a pan-hantavirus RT-PCR assay followed by Sanger sequencing and analysis., Results: SEOV RNA was detected in 19 per cent (13/68, 95% CI 11 to 30) of rats and all sequences fell within SEOV lineage 9. Twelve sequences were highly similar to each other and to the previously reported GB Humber strain of SEOV (98 per cent). One rat SEOV sequence was more distant. The SEOV prevalence in rats from pig farms was significantly greater (p=0.047) than other sites sampled. No significant sex or age differences were observed among positive and negative rats., Discussion: The results from this study suggest that SEOV could be widespread in wild rats in GB and therefore pose a potential risk to public health., Competing Interests: Competing interests: None declared., (© British Veterinary Association 2019. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ.)

Many pathogens causing hemorrhagic fevers of medical and veterinary importance have been identified and isolated from rodents in the Republic of Korea (ROK). We investigated the occurrence of emerging viruses causing hemorrhagic fevers, such as hemorrhagic fever with renal syndrome (HFRS), severe fever with thrombocytopenia syndrome (SFTS), and flaviviruses, from wild rodents. Striped field mice, Apodemus agrarius (n = 39), were captured during 2014-2015 in the south-west of ROK. Using molecular methods, lung samples were evaluated for SFTS virus, hantavirus, and flavivirus, and seropositivity was evaluated in the blood. A high positive rate of hantavirus (46.2%) was detected in A. agrarius lungs by reverse transcription-nested polymerase chain reaction (RT-N-PCR). The monthly occurrence of hantavirus was 16.7% in October, 86.7% in November, and 25% in August of the following year (p < 0.001). Moreover, 17.9% of blood samples were serologically positive for hantavirus antibodies. The most prevalent strain in A. agrarius was Hantaan virus. All samples were positive for neither SFTS virus nor flavivirus. Hantaan virus was detected in 86.7% of A. agrarius in November (autumn), and thus, virus shedding from A. agrarius can increase the risk of humans contracting HFRS. These findings may help to predict and prevent disease outbreaks in ROK.

Over the past few decades understanding and recognition of hantavirus infection has greatly improved worldwide, but both the amplitude and the magnitude of hantavirus outbreaks have been increasing. Several novel hantaviruses with unknown pathogenic potential have been identified in a variety of insectivore hosts. With the new hosts, new geographical distributions of hantaviruses have also been discovered and several new species were found in Africa. Hantavirus infection in humans can result in two clinical syndromes: haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS) caused by Old World and New World hantaviruses, respectively. The clinical presentation of HFRS varies from subclinical, mild, and moderate to severe, depending in part on the causative agent of the disease. In general, HFRS caused by Hantaan virus, Amur virus and Dobrava virus are more severe with mortality rates from 5 to 15%, whereas Seoul virus causes moderate and Puumala virus and Saaremaa virus cause mild forms of disease with mortality rates <1%. The central phenomena behind the pathogenesis of both HFRS and HCPS are increased vascular permeability and acute thrombocytopenia. The pathogenesis is likely to be a complex multifactorial process that includes contributions from immune responses, platelet dysfunction and the deregulation of endothelial cell barrier functions. Also a genetic predisposition, related to HLA type, seems to be important for the severity of the disease. As there is no effective treatment or vaccine approved for use in the USA and Europe, public awareness and precautionary measures are the only ways to minimize the risk of hantavirus disease., (Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.)

We report 17 patients with human granulocytic anaplasmosis between January 2015 and September 2018 at two tertiary university hospitals in Korea. Monthly incidence peaked in May and June. Among these patients, we identified three who were co-infected with scrub typhus, and one patient with hemorrhagic fever with renal syndrome., Competing Interests: Disclosure: The authors have no potential conflicts of interest to disclose.

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantaviruses (HVs). Climate factors have a significant impact on the transmission of HFRS. Here, we characterized the dynamic temporal trend of HFRS and identified the roles of climate factors in its transmission in Changchun, China.Surveillance data of HFRS cases and data on related environmental variables from 2013 to 2017 were collected. A principal components regression (PCR) model was used to quantify the relationship between climate factors and transmission of HFRS.During 2013 to 2017, a distinctly declining temporal trend of annual HFRS incidence was identified. Four principal components were extracted, with a cumulative contribution rate of 89.282%. The association between HFRS epidemics and climate factors was better explained by the PCR model (F = 10.050, P <.001, adjusted R = 0.456) than by the general multiple regression model (F = 2.748, P <.005, adjusted R = 0.397).The monthly trends of HFRS were positively correlated with the mean wind velocity but negatively correlated with the mean temperature, relative humidity, sunshine duration, and accumulative precipitation of the different previous months. The study results may be useful for the development of HFRS preventive initiatives that are customized for Changchun regarding specific climate environments.

Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in China, where approximately 90% of the total human cases in the world are reported. The Hebei province, one of areas with the highest prevalence, has reported HFRS cases every year in the last two decades. This study describes the spatiotemporal patterns of HFRS in the Hebei province from 2001 to 2016, detects the high-risk spatiotemporal clusters of HFRS, and provides valuable information for planning and implementation of local preventive measures. For the purpose of the analysis, HFRS cases recorded during the sixteen years in the Hebei province were aggregated into three temporal periods (2001-2006, 2007-2012, and 2013-2016). Spatiotemporal analyses, including Global spatial autocorrelation analysis and Kulldorff's scan statistical analysis, were applied to analyze te spatiotemporal clusters of HFRS at the county level. The results revealed that the spatial extent of the HFRS epidemic in the Hebei province changed dynamically from 2001 to 2016, which indicated that a comprehensive preventative strategy should be implemented in the northeastern regions of the Hebei province in spring., (© 2018 Wiley Periodicals, Inc.)

Zoonotic diseases are challenging to study from the ecological point of view as, broadly speaking, datasets tend to be either detailed on a small spatial extent, or coarse on a large spatial extent. Also, there are many ways to assess zoonotic disease transmission systems, from pathogens to hosts to humans. We explore the complementarity of datasets considering the pathogen in its host, the host and human cases in the context of Puumala orthohantavirus infection in Germany. We selected relevant environmental predictors using a conceptual framework based on resource-based habitats. This framework assesses the functions, and associated environmental resources of the pathogen and associated host. A resource-based habitat framework supports variable selection and result interpretation. Multiplying 'keyholes' to view a zoonotic disease transmission system is valuable, but requires a strong conceptual framework to select and interpret environmental explanatory variables. This study highlights the usefulness of a structured, ecology-based approach to study drivers of zoonotic diseases at the level of virus, host, and human - not only for PUUV but also for other zoonotic pathogens. Our results show that human disease cases are best explained by a combination of variables related to zoonotic pathogen circulation and human exposure.

Background: The potential effect of the inactivated hantavirus vaccine (IHV) remains controversial; however, it appears to be moderately effective for patients at high risk of hemorrhagic fever with renal syndrome (HFRS). This study of the epidemiology of HFRS from 2001 to 2017 aimed to examine those at high risk of HFRS in the Republic of Korea (ROK), particularly in terms of disease distribution according to age., Methods: Raw data of HFRS patients recorded in Korea from 2001 to 2017 were obtained from the Korean Center for Disease Control and Prevention. Patients were divided into three age groups: ≤39, 40-69, and ≥ 70 years. The incidence rate per 100,000 individuals in each age group was calculated using population data. The 12-month year was divided into three-month quarters, and the number and proportion of patients corresponding to each quarter were calculated. The effects of time, sex, and quarter on HFRS incidence were assessed in a Poisson regression analysis., Results: From 2001 to 2017, 7048 HFRS patients were recorded nationwide. Among these patients, the proportion of patients aged ≥70 years increased gradually from 16.4% in 2001 to 43.9% in 2017. Regarding the quarter-year periods, the fourth quarter contained a significantly higher proportion of patients in the ≥70 years group (69.4%) compared to the other age groups. In the Poisson regression analysis, patients aged ≥70 years had a significantly higher relative risk of HFRS incidence within each quartile compared to those in the other age groups (2.102- and 10.029-fold in the third and fourth quarters, respectively). An analysis of disease incidence revealed a more distinct pattern in seasonal variation among those aged ≥70 years compared with other age groups., Conclusions: In this study of the incidence of HFRS in the ROK, subjects aged ≥70 years exhibited a gradual increase in incidence and a distinct pattern of seasonal variation. These results may be important to identify individuals in Korea who are at high risk of developing HFRS. In future, active immunization programs will be needed to control HFRS among these high-risk groups in Korea.

Background: Hemorrhagic fever with renal syndrome (HFRS) is a zoonosis caused by hantavirus (belongs to Hantaviridae family). A large amount of HFRS cases occur in China, especially in the Heilongjiang Province, raising great concerns regarding public health. The distribution of these cases across space-time often exhibits highly heterogeneous characteristics. Hence, it is widely recognized that the improved mapping of heterogeneous HFRS distributions and the quantitative assessment of the space-time disease transition patterns can advance considerably the detection, prevention and control of epidemic outbreaks., Methods: A synthesis of space-time mapping and probabilistic logic is proposed to study the distribution of monthly HFRS population-standardized incidences in Heilongjiang province during the period 2005-2013. We introduce a class-dependent Bayesian maximum entropy (cd-BME) mapping method dividing the original dataset into discrete incidence classes that overcome data heterogeneity and skewness effects and can produce space-time HFRS incidence estimates together with their estimation accuracy. A ten-fold cross validation analysis is conducted to evaluate the performance of the proposed cd-BME implementation compared to the standard class-independent BME implementation. Incidence maps generated by cd-BME are used to study the spatiotemporal HFRS spread patterns. Further, the spatiotemporal dependence of HFRS incidences are measured in terms of probability logic indicators that link class-dependent HFRS incidences at different space-time points. These indicators convey useful complementary information regarding intraclass and interclass relationships, such as the change in HFRS transition probabilities between different incidence classes with increasing geographical distance and time separation., Results: Each HFRS class exhibited a distinct space-time variation structure in terms of its varying covariance parameters (shape, sill and correlation ranges). Given the heterogeneous features of the HFRS dataset, the cd-BME implementation demonstrated an improved ability to capture these features compared to the standard implementation (e.g., mean absolute error: 0.19 vs. 0.43 cases/105 capita) demonstrating a point outbreak character at high incidence levels and a non-point spread character at low levels. Intraclass HFRS variations were found to be considerably different than interclass HFRS variations. Certain incidence classes occurred frequently near one class but were rarely found adjacent to other classes. Different classes may share common boundaries or they may be surrounded completely by another class. The HFRS class 0-68.5% was the most dominant in the Heilongjiang province (covering more than 2/3 of the total area). The probabilities that certain incidence classes occur next to other classes were used to estimate the transitions between HFRS classes. Moreover, such probabilities described the dependency pattern of the space-time arrangement of HFRS patches occupied by the incidence classes. The HFRS transition probabilities also suggested the presence of both positive and negative relations among the main classes. The HFRS indicator plots offer complementary visualizations of the varying probabilities of transition between incidence classes, and so they describe the dependency pattern of the space-time arrangement of the HFRS patches occupied by the different classes., Conclusions: The cd-BME method combined with probabilistic logic indicators offer an accurate and informative quantitative representation of the heterogeneous HFRS incidences in the space-time domain, and the results thus obtained can be interpreted readily. The same methodological combination could also be used in the spatiotemporal modeling and prediction of other epidemics under similar circumstances., Competing Interests: The authors have declared that no competing interests exist.

Hantavirus is the causative agent of hemorrhagic fever with renal syndrome (HFRS). Heilongjiang Province is experiencing an epidemic of HFRS, the main causative agent is a variant of hantavirus called Seoul virus (SEOV). In this study, the entire genome of one SEOV, the DN2 strain, was sequenced and analyzed. The alignment analysis of the sequences indicated that the DN2 strain shares the highest homology with the SEOV-LYO852 strain. The nucleotide identity is 97.6% for the S segment, 97.7% for the M segment, and 98.0% for the L segment. The corresponding amino acid sequence homologies are 99.1%, 98.9% and 99.8%. The phylogenetic analysis of the segments suggests that the DN2 strain has a high genetic relationship with SEOV strains and no genetic recombination occurs.

Background: Hemorrhagic fever with renal syndrome (HFRS) occupies a leading place among natural focal human diseases in the Russian Federation. Sporadic incidence of HFRS-Sochi has been annually recorded in the Krasnodar Territory since 2000. The group outbreak of the HFRS-Sochi was first registered in Gelendzhik in the fall of 2013., Methods: Serological methods were used: indirect immunofluorescence, enzyme immunoassay, FRNT in Vero cells, and methods for the viral RNA detection: PCR and RT-PCR., Results: Data of clinical, epidemiological, immunological and molecular studies of 3 out of 4 cases in HFRS-Sochi outbreak are presented. Severity of the disease correlated with early gastrointestinal disorders appearance. Patient MA gastrointestinal disorders were joined on day 3 of a fever. Clinical and laboratory studies revealed signs of kidneys, liver, pancreas damage, bilateral hydrothorax, bilateral polysegmental pneumonia and polyneuropathy. As a result of long-term treatment, the patient recovered. Patient AA had gastrointestinal disturbances the next day after fever onset. The patient was not saved, despite early hospitalization. Hantavirus antigen and RNA were detected in the lung tissues 2 out of 10 Black-Sea field mice captured in the affected area, as well as in the organs of deceased patient. The most severe clinical course of the disease in close relatives, son and father, with a fatal outcome in the latter case may be the result of genetic features. The severity and outcome of the disease was not depend on day of hospitalization and correlated with the early manifestations of gastrointestinal disorders., Conclusions: Presented data confirm high virulence and pantropism of the Sochi virus, as well as the epidemiological role of Black-Sea field mouse (Apodemus ponticus) as the host of the Sochi virus and the source of human infection., Competing Interests: The authors declare no conflict of interest.

Hemorrhagic fever with renal syndrome (HFRS) is a naturally-occurring, fecally transmitted disease caused by a Hantavirus (HV). It is extremely damaging to human health and results in many deaths annually, especially in Hubei Province, China. One of the primary characteristics of HFRS is the spatiotemporal heterogeneity of its occurrence, with notable seasonal differences. In view of this heterogeneity, the present study suggests that there is a need to focus on trend simulation and the spatiotemporal prediction of HFRS outbreaks. To facilitate this, we constructed a new Seasonal Difference Space-Time Autoregressive Integrated Moving Average (SD-STARIMA) model. The SD-STARIMA model is based on the spatial and temporal characteristics of the Space-Time Autoregressive Integrated Moving Average (STARMA) model first developed by Cliff and Ord in 1974, which has proven useful in modelling the temporal aspects of spatially located data. This model can simulate the trends in HFRS epidemics, taking into consideration both spatial and temporal variations. The SD-STARIMA model is also able to make seasonal difference calculations to eliminate temporally non-stationary problems that are present in the HFRS data. Experiments have demonstrated that the proposed SD-STARIMA model offers notably better prediction accuracy, especially for spatiotemporal series data with seasonal distribution characteristics., Competing Interests: The authors have declared that no competing interests exist.

The transmission pattern of hemorrhagic fever with renal syndrome (HFRS) is associated with environmental conditions, including meteorological factors and land-cover. In the present study, the association between HFRS and environmental factors (including maximum temperature, relative humidity, rainfall, and normalized difference vegetation index) were explored in two typical counties in Northeast and two counties in Northwest China with severe HFRS outbreaks by using seasonal autoregressive integrated moving average model with exogenous variables (SARIMAX). The results showed that rainfall with 3- to 4-month lag was closely associated with HFRS in the two counties in Northeast China, whereas relative humidity with 1- or 5-month lag significantly impacts HFRS transmission in the two counties in Northwest China. Moreover, the SARIMAX models exhibit accurate forecasting ability of HFRS cases. Our findings provide scientific support for local HFRS monitoring and control, and the development of a HFRS early warning system.

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused mainly by two hantaviruses in China: Hantaan virus and Seoul virus. Environmental factors can significantly affect the risk of contracting hantavirus infections, primarily through their effects on rodent population dynamics and human-rodent contact. We aimed to clarify the environmental risk factors favoring rodent-to-human transmission to provide scientific evidence for developing effective HFRS prevention and control strategies. The 10-year (2006-2015) field surveillance data from the rodent hosts for hantavirus, the epidemiological and environmental data extracted from satellite images and meteorological stations, rodent-to-human transmission rates and impacts of the environment on rodent community composition were used to quantify the relationships among environmental factors, rodent species and HFRS occurrence. The study included 709 cases of HFRS. Rodent species in Chenzhou, a hantavirus hotspot, comprise mainly Rattus norvegicus, Mus musculus, R. flavipectus and some other species (R. losea and Microtus fortis calamorum). The rodent species played different roles across the various land types we examined, but all of them were associated with transmission risks. Some species were associated with HFRS occurrence risk in forest and water bodies. R. norvegicus and R. flavipectus were associated with risk of HFRS incidence in grassland, whereas M. musculus and R. flavipectus were associated with this risk in built-on land. The rodent community composition was also associated with environmental variability. The predictive risk models based on these significant factors were validated by a good-fit model, where: cultivated land was predicted to represent the highest risk for HFRS incidence, which accords with the statistics for HFRS cases in 2014-2015. The spatial heterogeneity of HFRS disease may be influenced by rodent community composition, which is associated with local environmental conditions. Therefore, future work should focus on preventing HFRS is moist, warm environments., Competing Interests: The authors have declared that no competing interests exist.

Hemorrhagic fever with renal syndrome (HFRS) caused by hantaviruses is a serious public health problem in China, accounting for 90% of HFRS cases reported globally. In this study, we applied geographical information system (GIS), spatial autocorrelation analyses and a seasonal autoregressive-integrated moving average (SARIMA) model to describe and predict HFRS epidemic with the objective of monitoring and forecasting HFRS in mainland China. Chinese HFRS data from 2004 to 2016 were obtained from National Infectious Diseases Reporting System (NIDRS) database and Chinese Centre for Disease Control and Prevention (CDC). GIS maps were produced to detect the spatial distribution of HFRS cases. The Moran's I was adopted in spatial global autocorrelation analysis to identify the integral spatiotemporal pattern of HFRS outbreaks, while the local Moran's Ii was performed to identify 'hotspot' regions of HFRS at province level. A fittest SARIMA model was developed to forecast HFRS incidence in the year 2016, which was selected by Akaike information criterion and Ljung-Box test. During 2004-2015, a total of 165 710 HFRS cases were reported with the average annual incidence at province level ranged from 0 to 13.05 per 100 000 persons. Global Moran's I analysis showed that the HFRS outbreaks presented spatially clustered distribution, with the degree of cluster gradually decreasing from 2004 to 2009, then turned out to be randomly distributed and reached lowest point in 2012. Local Moran's Ii identified that four provinces in northeast China contributed to a 'high-high' cluster as a traditional epidemic centre, and Shaanxi became another HFRS 'hotspot' region since 2011. The monthly incidence of HFRS decreased sharply from 2004 to 2009 in mainland China, then increased markedly from 2010 to 2012, and decreased again since 2013, with obvious seasonal fluctuations. The SARIMA ((0,1,3) × (1,0,1)12) model was the most fittest forecasting model for the dataset of HFRS in mainland China. The spatiotemporal distribution of HFRS in mainland China varied in recent years; together with the SARIMA forecasting model, this study provided several potential decision supportive tools for the control and risk-management plan of HFRS in China.