Analysis of Hemorrhagic Fever With Renal Syndrome Using Wavelet Tools in Mainland China, 2004-2019

Scientometric analysis of research trends in hemorrhagic fever with renal syndrome: A historical review and network visualization

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS) research has undergone significant global transformation over the past decades. A comprehensive scientometric overview of research trends and scholarly cooperation in HFRS is absent. This study employs scientometric analysis to map the evolution of research themes, identify widely and scarcely explored areas, and anticipate future research directions.

METHODS

We searched Web of Science Core Collection from inception until July 31, 2023, identifying 3908 HFRS-related studies published for analysis. Utilizing CiteSpace, VOSviewer, and Bibliometrix, we performed co-authorship, co-occurrence, and co-citation analyses, and visualized research networks.

RESULTS

Our analysis revealed a consistent upward trend in HFRS publications since 1980, with an average growth rate of 11.34 %. The United States led in publication and citation counts, followed by China, Finland, Germany, and Sweden. Through co-occurrence analysis, we categorized keywords into eight clusters and 24 sub-clusters, revealing six predominant research themes: Clinical Features, Epidemiology, Mechanisms, Virus, Evolution, and Host. Notably, while themes such as Virus and Pathogenesis have been extensively studied, others, including certain aspects of Host research and Environmental Factors, remain less explored.

CONCLUSION

This scientometric synthesis provides a global perspective on the breadth and depth of HFRS research, highlighting well-trodden and understudied areas. It offers a roadmap for researchers to navigate the evolving landscape of HFRS studies and prioritize areas ripe for future investigation.

Epidemiological Characteristics of Hemorrhagic Fever with Renal Syndrome in Longyou County, China

(1) Background: We aimed to analyze the epidemiological characteristics of hemorrhagic fever with renal syndrome (HFRS) in Longyou County and to provide a basis for the future response to this disease. (2) Methods: Data on hemorrhagic fever and host animals were collected from 2011 to 2023. Descriptive methods were used to analyze the epidemic. The R4.4.1 software was used to show how the host density relates to the virus levels, temperature, and rainfall and to predict the host density. (3) Results: We observed 58 cases of hemorrhagic fever, the majority of which occurred in farmers. There were two incidence peaks each year during the spring and winter seasons, accounting for 22.41% and 43.10% of the total cases, respectively. The outdoor rodent population density was significantly and positively correlated with the outdoor rodent virus prevalence (R2 = 0.9411), serving as a robust predictor of the outdoor rodent virus prevalence. Additionally, the density of outdoor rodents exhibited a strong nonlinear relationship with the temperature and precipitation. (4) Conclusions: After hemorrhagic fever vaccination, rodent population density control, and rodent carrier rodent control from 1995 to 2000, the hemorrhagic fever epidemic was generally stable, and the epidemiological characteristics remained stable. In the future, we should continue to take active and effective comprehensive measures to intervene, further realize the effective control of HFRS, and prevent the recurrence of hemorrhagic fever epidemics.

Incidence rate of hemorrhagic fever with renal syndrome complicated with acute pancreatitis: a meta-analysis

Background

Acute pancreatitis (AP) is a rare but serious complication in patients diagnosed with hemorrhagic fever with renal syndrome (HFRS). When AP complicates HFRS, the clinical outcome significantly worsens and the risk of mortality increases. However, the incidence of AP in HFRS patients and its associated mortality risk remain unclear. To address this knowledge gap, we conducted a meta-analysis to determine the AP incidence rate in HFRS patients and assess the impact of AP on mortality in these patients.

Methods

We systematically searched seven databases (PubMed, Web of Science, EMBase, Sinomed, Chinese National Knowledge Infrastructure, WanFang Data, and Chongqing VIP) for relevant studies on HFRS complicated by AP. The studies were selected using predefined inclusion and exclusion criteria based on the Population, Intervention, Comparison, Outcome, and Study design principle. Two independent reviewers screened the studies, and the quality of the included studies was assessed using the Agency for Healthcare Research and Quality and the Newcastle-Ottawa Evaluation Scale (NOS).

Results

In total, 11 studies, encompassing 1,218 HFRS patients, met the inclusion criteria. The overall incidence of HFRS complicated by AP was 8.5% (95% CI for r 5.9-11.1%). The HFRS patients with AP had a significantly higher risk of mortality than those without AP (OR = 3.668, 95% CI for OR 1.112-12.031). No statistically significant differences were observed in the subgroup and meta-regression analyses.

Conclusion

Although the incidence of AP in HFRS patients is not high, it significantly increases the risk of mortality in these patients. Future large-scale prospective studies are required to further validate these findings.

Using empirical dynamic modeling to identify the impact of meteorological factors on hemorrhagic fever with renal syndrome in Weifang, Northeastern China, from 2011 to 2020

BACKGROUND

Hemorrhagic Fever with Renal Syndrome (HFRS) continues to pose a significant public health threat to the well-being of the population. Given that the spread of HFRS is susceptible to meteorological factors, we aim to probe into the meteorological drivers of HFRS. Thus, novel techniques that can discern time-delayed non-linear relationships from nonlinear dynamical systems are compulsory.

METHODS

We analyze the epidemiological features of HFRS in Weifang City, 2011-2020, via the employment of the Empirical Dynamic Modeling (EDM) method. Our analysis delves into the intricate web of time-delayed non-linear associations between meteorological factors and HFRS. Additionally, we investigate the repercussions of minor perturbations in meteorological variables on future HFRS incidence.

RESULTS

A total of 2515 HFRS cases were reported in Weifang from 2011 to 2020. The number of cases per week was 4.81, and the average weekly incidence was 0.52 per 1,000,000. The propagation of HFRS is significantly impacted by the mean weekly temperature, relative humidity, cumulative rainfall, and wind speed, and the ρCCM converges to 0.55,0.48,0.38 and 0.39, respectively. The graphical representation of the relationship between temperature (lagged by 2 weeks) and the incidence of HFRS exhibits an inverted U-shaped curve, whereby the incidence of HFRS culminates as the temperature reaches 10 °C. Moreover, temperature, relative humidity, cumulative rainfall, and wind speed exhibit a positive correlation with HFRS incidence, with a time lag of 4-6 months.

CONCLUSIONS

Our discoveries suggest that meteorological factors can drive the transmission of HFRS both at a macroscopic and microscopic scale. Prospective alterations in meteorological conditions, for instance, elevations in temperature, relative humidity, and precipitation will instigate an upsurge in the incidence of HFRS after 4-6 months, and thus, timely public health measures should be taken to mitigate these changes.

Construction of an early differentiation diagnosis model for patients with severe fever with thrombocytopenia syndrome and hemorrhagic fever with renal syndrome

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with a high mortality rate. Differentiating between SFTS and hemorrhagic fever with renal syndrome (HFRS) is difficult and inefficient. Retrospective analysis of the medical records of individuals with SFTS and HFRS was performed. Clinical and laboratory data were compared, and a diagnostic model was developed based on multivariate logistic regression analyzes. Receiver operating characteristic curve analysis was used to evaluate the diagnostic model. Among the 189 patients, 113 with SFTS and 76 with HFRS were enrolled. Univariate analysis revealed that more than 20 variables were significantly associated with SFTS. Multivariate logistic regression analysis revealed that gender, especially female gender (odds ratio [OR]: 4.299; 95% confidence interval [CI]: 1.163-15.887; p = 0.029), age ≥65 years (OR: 16.386; 95% CI: 3.043-88.245; p = 0.001), neurological symptoms (OR: 12.312; 95% CI: 1.638-92.530; p = 0.015), leukopenia (<4.0 × 109/L) (OR: 17.355; 95% CI: 3.920-76.839; p < 0.001), and normal Cr (OR: 97.678; 95% CI: 15.483-616.226; p < 0.001) were significantly associated with SFTS but not with HFRS. The area under the curve of the differential diagnostic model was 0.960 (95% CI: 0.936-0.984), which was significantly better than that of each single factor. In addition, the model exhibited very excellent sensitivity and specificity (92.9% and 85.5%, respectively). In cases where HFRS and SFTS are endemic, a diagnostic model based on five parameters, such as gender, age ≥65 years, neurological symptoms, leukopenia and normal Cr, will facilitate the differential diagnosis of SFTS and HFRS in medical institutions, especially in primary care settings.

Visual analysis of global hemorrhagic fever with renal syndrome research from 1980 to 2022: Based on CiteSpace and VOSviewer

OBJECTIVE

The development and current state of hemorrhagic fever with renal syndrome (HFRS) over the past 40 years are analyzed in this study, along with explored and discovered the hotspots and frontiers in the field, which serve as the foundation for future investigation.

METHODS

CiteSpace and VOSviewer analysis software were used to visually analyze the literature data on HFRS from 1980 to 2022, including the annual number of publications, countries and research institutions, authors, co-cited literature and keywords.

RESULTS

The number of pertinent papers published in the field of HFRS displayed an overall upward trend from 1980 to 2022. The United States, China, Germany, Sweden, and France are the top 5 countries in terms of publishing volume, with high intermediate centrality mainly concentrated in Europe and the United States. The top 10 co-occurring keywords were hemorrhagic fever, renal syndrome, infection, virus, epidemic, nephropathia epidemical, disease, hantavirus, outbreak, and transmission. According to keyword cluster analysis, there were 4 main research fields. In the HFRS-related study, there were mainly 21 notable keywords and "Korean hemorrhagic fever" had the highest hemorrhagic value (28.87).

CONCLUSION

The United States, China, Germany, Sweden and other countries attached great importance to the HFRS-related research. Moreover, the collaboration between authors and institutions in various collaborator clusters should be strengthened. In recent decades, investigations have focused on the study of viral infection and the clinical symptoms and pathophysiology of HFRS. Future research may concentrate on factors affecting host population distribution and density, such as vaccine development and meteorological factors pertaining to virus transmission.

Comparison of simulation and predictive efficacy for hemorrhagic fever with renal syndrome incidence in mainland China based on five time series models

Background

Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic infectious disease commonly found in Asia and Europe, characterized by fever, hemorrhage, shock, and renal failure. China is the most severely affected region, necessitating an analysis of the temporal incidence patterns in the country.

Methods

We employed Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Nonlinear AutoRegressive with eXogenous inputs (NARX), and a hybrid CNN-LSTM model to model and forecast time series data spanning from January 2009 to November 2023 in the mainland China. By comparing the simulated performance of these models on training and testing sets, we determined the most suitable model.

Results

Overall, the CNN-LSTM model demonstrated optimal fitting performance (with Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute Error (MAE) of 93.77/270.66, 7.59%/38.96%, and 64.37/189.73 for the training and testing sets, respectively, lower than those of individual CNN or LSTM models).

Conclusion

The hybrid CNN-LSTM model seamlessly integrates CNN's data feature extraction and LSTM's recurrent prediction capabilities, rendering it theoretically applicable for simulating diverse distributed time series data. We recommend that the CNN-LSTM model be considered as a valuable time series analysis tool for disease prediction by policy-makers.

Epidemiology of Hemorrhagic Fever with Renal Syndrome and Host Surveillance in Zhejiang Province, China, 1990-2021

Hemorrhagic fever with renal syndrome (HFRS) is caused by hantaviruses (HVs) and is endemic in Zhejiang Province, China. In this study, we aimed to explore the changing epidemiology of HFRS cases and the dynamics of hantavirus hosts in Zhejiang Province. Joinpoint regression was used to analyze long-term trends in the incidence of HFRS. The comparison of animal density at different stages was conducted using the Mann-Whitney Test. A comparison of HV carriage rates between stages and species was performed using the chi-square test. The incidence of HFRS shows a continuous downward trend. Cases are widely distributed in all counties of Zhejiang Province except Shengsi County. There was a high incidence belt from west to east, with low incidence in the south and north. The HFRS epidemic showed two seasonal peaks in Zhejiang Province, which were winter and summer. It showed a marked increase in the age of the incidence population. A total of 23,073 minibeasts from 21 species were captured. Positive results were detected in the lung tissues of 14 rodent species and 1 shrew species. A total of 80% of the positive results were from striped field mice and brown rats. No difference in HV carriage rates between striped field mice and brown rats was observed (χ2 = 0.258, p = 0.611).

Investigation of a subunit protein vaccine for HFRS based on a consensus sequence between envelope glycoproteins of HTNV and SEOV

Due to the global resurgence of hemorrhagic fever with renal syndrome (HFRS), more attention is being focused on this dangerous illness. In China and Korea, the only vaccines available are the virus-inactivated vaccine against Hantaan virus (HTNV) or Seoul virus (SEOV), but their efficacy and safety are inadequate. Therefore, it is important to develop new vaccines that are safer and more efficient to neutralize and regulate areas with a high prevalence of HFRS. We employed bioinformatics methods to design a recombinant protein vaccine based on conserved regions of protein consensus sequences in HTNV and SEOV membranes. The S2 Drosophila expression system was utilized to enhance protein expression, solubility and immunogenicity. After the Gn and Gc proteins of HTNV and SEOV were successfully expressed, mice were immunized, and the humoral immunity, cellular immunity, and in vivo protection of the HFRS universal subunit vaccine were systematically evaluated in mouse models. These results indicated that the HFRS subunit vaccine generated elevated levels of binding and neutralizing antibodies, particularly IgG1, compared to that of the traditional inactivated HFRS vaccine. Additionally, the spleen cells of immunized mice secreted IFN-r and IL-4 cytokines effectively. Moreover, the HTNV-Gc protein vaccine successfully protected suckling mice from HTNV infection and stimulated GC responses. In this research, a new scientific approach is investigated to develop a universal HFRS subunit protein vaccine that is capable of producing effective humoral and cellular immunity in mice. The results suggest that this vaccine could be a promising candidate for preventing HFRS in humans.

The Spatiotemporal Pattern and Its Determinants of Hemorrhagic Fever With Renal Syndrome in Northeastern China: Spatiotemporal Analysis

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS) is a significant zoonotic disease mainly transmitted by rodents. However, the determinants of its spatiotemporal patterns in Northeast China remain unclear.

OBJECTIVE

This study aimed to investigate the spatiotemporal dynamics and epidemiological characteristics of HFRS and detect the meteorological effect of the HFRS epidemic in Northeastern China.

METHODS

The HFRS cases of Northeastern China were collected from the Chinese Center for Disease Control and Prevention, and meteorological data were collected from the National Basic Geographic Information Center. Times series analyses, wavelet analysis, Geodetector model, and SARIMA model were performed to identify the epidemiological characteristics, periodical fluctuation, and meteorological effect of HFRS in Northeastern China.

RESULTS

A total of 52,655 HFRS cases were reported in Northeastern China from 2006 to 2020, and most patients with HFRS (n=36,558, 69.43%) were aged between 30-59 years. HFRS occurred most frequently in June and November and had a significant 4- to 6-month periodicity. The explanatory power of the meteorological factors to HFRS varies from 0.15 ≤ q ≤ 0.01. In Heilongjiang province, mean temperature with a 4-month lag, mean ground temperature with a 4-month lag, and mean pressure with a 5-month lag had the most explanatory power on HFRS. In Liaoning province, mean temperature with a 1-month lag, mean ground temperature with a 1-month lag, and mean wind speed with a 4-month lag were found to have an effect on HFRS, but in Jilin province, the most important meteorological factors for HFRS were precipitation with a 6-month lag and maximum evaporation with a 5-month lag. The interaction analysis of meteorological factors mostly showed nonlinear enhancement. The SARIMA model predicted that 8,343 cases of HFRS are expected to occur in Northeastern China.

CONCLUSIONS

HFRS showed significant inequality in epidemic and meteorological effects in Northeastern China, and eastern prefecture-level cities presented a high risk of epidemic. This study quantifies the hysteresis effects of different meteorological factors and prompts us to focus on the influence of ground temperature and precipitation on HFRS transmission in future studies, which could assist local health authorities in developing HFRS-climate surveillance, prevention, and control strategies targeting high-risk populations in China.

Potential distribution of Leptotrombidium scutellare in Yunnan and Sichuan Provinces, China, and its association with mite-borne disease transmission

BACKGROUND

Leptotrombidium scutellare is one of the six main vectors of scrub typhus in China and is a putative vector of hemorrhagic fever with renal syndrome (HFRS). This mite constitutes a large portion of the chigger mite community in southwest China. Although empirical data on its distribution are available for several investigated sites, knowledge of the species' association with human well-being and involvement in the prevalence of mite-borne diseases remains scarce.

METHODS

Occurrence data on the chigger mite were obtained from 21 years (2001-2021) of field sampling. Using boosted regression tree (BRT) ecological models based on climate, land cover and elevation variables, we predicted the environmental suitability for L. scutellare in Yunnan and Sichuan Provinces. The potential distribution range and shifts in the study area for near-current and future scenarios were mapped and the scale of L. scutellare interacting with human activities was evaluated. We tested the explanatory power of the occurrence probability of L. scutellare on incidences of mite-borne diseases.

RESULTS

Elevation and climate factors were the most important factors contributing to the prediction of the occurrence pattern of L. scutellare. The most suitable habitats for this mite species were mainly concentrated around high-elevation areas, with predictions for the future showing a trend towards a reduction. Human activity was negatively correlated with the environmental suitability of L. scutellare. The occurrence probability of L. scutellare in Yunnan Province had a strong explanatory power on the epidemic pattern of HFRS but not scrub typhus.

CONCLUSIONS

Our results emphasize the exposure risks introduced by L. scutellare in the high-elevation areas of southwest China. Climate change may lead to a range contraction of this species towards areas of higher elevation and lessen the associated exposure risk. A comprehensive understanding of the transmission risk requires more surveillance efforts.

Hemorrhagic Fever with Renal Syndrome in Asia: History, Pathogenesis, Diagnosis, Treatment, and Prevention

Hemorrhagic Fever with Renal Syndrome (HFRS) is the most frequently diagnosed zoonosis in Asia. This zoonotic infection is the result of exposure to the virus-contaminated aerosols. Orthohantavirus infection may cause Hemorrhagic Fever with Renal Syndrome (HRFS), a disease that is characterized by acute kidney injury and increased vascular permeability. Several species of orthohantaviruses were identified as causing infection, where Hantaan, Puumala, and Seoul viruses are most common. Orthohantaviruses are endemic to several Asian countries, such as China, South Korea, and Japan. Along with those countries, HFRS tops the list of zoonotic infections in the Far Eastern Federal District of Russia. Recently, orthohantavirus circulation was demonstrated in small mammals in Thailand and India, where orthohantavirus was not believed to be endemic. In this review, we summarized the current data on orthohantaviruses in Asia. We gave the synopsis of the history and diversity of orthohantaviruses in Asia. We also described the clinical presentation and current understanding of the pathogenesis of orthohantavirus infection. Additionally, conventional and novel approaches for preventing and treating orthohantavirus infection are discussed.

Dual seasonal pattern for hemorrhagic fever with renal syndrome and its potential determinants in China

Hemorrhagic fever with renal syndrome (HFRS) continued to affect human health across Eurasia, which complicated by climate change has posed a challenge for the disease prevention measures. Nation-wide surveillance data of HFRS cases were collected during 2008-2020.The seasonality and epidemiological features were presented by combining the HFRS incidence and the endemic types data. Factors potentially involved in affecting incidence and shaping disease seasonality were investigated by generalized additive mixed model, distributed lag nonlinear model and multivariate meta-analysis. A total of 76 cities that reported totally 111,054 cases were analyzed. Three endemic types were determined, among them the Type I cities (Hantaan virus-dominant) were related to higher incidence level, showing one spike every year in Autumn-Winter season; Type II (Seoul virus-dominant) cities were related to lower incidence, showing one spike in Spring, while Type III (Hantaan/Seoul-mixed type) showed dual peaks with incidence lying between. Persistently heavy rainfall had significantly negative influence on HFRS incidence in Hantaan virus-dominant endemic area, while a significantly opposite effect was identified when continuously heavy rainfall induced floods, where temperature and relative humidity affected HFRS incidence via an approximately parabolic or linear manner, however few or no such effects was shown in Seoul virus-dominant endemic areas, which was more vulnerable to temperature variation. Dual seasonal pattern of HFRS was depended on the dominant genotypes of hantavirus, and impact of climate on HFRS was greater in Hantaan virus-dominant endemic areas, than in Seoul virus-dominant areas.

A long-term retrospective analysis of the haemorrhagic fever with renal syndrome epidemic from 2005 to 2021 in Jiangxi Province, China

Jiangxi is one of the provinces in China most seriously affected by the haemorrhagic fever with renal syndrome (HFRS) epidemic. The aim of this paper was to systematically explore the HFRS epidemic in Jiangxi from the perspective of Hantavirus (HV) prevalence in rodents and humans and virus molecular characteristics. Individual information on all HFRS cases in Jiangxi from 2005 to 2021 was extracted from the China Information System for Disease Control and Prevention. All S and M fragment sequences of the Seoul virus and Hantan virus strains uploaded by Jiangxi and its neighbouring provinces and some representative sequences from provinces in China or some countries of Southeast Asia with the highest HV prevalence were retrieved and downloaded from NCBI GenBank. Periodogram and spatial autocorrelation were adopted for temporal periodicity and spatial clustering analysis of the HFRS epidemic. Joinpoint regression was utilized to explore the changing morbidity trend patterns of HFRS. Multiple sequence alignment and amino acid variation analysis were used to explore the homology and variation of strain prevalence in Jiangxi. Based on monthly morbidity time series, the periodogram analysis showed that the prevalence of HFRS had periodicities of 6 months and 12 months. Spatial autocorrelation analysis showed that HFRS distributed in Jiangxi was not random, with a "High-High" clustering area around Gaoan County. HFRS morbidity among the 0 ~ 15-year-old and ~ 61-year-old or older populations in Jiangxi increased significantly during the period of 2008-2015. Generally, HFRS morbidity was significantly positively correlated with the index of rat with virus (IRV) (r = 0.742) in the counties surrounding Gaoan from 2005 to 2019. HTNV strains in Jiangxi were in one independent branch, while the SEOV strains in Jiangxi were relatively more diverse. Both the YW89-15 and GAW30/2021 strains shared approximately 85% nucleotide homology and approximately 97% amino acid homology with their corresponding standard strains and vaccine strains. GAW30/2021 and YW89-15 had some amino acid site variations in nucleoprotein, glycoprotein precursor and RNA-dependent polymerase with their corresponding vaccine strains Z10 (HTNV) and Z37 (SEOV). The HFRS epidemic in Jiangxi has obvious temporal periodicity and spatial clustering, and the significant increase in the non-Immunization Expanded Program (EPI) targeted population (children and elderly) suggests that HFRS vaccination in this population needs to be considered. Although applying the EPI played a certain role in curbing the incidence of HFRS in Jiangxi from the perspective of ecological epidemiology, HTNV and SEOV strains prevalent in Jiangxi have some amino acid site variations compared to their corresponding vaccine strains, suggesting that HV variation needs to be continuously monitored in the future to observe vaccine protective efficiency.

Bayesian spatiotemporal modelling analysis of hemorrhagic fever with renal syndrome outbreaks in China using R-INLA

Hemorrhagic fever with renal syndrome (HFRS) is a category B infectious disease caused by Hantavirus infection, which can cause acute kidney injury and has a high mortality rate. At present, China is the country most severely afflicted by HFRS in the world, and it is critical to carry out efficient HFRS prevention and management in a scientific and accurate manner. The study used data on the incidence of HFRS in mainland China from 2015 to 2018, built a Bayesian hierarchical spatiotemporal distribution model, and applied the Integrated Nested Laplace Approximation algorithm to analyse the factors influencing the development of HFRS, the spatial and temporal distribution characteristics, and the threshold exceedance locations. The results revealed that the woodland and grassland area (RR = 1.357, 95% CI: 1.005-1.791), economic level (RR = 1.299, 95% CI: 1.007-1.649), and traffic level (RR = 2.442, 95% CI: 1.825-3.199) were all significantly and positively associated with the development of HFRS, with traffic level having the strongest promoting effect. The seasonal cycle was obvious in time, with peaks in May-June and October-December each year, most notably in November. Spatially, there was a south-heavy north-light trend, with a high risk of incidence largely in places rich in mountain and forest vegetation, of which Guizhou, Guangxi, Guangdong, and Jiangxi provinces continuing to have a high incidence in recent years, and the evolution of the epidemic in Hubei and Hunan was becoming more serious. When the early warning threshold was set at 0.2, the detection impact was best, and Guizhou, Guangxi, Guangdong, Jiangxi, Hainan, and Tianjin were positioned near the critical point of the exceedance threshold with the highest risk of incidence. It is recommended that the relevant managers call for active vaccination of outdoor workers, such as those working in agriculture and construction sites, implement rat prevention and extermination before winter arrives, and warn high-risk and medium-high-risk areas to conduct early outbreak surveillance. Move the prevention and control gates forward based on the exceedance threshold for doing preventive and control detection and epidemic research and judgement work.

Spatial-temporal dynamics and time series prediction of HFRS in mainland China: A long-term retrospective study

Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China. The current study aims to characterize the spatial-temporal dynamics of HFRS in mainland China during a long-term period (1950-2018). A total of 1 665 431 cases of HFRS were reported with an average annual incidence of 54.22 cases/100 000 individuals during 1950-2018. The joint regression model was used to define the global trend of the HFRS cases with an increasing-decreasing-slightly increasing-decreasing-slightly increasing trend during the 68 years. Then spatial correlation analysis and wavelet cluster analysis were used to identify four types of clusters of HFRS cases located in central and northeastern China. Lastly, the prophet model outperforms auto-regressive integrated moving average model in the HFRS modeling. Our findings will help reduce the knowledge gap on the transmission dynamics and distribution patterns of the HFRS in mainland China and facilitate to take effective preventive and control measures for the high-risk epidemic area.

The current and future risk of spread of Leptotrombidium deliense and Leptotrombidium scutellare in mainland China

BACKGROUND

The chigger mites Leptotrombidium deliense (L. deliense) and Leptotrombidium scutellare (L. scutellare) are two main vectors of mite-borne diseases in China. However, the associated environmental risk factors are poorly understood, and the potential geographic ranges of the two mite species are unknown.

METHODS

We combined an ensemble boosted regression tree modelling framework with contemporary records of mites and multiple environmental factors to explore the effects of environmental variables on both mites, as well as to predict the current and future environmental suitability distributions of both species. Additionally, the human population living in the potential spread risk zones of each species was also estimated across mainland China.

RESULTS

Our results indicated that climate, land cover, and elevation are significantly associated with the spatial distributions of the two mite species. The current environmental suitability distribution of L. deliense is mainly concentrated in southern China, and that of L. scutellare is mainly distributed in southern and eastern coastal areas. With climate warming, the geographical distribution of the two mites generally tends to expand to the north and northwest. In addition, we estimated that 305.1-447.6 and 398.3-430.7 million people will inhabit the future spread risk zones of L. deliense and L. scutellare, respectively, in mainland China.

CONCLUSIONS

Our findings provide novel insights into understanding the current and future risks of spread of these two mite species and highlight the target zones for helping public health authorities better prepare for and respond to future changes in mite-borne disease risk.

An HFman Probe-Based Multiplex Reverse Transcription Loop-Mediated Isothermal Amplification Assay for Simultaneous Detection of Hantaan and Seoul Viruses

Hantaviruses are zoonotic pathogens that are widely distributed worldwide. Hantaan virus (HTNV) and Seoul virus (SEOV) are two most common hantaviruses that infect humans and cause hemorrhagic fever with renal syndrome (HFRS). Rapid and sensitive detection of HTNV and SEOV are crucial for surveillance, clinical treatment and management of HFRS. This study aimed to develop a rapid HFman probe-based mulstiplex reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay to simultaneously detect HTNV and SEOV. A novel multiplex RT-LAMP assay was developed, and 46 serum samples obtained from clinically suspected patients were used for evaluation. The novel RT-LAMP assay can detect as low as 3 copies/reaction of hantaviruses with a detection limit of 41 and 73 copies per reaction for HTNV and SEOV, respectively. A clinical evaluation showed that the consistencies of the multiplex RT-LAMP with RT-qPCR assay were 100% and 97.8% for HTNV and SEOV, respectively. In view of the high prevalence of HTNV and SEOV in rural areas with high rodent density, a colorimetric visual determination method was also developed for point-of-care testing (POCT) for the diagnosis of the two viruses. The novel multiplex RT-LAMP assay is a sensitive, specific, and efficient method for simultaneously detecting HTNV and SEOV.

Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China

OBJECTIVE

We aim to examine the adequacy of an innovation state-space modeling framework (called TBATS) in forecasting the long-term epidemic seasonality and trends of hemorrhagic fever with renal syndrome (HFRS).

METHODS

The HFRS morbidity data from January 1995 to December 2020 were taken, and subsequently, the data were split into six different training and testing segments (including 12, 24, 36, 60, 84, and 108 holdout monthly data) to investigate its predictive ability of the TBATS method, and its forecasting performance was compared with the seasonal autoregressive integrated moving average (SARIMA).

RESULTS

The TBATS (0.27, {0,0}, -, {<12,4>}) and SARIMA (0,1,(1,3))(0,1,1)12 were selected as the best TBATS and SARIMA methods, respectively, for the 12-step ahead prediction. The mean absolute deviation, root mean square error, mean absolute percentage error, mean error rate, and root mean square percentage error were 91.799, 14.772, 123.653, 0.129, and 0.193, respectively, for the preferred TBATS method and were 144.734, 25.049, 161.671, 0.203, and 0.296, respectively, for the preferred SARIMA method. Likewise, for the 24-, 36-, 60-, 84-, and 108-step ahead predictions, the preferred TBATS methods produced smaller forecasting errors over the best SARIMA methods. Further validations also suggested that the TBATS model outperformed the Error-Trend-Seasonal framework, with little exception. HFRS had dual seasonal behaviors, peaking in May-June and November-December. Overall a notable decrease in the HFRS morbidity was seen during the study period (average annual percentage change=-6.767, 95% confidence intervals: -10.592 to -2.778), and yet different stages had different variation trends. Besides, the TBATS model predicted a plateau in the HFRS morbidity in the next ten years.

CONCLUSION

The TBATS approach outperforms the SARIMA approach in estimating the long-term epidemic seasonality and trends of HFRS, which is capable of being deemed as a promising alternative to help stakeholders to inform future preventive policy or practical solutions to tackle the evolving scenarios.

Epidemiological Characteristics and Regional Risk Prediction of Hemorrhagic Fever with Renal Syndrome in Shandong Province, China

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease caused by different species of hantaviruses, is widely endemic in China. Shandong Province is one of the most affected areas. This study aims to analyze the epidemiological characteristics of HFRS, and to predict the regional risk in Shandong Province.

METHODS

Descriptive statistics were used to elucidate the epidemiological characteristics of HFRS cases in Shandong Province from 2010 to 2018. Based on environmental and socioeconomic data, the boosted regression tree (BRT) model was applied to identify important influencing factors, as well as predict the infection risk zones of HFRS.

RESULTS

A total of 11,432 HFRS cases were reported from 2010 to 2018 in Shandong, with groups aged 31-70 years (81.04%), and farmers (84.44%) being the majority. Most cases were from central and southeast Shandong. There were two incidence peak periods in April to June and October to December, respectively. According to the BRT model, we found that population density (a relative contribution of 15.90%), elevation (12.02%), grassland (11.06%), cultivated land (9.98%), rural settlement (9.25%), woodland (8.71%), and water body (8.63%) were relatively important influencing factors for HFRS epidemics, and the predicted high infection risk areas were concentrated in central and eastern areas of Shandong Province. The BRT model provided an overall prediction accuracy, with an area under the receiver operating characteristic curve of 0.91 (range: 0.83-0.95).

CONCLUSIONS

HFRS in Shandong Province has shown seasonal and spatial clustering characteristics. Middle-aged and elderly farmers are a high-risk population. The BRT model has satisfactory predictive capability in stratifying the regional risk of HFRS at a county level in Shandong Province, which could serve as an important tool for risk assessment of HFRS to deploy prevention and control measures.